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DYNAMIC EVALUATION OF CORRUPTION IN PUBLIC PROJECT
PROCUREMENT: A COMPARATIVE STUDY OF EMERGING AND
ESTABLISHED ECONOMIES.

EMMANUEL KINGSFORD OWUSU

PhD

The Hong Kong Polytechnic University

2020
 The Hong Kong Polytechnic University
Department of Building and Real Estate

Dynamic Evaluation of Corruption in Public Project Procurement: A Comparative

Study of Emerging and Established Economies.

Emmanuel Kingsford Owusu

A thesis submitted in partial fulfilment of the requirements

for the degree of Doctor of Philosophy

MARCH 2020

i
CERTIFICATE OF ORIGINALITY

I hereby declare that this thesis is my own work and that, to the best of my knowledge and
belief, it reproduces no material previously published or written, nor material that has been
accepted for the award of any other degree or diploma, except where due acknowledgment
has been made in the text.

_____________________________ (Signed)

Emmanuel Kingsford Owusu (Name of Student)

ii
 DEDICATION

Salvator Mundi, Iesus Christus.

iii
 "Hi, Emmanuel,
“We just released our Corruption Perceptions Index 2018, and the results are troubling.
This year's index shows that the majority of countries are making little or no progress in ending
corruption. Even worse, it reveals that the continued failure of most countries to significantly control
corruption is contributing to a crisis in democracy around the world."
Transparency International, 2019.

iv
 ABSTRACT

The evolution and dynamism of corrupt practices have not only been tagged as one of the most critical

socio-economic setbacks of governments and institutions but has also been identified to be one of the

unending or cyclical phenomena globally. Public projects are not exempted from the effects of

corruption. On the contrary, they are also greatly affected by the incident of corruption. Given that the

industry responsible for executing public projects (i.e., the construction industry) is noted as the second

most corrupt industry in the world coupled with the procurement process of projects identified as the

most susceptible process to corruption globally. However, even though corruption is a global issue, the

incidence, proliferation, and effects vary from context to context (i.e., from county to county and

institutions to institutions). Anti-corruption advocates and researchers have extended both individual

and collaborative efforts to explore the dynamism and effects of corruption over the past decades and

centuries. However, analogous to a virus, the evolution of corruption never stops. Moreover, while

efforts are being expended in the exploration of corruption in different fields such as sociology,

criminology, business, among others, it forms one of the least research concerns for project

management-related and construction management related scholars. As a result, even though corruption

constitutes one of the topmost critical concerns in the project management and construction

management-related domains, little attention has been devoted in this regard by related scholars,

specifically in the developing context.

Against these backdrops, this research examines this long-standing socio-economic plague in

public infrastructure projects holistically. Specifically, this research explores all prevailing constructs

of corruption in public project planning, procurement, and management. Thus, this study investigates

the various forms of corrupt practices and their associated causal factors of corruption in public

infrastructure projects. It continues with the examination of procurement irregularities or risk indicators

of corruption, anti-corruption measures (ACMs) developed and enforced to extirpate the proliferation

and the effects of corruption, and lastly, the barriers that hamper the efficacy of the existing anti-

corruption measures. This research employs diverse methodological tools and techniques to realize the

v
aim and objectives of this research. They include but not limited to descriptive statistics, fuzzy synthetic

evaluation, social network analysis, among others. Data is gathered from both relevant literature and

the experts identified through non-probabilistic sampling techniques.

The results indicate that the project procurement process in the developing context is

susceptible to corruption. Although the negative constructs (causes of corruption, risk indicators, and

the barriers that hamper the efficacy of ACMs) were revealed to have a significant impact on the

procurement process, none of the anti-corruption measures was identified to be effective. Intensive

efforts are needed to help address the issue of corruption in public projects, especially at the various

stages of the procurement process. The models and framework developed in this research constitute

proposed overarching measures to help address and extirpate corruption prevalent in public projects.

The models developed are intended to help predict and evaluate the incidence and proliferation of

corrupt practices throughout the different phases of the project procurement process with the sole aim

to help fight corruption prevalent in public project procurement. Moreover, the overall framework

developed is intended to inform project parties, anti-corruption activists, contract administrators and

other relevant procurement-related experts about the dynamics and evolution of corrupt practices with

their associated causal factors in projects and the specific efforts to extirpate their influence and effects

throughout the most vulnerable process to corruption globally (i.e., the procurement process).

Keywords: Corruption; Forms of corruption causes; Vulnerability; Public projects; Infrastructure

procurement; Developing and developed context; Ghana; Hong Kong.

vi
LIST OF RESEARCH PUBLICATIONS (Published or Accepted)
1. Owusu, E. K., Chan, A., & Hosseini, M. R. (2020). Impacts of anti-corruption barriers on the
efficacy of anti-corruption measures in infrastructure projects: Implications for sustainable
development. Journal of Cleaner Production, 119078. (Impact Factor = 6.395)

2. Owusu, E. K., Chan, A. P., Ameyaw, E. E., & Robert, O. K. (2020). Evaluating the Effectiveness
of Strategies for Extirpating Corrupt Practices in Infrastructure Project Procurement. ASCE
Journal of Infrastructure Systems, Ref.: ISENG-1519R5. (in press) (Impact Factor = 1.538)

3. Owusu, E. K., Chan, A. P., Yang, J., & Pärn, E. (2020). Towards corruption-free cities:
Measuring the effectiveness of anti-corruption measures in infrastructure project procurement and
management in Hong Kong. Cities, 96, 102435. (Impact Factor = 3.853)

4. Owusu, E. K., Chan, A. P., Hosseini M. R., Nikmehr B., (2020). Assessing Procurement
Irregularities in the Supply-Chain of Ghanaian Construction Projects: A Soft-Computing
Approach. Journal of Civil Engineering and Management. Manuscript ID. SCEM-2019-0215.R1
(In Press). (Impact Factor = 2.029)

5. Owusu, E. K., Chan, A. P., & Ameyaw, E. (2019). Toward a Cleaner Project Procurement:
Evaluation of Construction Projects' Vulnerability to Corruption in Developing Countries.
Journal of Cleaner Production. pp.394-407 (Impact Factor = 6.395)

6. Owusu E. K Chan A. P. C. and Darko A (2018). Owusu, E. K., Chan, A. P., & Darko, A. (2019).
Thematic Overview of Corruption in Infrastructure Procurement Process. ASCE Journal of
Infrastructure Systems, 25(2), 02519001. (Impact Factor = 1.538)

7. Owusu, E. K., & Chan, A. P. (2018). Barriers Affecting Effective Application of Anticorruption
Measures in Infrastructure Projects: Disparities between Developed and Developing Countries.
ASCE Journal of Management in Engineering, 35(1), 04018056. (Impact Factor = 3.269)

8. Owusu, E. K., Chan, A. P., Shan, M., & Pärn, E. (2019). An Empirical Study on Construction
Process Corruption Susceptibility: A Vignette of International Expertise. Science and
Engineering Ethics, 1-25. (Impact Factor = 2.275)

9. Owusu, E. K., Chan, A. P., & Shan, M. (2017). Causal Factors of Corruption in Construction
Project Management: An Overview. Science and engineering ethics, 1-31. (Impact Factor =
2.275)

10. Owusu, E. K., Chan, A. P., DeGraft, O. M., Ameyaw, E. E., & Robert, O. K. (2019). A
contemporary review of anti-corruption measures in construction project management. Project
Management Journal, 50(1), 40-56. (Impact Factor = 2.043)

11. Chan, A. P., & Owusu, E. K. (2017). Corruption Forms in the Construction Industry: Literature
Review. ASCE Journal of Construction Engineering and Management, 143(8), 04017057.
(Corresponding Author) (Impact Factor = 2.734)

11. Darko, A., Chan, A. P. C. & Owusu, E. K. (2018). What are the green technologies for
sustainable housing development? An empirical study in Ghana. Business Strategy &
Development, 1(2), 140-153.

vii
 12. Darko, A., Chan, A. P. C., Ameyaw, E. E., Owusu, E. K., Pärn, E., & Edwards, D. J. (2018).
Review of application of analytic hierarchy process (AHP) in construction. International Journal
of Construction Management, 1-17.

13. Osei - Kyei, R, Chan A. P. C, Danso A, Kuragu K.O, Owusu E. K. (2017) "Motivations for
adopting Unsolicited Proposals for Public-Private Partnership Project Implementation: A survey
of International Experts." Journal of Financial Management of Property and Construction, 23(2).

14. Ekanayake A., Shen Q. P., Kumaraswamy M. M., Owusu E.K. (2020) Identifying Supply Chain
Vulnerabilities in Industrialized Construction: An Overview. International Journal of
Construction Management. DOI: 10.1080/15623599.2020.1728487

Conference Publications (Accepted or Presented)

1. Owusu E. K, Chan A. P. C. (2020). How Critical are the Extant Procurement Systems Prone
to Corruption? An Expert Survey. Royal Institution of Chartered Surveyors COBRA 2020
Conference, Fort Myers, Florida, United States.

2. Owusu E. K, Chan A. P. C. (2020). A Turn to Smart Contracts and Future Applications

Towards Construction Innovation: A Scientometric Review. ASCE Construction Research
Congress (CRC). 8-10 March 2020, Arizona, United States.

3. *Owusu, E. K., Chan, A. P. (2019). Examining the Contextual Disparities of the

Effectiveness of Anti-Corruption Measures in Infrastructure Project Management between
Developed and Developing Regions. International Annual Conference for Integrity - CAII
2019. Lima, Peru

4. Owusu E. K, Chan A. P. C (2019). Investigating the Criticalities of Corruption Forms in

Infrastructure Projects in the Developing Context. Construction in the 21st Century (CITC). 9-
11 September 2019, United Kingdom.

5. Owusu E. K, Chan A. P. C., Siu, M.F. (2019). Dynamic Assessment of Corruption Forms
Throughout Infrastructure Procurement Process: An International Expert Survey. CIB World
Building Congress: Constructing Smart Cities. 17 - 21 June 2019, Hong Kong.

6. Owusu E. K, Chan A. P. C., Darko A (2018). What are the barriers that affect the potency of
anti-corruption measures in construction and infrastructure procurement? A Systematic
Review. Eben, 2018 Research Conference. Corruption and Beyond: Fraudulent Behavior in
and of Corporations. 6-8 September 2018, Vienna, Austria.

7. Owusu E. K, Chan A. P. C. (2017). Anti-Corruption Measures in the Construction Industry:

A state-of-the-art review. 12th Talks at Zittau Concerning Business Ethics: ethical aspects of
corruption, 20-21 October 2017, Dresden, Germany. pp. 26-28

8. Owusu E. K, Chan A. P. C. (2017). Addressing the Multiple Facets of Corruption in

Construction Procurement Research: An Overview. 16th International Council for Research
and Innovation in Building and Construction, Students' Chapter Conference. Schengen,
China.

viii
9. Owusu E. K, Chan A. P. C. (2017). A Longitudinal Review of the Evolution and Variants of
Corruption in Infrastructure Procurement. Conference on Interdisciplinary and Comparative
Learning: Positioning the Young Scholar for Excellence in The Age of Shifting Educational
Paradigm, Lingnan University, Hong Kong

10. Darko A., Chan A.P, Owusu E.K., and Antwi-Afari M.F. (2018) Benefits of Green Building:
A Review. Royal Institution of Chartered Surveyors COBRA 2018 Conference, London, UK.

11. Nwaogu J.M., Chan A.P.C, Owusu E.K. (2019) Barriers and motivators to electronic and
mobile Health (e&mHealth) interventions in mental illness management amongst
construction workers. CIB World Building Congress: Constructing Smart Cities. 17 - 21 June
2019, Hong Kong.
12. Ma X., Chan A.P.C., Owusu E.K., Xiong F., Dong N. (2020). Contextualizing the
institutional changes in BIM-based construction: a comparison of BIM-attached and BIM-
integrated projects. ASCE Construction Research Congress (CRC). 8-10 March 2020,
Arizona, United States.4

Book(s) (Monograph)
• Owusu E. K and Chan A. P. C. (2019) Corruption in Infrastructure Procurement
Addressing the Dynamic Criticalities. (Taylor and Francis. Contract No. 185422).

Invited Speaker Presentations (*)

1. *Owusu, E. K., Chan, A. P. (2019). Examining the Contextual Disparities of the

Effectiveness of Anti-Corruption Measures in Infrastructure Project Management between
Developed and Developing Regions. International Annual Conference for Integrity - CAII
2019. Lima, Peru

2. *Owusu, E. K., Chan, A. P., Yang, J., & Pärn, E. (2019). Towards corruption-free cities:
Measuring the effectiveness of anti-corruption measures in infrastructure project procurement
and management in Hong Kong (16 September 2019). Independent Commission Against
Corruption (ICAC), Hong Kong

3. *Owusu, E. K., & Chan, A. P. (2018). Barriers Affecting Effective Application of

Anticorruption Measures in Infrastructure Projects: Disparities between Developed and
Developing Countries. Research Seminar, Hong Kong Polytechnic University, Hong Kong.

Completed Works (Under Review)

1. Owusu, E.K., Chan A.P.C., Darko, A. (2020). Evaluating the Corruption Susceptibility
Index of Infrastructure Procurement and Management in the Developed Context: The
Case of Hong Kong. ASCE Journal of Infrastructure Systems, (Manuscript ID: ISENG-1717)

ix
 2. Owusu, E.K., Chan A.P.C. (2020). Extirpating Corruption in Urban Infrastructure
Procurement: The Dynamic Criticalities and the Way Forward. Cities (Manuscript ID:
JCIT_2019_1839)

3. Owusu, E.K., Chan A.P.C., Siu, F. (2020). Corruption in Supply-Chain Management

Process: A Hybrid Metric Review. Built Environment Project and Asset Management

4. Zhang, Z., Owusu E.K., (2020). Accounting for the downtime-impact in scheduling
resilience-based restoration strategies for highway networks. Safety Science.

5. Ekanayake A., Shen Q. P., Kumaraswamy M. M., Owusu E.K. (2020) Critical Supply Chain
Vulnerabilities Affecting Supply Chain Resilience in Industrialized Construction in Hong
Kong. Journal of Cleaner Production. (Manuscript ID: JCLEPRO-D-19-19975)

6. Wang T., Chan A.P.C., He Q., Owusu E.K. (2019). Studies on the Success Criteria and
Critical Success Factors for Mega Infrastructure Construction Projects: A Literature Review
ASCE's Journal of Infrastructure Systems. (Ref.: Ms. No. ISENG-1617R1)

Honors and Awards

1. 1st Price – CIB World Congress Competition on the Topic of Smart People and Living,
Smart Service, Smart Governance, Policy and Economy, 2019. Hong Kong.

2. HK$100,000 book scholarship award from the Hong Kong Institute of Surveyors.

3. Overall GPA for course credits in partial requirements for the degree of Doctor of
Philosophy = 4.0

x
ACKNOWLEDGEMENTS

I am most grateful to my Triune Father (God Almighty, Jesus Christ, and the Holy Spirit) by whom all

grace and mercies abound. I am thankful to Him for preserving me and helping me to excel in my

studies.

My second appreciation goes to the Research Grants Council and the Hong Kong Polytechnic

University for fully funding this research by awarding me with both the Hong Kong Ph.D. Fellowship

Scheme and studentship, respectively.

I am heavily indebted to my Chief Supervisor, Professor Albert P. C. Chan, who has been more than a

supervisor and a Father to me. He has coached me, mentored, and groomed me to become the academic

researcher I am today. He believed in me right from the start of this project and had guided every step.

I know I cannot thank him enough for all that he has done and the value that he added to my life. I will

forever be grateful to him. To my biological and spiritual parents who have nurtured me, groomed me,

prayed for me, and supported me during my entire period of study, I am thankful. May our good Father,

continue to be gracious to you and reward you with every good gift from above. I love you, and I will

forever be grateful for all the sacrifices. From Very Rev James Kingsley, Mrs. Sabina Owusu, Pastor

Samuel Song, Mr. Kwabena Kwarteng, Pastor Roderic Agyekum, Pastor Kizito Amatey, and Pastor

Elton Afflu, I say God bless you.

Moreover, I want to extend my warmest regards to Mrs. Catherine Stanbury (President of Global

Infrastructure Anti-corruption Coalition, GIACC), Mr. Ronan Olaoire from the United Nations Office

on Drugs and Crime, Mr. Cesar Queiroz, a former World Bank Highways Adviser and all the industry

experts who afforded me their valuable time to review parts of my work and gave me valuable advice

and rich information, I am deeply grateful to you all. Lastly, I would want to extend my sincere gratitude

to all my research team members and friends who have supported me throughout my entire journey.

xi
TABLE OF CONTENTS

DEDICATION ..................................................................................................................... iii

ABSTRACT.......................................................................................................................... v
ACKNOWLEDGEMENTS .................................................................................................. xi
TABLE OF CONTENTS .................................................................................................... xii
LIST OF FIGURES.......................................................................................................... xviii
LIST OF TABLES ........................................................................................................... xviii
LIST OF ABBREVIATIONS ............................................................................................ xxii

CHAPTER 1 – INTRODUCTION ........................................................................................ 1

1.1 Research Background.............................................................................................. 1
1.2 Research Aim and Objectives.................................................................................. 4
1.2.1 Research Questions .......................................................................................... 4
1.2.2 Research Aim .................................................................................................. 5
1.2.3 Research Objectives ......................................................................................... 5
1.3 Research Focus ....................................................................................................... 7
1.4 Research Methodology ............................................................................................ 7
1.5 Research Significance and Worth .......................................................................... 11
1.6 Structure of the Thesis .......................................................................................... 12
1.7 Chapter Summary ................................................................................................. 16

CHAPTER 2 – RESEARCH METHODOLOGY ................................................................ 17

2.1 Introduction .......................................................................................................... 17
2.2 Research Design and Methods for the study .......................................................... 18
2.3 Methods of Data Collection................................................................................... 21
2.5.1. Literature Review .......................................................................................... 22
2.5.2. Questionnaire Development ........................................................................... 23
2.5.3. Ranking Scales .............................................................................................. 25
2.5.4. Questionnaire Pilot Study............................................................................... 26

2.6 DATA PROCESSING AND ANALYSIS ............................................................. 29

2.6.1. Mean Score (MS) Ranking Technique............................................................ 30
2.6.2. Mann Whitney U (MWU) Statistics ............................................................... 30
2.6.3. Kendall’s Coefficient of Concordance (W)..................................................... 31
2.6.4. Risk Importance Index (Expected Value) ....................................................... 32

xii
 2.6.5. Reliability Test .............................................................................................. 32
2.6.6. Factor Analysis .............................................................................................. 33
2.6.7. PLS-SEM ...................................................................................................... 35
2.6.8. Fuzzy Set Theory (Fuzzy Synthetic Evaluation) ............................................. 38
2.6.9. System Dynamics .......................................................................................... 41
2.6.10. Content Analysis ........................................................................................ 43
2.7 Chapter Summary ................................................................................................. 45

CHAPTER 3 - A CONTEMPORARY REVIEW OF CORRUPTION ................................. 46

3.1 Introduction .......................................................................................................... 46
3.2 Forms of Corruption.............................................................................................. 46
3.2.1 Findings from Studies on the Analysis of Corruption Forms .......................... 48
3.2.2 Categorization of the Corruption Forms ......................................................... 51
3.2.3 Corruption Forms Constructs ......................................................................... 51
3.3 Causal Factors of Corruption................................................................................. 57
3.3.1 Findings of Corruption Causal Factors ........................................................... 58
3.3.2 Categorization of Variables ............................................................................ 61
3.4 Anti-Corruption Measures ..................................................................................... 72
3.4.1 Preventing Corruption .................................................................................... 73
3.4.2 Findings from Studies on Anti-Corruption Measures ...................................... 75
3.4.3 Constructs’ Development ............................................................................... 79
3.4.4 Discussion ..................................................................................................... 81
3.4.5 Factors Influencing ACM Formulation........................................................... 90
3.5 Barriers Affecting Effective Application of Anti-Corruption Measures ................. 91
3.5.1 Anti-corruption Efforts and Identification of the Barriers ............................... 93
3.6 Regional Perspectives of Corruption: The Developing and The Developed Contexts
96
3.6.1 Developing Countries – Ghana as a Case Study ............................................. 97
3.7 Developed Countries .......................................................................................... 110
3.7.1 The Case of Hong Kong............................................................................... 110
3.8 Chapter Summary ............................................................................................... 127

CHAPTER 4 – CONCEPTUAL FRAMEWORK DEVELOPMENT................................. 129

4.1 Introduction ........................................................................................................ 129
4.2 The Procurement Process .................................................................................... 132
4.2.1 Understanding the Systems, Policies, and Processes in IP ............................ 133

xiii
 4.2.2 The Procurement Process ............................................................................. 137
4.2.3 Procedures and Policies................................................................................ 138
4.2.4 Causal Mappings with Corruption ................................................................ 141
4.2.5 Corruption Forms within the Procurement Process ....................................... 142
4.2.6 Anti-Corruption Measures (ACMs) and associated Barriers in IP ................. 144
4.2.7 E-Procurement as an ACM........................................................................... 146
4.2.8 Vulnerabilities to Corruption (Irregularities/risk indicators) ......................... 147
4.2.9 Conceptual Framework ................................................................................ 148
4.2.10 Section concluding remarks ......................................................................... 150
4.3 Chapter Summary ............................................................................................... 151

CHAPTER 5 – THE PROCUREMENT PROCESS’ PRONENESS TO CORRUPTION ... 152

5.1 Introduction ........................................................................................................ 152
5.2 Research Design ................................................................................................. 153
5.3 Procurement Process’ Proneness Model Development......................................... 154
5.3.1 Developing an assessment Index System ...................................................... 154
5.3.2 Estimations of Input Variables’ Weightings. ................................................ 155
5.3.3 Determining the Membership Functions of the Input Variables for the Activities
158
5.3.4 Determination of the Membership Functions for the Constructs/Stages (Level 2)
159
5.3.5 Establishment of the Multi-level and Multi-criteria FSE Model .................... 160
5.3.6 Estimating the overall vulnerability Index .................................................... 164
5.3.7 Development of the Procurement Vulnerability Model ................................. 167
5.4 Discussion........................................................................................................... 168
5.4.1 The Pre-Contract Stage ................................................................................ 168
5.4.2 The Contract Stage and the Contract Administration Stage .......................... 169
5.4.3 The Post Contract Stage ............................................................................... 170
5.5 Chapter Summary ............................................................................................... 172

CHAPTER 6 – MEASURING THE CRITICALITIES OF THE NEGATIVE CONSTRUCTS

OF CORRUPTION AND THEIR IMPACT ON THE PROCUREMENT PROCESS ........ 175
6.1 Introduction ........................................................................................................ 175
6.2 Forms of Corruption............................................................................................ 175
6.2.1 Bribery Acts................................................................................................. 177
6.2.2 Collusive Acts.............................................................................................. 178

xiv
 6.2.3 Discriminatory Acts ..................................................................................... 179
6.2.4 Fraudulent and Extortionary Acts ................................................................. 180
6.2.5 Unclassified Acts (Professional Malfeasance Acts) ...................................... 181
6.2.6 Extortionary Acts ......................................................................................... 182
6.3 Causal Factors of Corruption............................................................................... 183
6.4 Procurement Irregularities ................................................................................... 189
6.4.1 Developing the Constructs for the Risk Variables ........................................ 192
6.5 Assessment of the Impact of the Variables on the Procurement Process .............. 201
6.6 Chapter Summary ............................................................................................... 207

CHAPTER 7 – EXAMINING THE EFFECTIVENESS OF ANTI-CORRUPTION

MEASURES AND ASSOCIATED BARRIERS’ .............................................................. 209
7.1 Introduction ........................................................................................................ 209
7.2 Anti-Corruption Estimation and Prediction Model Development ......................... 211
7.2.1 Index System Development.......................................................................... 211
7.2.2 Determining the MF for variables and constructs of the ACM ...................... 213
7.2.3 Estimation of the weightings ........................................................................ 216
7.2.4 Development of the Multi-Criteria and Multi-Level Fuzzy Model ................ 217
7.2.5 Discussions .................................................................................................. 220
7.2.6 The development of the EI model for other Developing Regions .................. 221
7.2.7 Performance of the Measures ....................................................................... 223
7.3 Barriers Inhibiting the Efficacy of Anti-corruption Measures .............................. 227
7.3.1 Introduction ................................................................................................. 227
7.3.2 Hypotheses Formulation .............................................................................. 231
7.3.3 Discussions .................................................................................................. 236
7.3.4 The criticality of constructs and the variables ............................................... 237
7.3.5 Measurement Models Evaluation ................................................................. 237
7.4 Chapter Summary ............................................................................................ 247

CHAPTER 8 – GLOBAL PERSPECTIVES – COMPARATIVE ANALYSIS AND

EXEMPLARY LESSONS ................................................................................................ 249
8.1 Introduction ........................................................................................................ 249
8.2 Findings from experts survey .............................................................................. 250
8.2.1 Stages-Comparative Results ......................................................................... 254
8.2.2 Corruption Prevalence and Control in Project Procurement .......................... 256
8.2.3 Prevalent Forms of Corruption throughout the Procurement Process ............ 258

xv
 8.2.4 Discussions .................................................................................................. 262
8.2.5 Section Concluding Remarks ....................................................................... 265
8.3 Anti-Corruption Measures ................................................................................... 267
8.3.1 Results and Discussions ............................................................................... 270
8.3.2 Significant disparities as indicated by the MWU test results ......................... 277
8.4 An empirical assessment of the Barriers .............................................................. 281
8.4.1 Introduction ................................................................................................. 281
8.4.2 Data Analysis and Survey Results ................................................................ 281
8.4.3 The criticality of Individual barriers of both contexts ................................... 285
8.4.4 Individual Comparability ............................................................................. 287
8.4.5 Factor and Network Analyses Results .......................................................... 288
8.4.6 Construct’s Criticality .................................................................................. 292
8.4.7 Section Summary ......................................................................................... 298
8.5 Exemplary Lessons: The Case of Hong Kong...................................................... 300
8.5.1 Pretests ........................................................................................................ 301
8.5.2 Mean Index Estimations ............................................................................... 302
8.5.3 Measuring the effectiveness of the measures ................................................ 302
8.5.4 Discussions .................................................................................................. 313
8.5.5 Concluding remarks ..................................................................................... 320
8.6 Chapter Summary ............................................................................................... 322

CHAPTER 9 – DEVELOPING THE DYNAMIC FRAMEWORK .................................. 323

9.1 Introduction ........................................................................................................ 323
9.1.1 SD Model development - A ‘corrupt free’ procurement SD model ...................... 324
9.1.2 Causal Loop Diagram (CLD) and conceptual model formulation ........................ 326
9.1.3 Stock-flow diagram (SLD) .................................................................................. 330
9.2 Anti-Corruption Framework: Ex-ante and Ex-post Classification ........................ 337
9.3 Chapter Summary ............................................................................................... 339
9.4 Validation of Variables Constructs and Models ................................................... 341
9.4.1 Validation Results ........................................................................................ 343
9.5 Chapter Summary ............................................................................................... 347

CHAPTER 10 – CONCLUSIONS AND RECOMMENDATIONS ................................... 349

10.1 Introduction ........................................................................................................ 349
10.2 Review of the Research aim and objectives and their significance ....................... 349
10.3 Limitations of the study and recommendations for future research ...................... 363
xvi
 10.4 Chapter Summary ............................................................................................... 366

APPENDICES .................................................................................................................. 367

Appendix A ................................................................................................................... 368
Appendix B ................................................................................................................... 378
Appendix C ................................................................................................................... 379
Appendix D ................................................................................................................... 380
Appendix E ................................................................................................................... 381
Appendix F.................................................................................................................... 382
Appendix G ................................................................................................................... 384
Appendix H ................................................................................................................... 385

REFERENCES ................................................................................................................. 397

xvii
LIST OF FIGURES

FIGURE 1.1 INTERCONNECTIONS OF RESEARCH OBJECTIVES ..................................................................... 6

FIGURE 1.2 ................................................................................................................................................... 10

FIGURE 3.1: CONCEPTUAL FRAMEWORK FOR CFS CLASSIFICATION .................................................. 52

FIGURE 3.3 CONCEPTUAL FRAMEWORK FOR CAUSES OF CORRUPTION .............................................. 62

FIGURE 3.4 GRAPHICAL PRESENTATION OF THE CONSTRUCTS MEAN SCORE...................................... 71

FIGURE 3.5 CONCEPTUAL FRAMEWORK OF ACMS IN CPM. ............................................................. 80

FIGURE 3.6 GRAPHICAL ILLUSTRATION OF INDIVIDUAL CONSTRUCTS’ MEAN SCORES...................... 90

FIGURE 3.7 CPI OF GHANA FOR THE PAST DECADE (ADAPTED FROM TI, 2017) ............................... 100

FIGURE 3.8: WORLDWIDE GOVERNANCE INDICATORS, (WGI) ON CORRUPTION CONTROL ............. 102

FIGURE 3.9: GLOBAL COMPETITIVENESS INDEX (GCI) ON GOVERNMENT INTEGRITY ..................... 102

FIGURE 3.10: DECADAL EFFORTS ON LEGAL ANTI-CORRUPTION FRAMEWORKS. ........................... 103

FIGURE 3.11: TOPICAL COVERAGE OF CORRUPTION-RELATED STUDIES OF HONG KONG ................. 112

FIGURE 3.12: NUMBER OF COMPLAINTS RECORDED BY ICAC FROM 1996-2015.............................. 120

FIGURE 3.13: INDIVIDUALS CAUTIONED AND INDIVIDUALS PROSECUTED RECORDED BY ICAC FROM

1997-2015 ............................................................................................................................. 121

FIGURE 3.14: CORRUPTION PERCEPTION INDEX (CPI) OF HONG KONG........................................... 122

FIGURE 3.15: WORLDWIDE GOVERNANCE INDICATORS, (WGI) ON CORRUPTION CONTROL ........... 122

FIGURE 3.16: GLOBAL COMPETITIVENESS INDEX ON GOVERNMENT INTEGRITY (2017) .................. 123

FIGURE 4.1: CORRUPT PRACTICES FRAMEWORK (ADAPTED FROM VARIOUS LITERATURE) .............. 131

FIGURE 4.2: THE IP PROCESS ......................................................................................................... 137

FIGURE 4.3: PROCUREMENT PROCEDURES ..................................................................................... 139

FIGURE 4.4: CONCEPTUAL FRAMEWORK ........................................................................................ 150

FIGURE 6.1: GRAPHICAL PRESENTATION OF THE CRITICALITIES OF CORRUPTION CAUSAL

CONSTRUCTS ......................................................................................................................... 188

FIGURE 6.2: CONCEPTUAL ILLUSTRATION OF THE NEGATIVE CONSTRUCTS OF CORRUPTION ON THE

PROCUREMENT PROCESS ........................................................................................................ 202

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FIGURE 6.3: NETWORK ANALYSIS OF THE NEGATIVE CONSTRUCTS OF CORRUPTION ON THE

PROCUREMENT PROCESS. ....................................................................................................... 203

FIGURE 6.4: CRITICALITY IMPACT OF THE CORRUPTION CONSTRUCTS ON THE PROCUREMENT PROCESS

.............................................................................................................................................. 204

FIGURE 7.1: INDIVIDUAL VARIABLES AND CONSTRUCTS OF BARRIERS AND ACMS ......................... 230

FIGURE 7.2: HYPOTHETICAL MODEL OF THE STUDY (EXPANDED MODEL)........................................ 233

FIGURE 7.3: CRITICALITY IMPACT INDEXES OF THE BARRIERS’ CONSTRUCTS ................................ 236

FIGURE 7.4: STRUCTURAL EQUATION MODEL OF THE STUDY (EXPANDED MODEL) ........................ 247

FIGURE 8.1: DISPARITIES OF CORRUPTION PREVALENCE ACMS EFFECTIVENESS IN PROCUREMENT

PROCESS ................................................................................................................................ 258

FIGURE 8.2: MEAN INDEXES FOR CFS PREVALENCE WITHIN THE PP (DEVELOPED COUNTRIES) ...... 259

FIGURE 8.3: MEAN INDEXES FOR CFS PREVALENCE WITHIN THE PP (DEVELOPING COUNTRIES). .... 260

FIGURE 8.4: GRAPHICAL ILLUSTRATION OF MS DISPARITIES OF ACM CONSTRUCTS ....................... 280

FIGURE 8.5: NETWORK ANALYSIS OF THE ACMS BARRIERS IN THE DEVELOPED CONTEXT. ............ 290

FIGURE 8.6: NETWORK ANALYSIS OF THE ACMS BARRIERS IN THE DEVELOPING CONTEXT. ........... 290

FIGURE 8.7: CONSTRUCTS' COMPARISON OF THE DEVELOPED AND DEVELOPING CONTEXTS ........... 298

FIGURE 8.8: THEMATIC REPRESENTATION OF ACM CONSTRUCTS .................................................. 314

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LIST OF TABLES

TABLE 2.1: RESEARCH PROCESS ...................................................................................................... 20

TABLE 2.2: RANKING SCORES DEFINITIONS ..................................................................................... 25

TABLE 3.1: CORRUPTION FORMS (CF) IDENTIFIED IN THE LITERATURE .............................................................................. 50

TABLE 3.3: CAUSAL FACTORS OF CORRUPTION IN CONSTRUCTION ................................................... 59

TABLE 3.5: OVERVIEW OF SELECTED ORGANIZATIONAL INITIATIVES ............................................... 74

TABLE 3.6: FINDINGS ON ANTI-CORRUPTION MEASURES ............................................................................. 77

TABLE 3.8: BARRIERS TO EFFECTIVE ANTI-CORRUPTION MEASURES ................................................................ 95

TABLE 3.9: IRREGULARITIES IN PROCUREMENT ......................................................................................... 106

TABLE 3.10: STATISTICS ON CORRUPTION IN HONG KONG FOR THE PAST 2 DECADES ........................................ 119

TABLE 4.1: PROCUREMENT SYSTEMS AT A GLANCE........................................................................ 135

TABLE 5.1: INPUT VARIABLES’ LINGUISTIC TERMS ........................................................................ 155

TABLE 5.2: MF FOR STAGES AND RESPECTIVE ACTIVITIES OF THE PROCUREMENT PROCESS........... 157

TABLE 5.3: MF FOR STAGES OF THE PROCUREMENT PROCESS........................................................ 163

TABLE 5.4: STAGES OF THE PROCUREMENT PROCESS..................................................................... 167

TABLE 6.1: FORMS OF CORRUPTION VARIABLES ............................................................................. 176

TABLE 6.2: CRITICALITIES ESTIMATIONS OF THE CORRUPTION CAUSAL VARIABLES ....................... 184

TABLE 6.3: FACTOR ANALYSIS OF THE VARIABLES (IRREGULARITIES) ........................................... 191

TABLE 6.4: FACTOR ANALYSIS OF THE VARIABLES (IRREGULARITIES) ........................................... 193

TABLE 6.5: OVERALL DESCRIPTORS AND HYPOTHESIS VALIDATION .............................................. 200

TABLE 7.1: ANTI-CORRUPTION VARIABLES ................................................................................... 212

TABLE 7.2: MEMBERSHIP FUNCTIONS (MFS) AT ACM VARIABLES AND CONSTRUCTS LEVELS ...... 215

TABLE 7.3: STAGES OF THE PROCUREMENT PROCESS..................................................................... 219

TABLE 7.4: STAGES OF THE PROCUREMENT PROCESS..................................................................... 222

TABLE 7.5: DESCRIPTIVE AND IMPACT EVALUATION OF BARRIERS TO EFFECTIVE APPLICATION OF

ACMS ................................................................................................................................... 234

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TABLE 7.6: FACTOR ANALYSIS OF BARRIERS ................................................................................. 235

TABLE 7.7: MEASUREMENT VALIDITY OF THE CONSTRUCTS .......................................................... 237

TABLE 7.8: DISCRIMINANT VALIDITY OF THE CONSTRUCTS ........................................................... 238

TABLE 7.9: STRUCTURAL MODEL EVALUATION ............................................................................. 242

TABLE 8.1: DESCRIPTIVE STATISTICS AND NORMALITY TEST OF PROCUREMENT ACTIVITIES........... 251

TABLE 8.2: STAGES OF THE PROCUREMENT PROCESS..................................................................... 252

TABLE 8.3: DEVELOPING COUNTRIES............................................................................................. 254

TABLE 8.4: DEVELOPED COUNTRIES .............................................................................................. 255

TABLE 8.5: DESCRIPTIVE STATISTICS OF THE EFFECTIVENESS OF ANTI-CORRUPTION MEASURES .. 269

TABLE 8.6: PAIRWISE COMPARISONS OF THE EFFECTIVENESS OF ACM IN THE DEVELOPING CONTEXT

.............................................................................................................................................. 273

TABLE 8.7: PAIRWISE COMPARISONS OF THE EFFECTIVENESS OF ACM IN THE DEVELOPED CONTEXT

.............................................................................................................................................. 276

TABLE 8.8: MANN-WHITNEY U TEST STATISTICSA INDICATING SIGNIFICANT DISPARITIES OF

VARIABLES ............................................................................................................................ 278

TABLE 8.9: FACTOR ANALYSIS OF BARRIERS IN BOTH CONTEXTS .................................................. 289

TABLE 8.10: DESCRIPTIVE AND WEIGHTINGS OF ACM VARIABLES AND CONSTRUCTS .................. 307

TABLE 8.11: MEMBERSHIP FUNCTIONS (MFS) AT ACM VARIABLES AND CONSTRUCTS LEVELS .... 309

TABLE 8.12: MEMBERSHIP FUNCTIONS (MFS) AT ACM LEVEL 2 AND 1 ......................................... 312

xix
LIST OF ABBREVIATIONS
AC – Anti-Corruption

ACET – The Global Anticorruption Education and Training Project

ACM – Anti-Corruption Measures

A-G – Attorney-General

AHP – Analytic Hierarchy Process

ASCE – American Society of Civil Engineers

CIECI – Construction Industry Ethics & Compliance Initiative

CIOB – The Chartered Institute of Building

CEM – Construction and Engineering Management

CM – Construction Management

COC – Code of Compliance

CoST – Construction Sector Transparency Initiative

CPI – Corruption Perception Index

DC – Design and Construct

DCEC – Directorate on Corruption and Economic Crime

FA – Factor Analysis

FCP – Fixed Price Contracting

FCR – Full-Cost Reimbursable

FIDIC – International Federation of Consulting Engineers

FSE – Fuzzy Synthetic Evaluation

GAS – Ghana Audit Service

GCI – Global Competitiveness Index

GDP – Gross Domestic Product

GFCF – Gross Fixed Capital Formation

GIACC – Global Infrastructure Anti-Corruption Centre

GMP – Guaranteed Maximum Price

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GOG – Government of Ghana

HKSAR – Hong Kong Special Administrative Region

ICAC – Independent Commission Against Corruption

IP – Infrastructure Procurement

ISO – International Organization for Standardization

KMO – Kaiser-Meyer-Olkin

NACAP – National Anti-Corruption Action Plan

OCC – On-Call Contracting

OECD – Organization for Economic Co-operation and Development

OSC – Organizational-Specific Causes

PBC – Performance-Based Contracting

PCI – Procurement and Contractual Irregularities

PLS-SEM – Partial least squares path modeling

PPA – Public Procurement Act

PPB – Public Procurement Board

PPP – Public-Private Partnerships

PSC – Project-Specific Causes

PSSC – Psychosocial-Specific Causes

RSC – Regulatory-Specific Causes

SD – System Dynamics

SSC – Statutory-Specific Causes

TI – Transparency International

TPO – Total Package Options

UPADI – Union of Pan-American Engineering Societies

UN – United Nations

WEF – World Economic Forum

WFEO – World Federation of Engineering Organizations

WGI – Worldwide Governance Indicators

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 Chapter 1 – Introduction

CHAPTER 1 – INTRODUCTION

1.1 Research Background

Many public and private enterprises globally regard corruption in Infrastructure Procurement (IP) as an

inescapable fact of life. This is not uncommon in developing countries as corruption adversely

influences the day-to-day modus operandi of the procurement of infrastructure projects, goods, and

services. Corruption has had several definitions that vary across different norms, laws, and cultures

(Jain, 2001). However, it is defined generically as the abuse of public office for private gain

(Transparency International, 2016; Le et al., 2014; CIOB, 2013; Bowen et al., 2012; World Bank, 2003).

The definition given above affirms the notion that corruption affects the public sector more than it does

to the private sector, although private sector practitioners as well heavily influence the incidences of

corrupt practices. This socio-economic scourge has evolved throughout the history of humanity and has

been a global issue and a growing challenge for individuals, communities, societies, businesses, and the

world at large.

Corruption connotes 5% an estimate of the total global economic output, which is approximately US

$2.6 trillion annually (World Economic Forum, 2012; Osterman and Staudinger, 2008). Other negative

impacts of corruption on the world economy identified included but not limited to: increased poverty,

inhibited services provision, stifled investment, truncated economic growth and increased inequality

(Gupta et al., 2002; Shakantu, 2006; Le et al., 2014; CIOB, 2013). In the developing world, it is widely

admitted that corruption is a significant contributor to the truncated economy. According to the World

Bank, corruption has been one of the utmost barriers to socio-economic development, which does not

only result in misappropriation of resources but also, loss of lives and properties (Lewis, 2003).

Corruption destabilizes development by weakening the economic foundations of institutions and

distorting the rule of law (Tabish and Jha, 2011). The proliferation of corrupt practices in public

infrastructure procurement globally has been intense, with the procurement process being regarded as

the most vulnerable process to corruption.

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Corruption, in public infrastructure procurement, can be defined as the use of entrusted power to the

detriment of the infrastructure project or process for personal gain, (Transparency International, 2009).

It is considered as the abuse of position, regulatory, legal, or political leverage to extract extra costs

allocated to the procurement of infrastructural projects (Le et al., 2014). In this event, the project

financier or developer may never recoup the loss incurred, and the perpetrators mostly deny their

involvement thereof (Wang et al., 1999; Shan et al., 2016). Procurement of goods and services as well

as investing in financial and public infrastructure in both developed and developing economies account

for a substantial share of the budgets of states (World Bank, 2003; OECD, 2005; Mauro, 1995; Regan,

2008). OECD (2008) indicated that averagely, 17% of gross domestic product (GDP) represented gross

fixed capital formation (GFCF) in developed countries and also in the range of 20% for developing

countries. As a result, the misappropriation of funds allocated for infrastructure can pose a significant

risk to the economy (World Bank, 2012). Walker (2003) purported that due to its nature of being capital

intensive, most public practitioners in esteemed positions take advantage to exploit federal funds

allocated for infrastructure for personal gain – corruption, which results in the distortion of the entire

procurement process. This case is not uncommon in the developing world as excerpts of corrupt acts

have been identified in almost every developing country (Hunga, 2003).

In most developing countries, existing literature and reports reveal how corruption has plagued the

public sectors, which are also traceable in public projects. For instance, particularly in the case of

Ghana, corruption has been noted as a critical impediment to the successful completion of vital public

projects. For example, Ameyaw and Chan (2015) identified corruption as the second most critical risk

indicator against public-private partnership (PPP) water projects in Ghana. A similar study conducted

by Osei-Kyei and Chan (2017) also revealed corruption to be the leading risk indicator against PPP

projects in Ghana. The list goes on and on as Damoah and Kumi (2018) recently reporting corruption

to be one of the vital contributors to public project failure. The issue of corruption in the developing

context, particularly in Ghana, has always been on the rise with limited efforts expended in exploring

this menace can be tackled. Moreover, while some of the critical constructs of corruption in public

projects such as the forms of corrupt practices with their causal factors, the risk indicators, anti-

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corruption measures, and their associated barriers have been scantly explored, most of these efforts

focus on the criticalities of the negative constructs of corruption such as the causes and the risk

indicators. The explorations of these negative constructs are mostly conducted to reaffirm the notion or

supposition that corruption is prevalent in the developing context.

However, in developed countries such as Singapore, the USA, UK and cities like Hong Kong,

corruption in infrastructure procurement is somewhat checked and balanced by measures or systems

such as e-procurement, raising awareness, rigorous technical auditing system, contract monitoring,

comprehensive rules and regulations, education, access to information, stringent supervision among

others (de Jong et al., 2009; Le et al. 2014; Tabish and Jha, 2012; Zou, 2006; Vaidya et al., 2006;

Neupane et al., 2014). Particularly, Hong Kong, one of the world’s finest cities, has gone a long way in

dealing with corruption and has made tremendous efforts in their fight against corruption in

infrastructure procurement (IP). The establishment of the Independent Commission Against Corruption

(ICAC) in 1974 revealed that Hong Kong had experienced similar challenges of corruption in the past.

However, the case has overturned with time (Yeung, 2000). Studies show that there is an apparent

agreement among scholars that Hong Kong’s ICAC stands to effectively transform its society in the

direction of a corruption-free environment or records very minimal level of corruption as compared to

its correlative agencies such as the ICAC of Korea (Quah, 2003; Bhargava and Bologaita, 2004; Choi,

2009). According to Rooke and Wiehem (1999), one of the brilliant, outstanding successes with regards

to corruption combat in Hong Kong is the Airport Core Program. A report by TI (1999) indicated that

this program outlines how corruption can be curtailed even in mega-size infrastructure projects. It is a

typical exemplary success model in Hong Kong's infrastructure procurement.

This thesis, therefore, explores the principal concerns of the prevalence of corrupt practices observed

in the public project procurement process in both the developed and the developing contexts using

Ghana and Hong Kong as the representative scopes. Predominantly, it explores the forms of corruption,

the factors that cause corruption, corruption risk indicators, anti-corruption measures and the barriers

that hinder the effective adoption and application of anti-corruption measures in the public procurement

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process. Models of the various constructs are developed to provide insights into the mentioned

constructs of corruption. Moreover, an in-depth study on how the negative constructs (including the

causes, risk indicators, and the barriers) can be dynamically tackled in all the stages involved in the

procurement process are examined. The developed frameworks and checklist provided in this research

may serve as a guide for industry practitioners, procurement entities, policymakers, anti-corruption

institutions, decision-makers, and researchers. This is to facilitate the development of more strategic,

advanced, and holistic anti-corruption measures potent enough to extirpate the proliferation of corrupt

practices and resilient enough to resist the incidences and effects of the barriers that hamper the efficacy

of anti-corruption measures. Consequently, such findings also contribute to the existing body of

knowledge (BoK) on corruption-related studies in both construction and project management

scholarships. The work also serves to provide a foundation for further empirical studies on the subject

matter. The research questions, overall aim, and the objectives guiding the direction of the research are

presented in the next section and Fig. 1.1.

1.2 Research Aim and Objectives

1.2.1 Research Questions

After thorough exploratory and preliminary review and following the background and problems

aforementioned, the following questions are articulated based on the theoretical gaps identified:

1. What are the dominant forms of corrupt practices prevalent in the public IP sector and their

causal instigators?

2. Are there any notable risk indicators (irregularities) within the IP process?

3. How effective are legal and institutional anti-corruption frameworks in their fight against

corrupt practices and their mode of implementation? Are there any barriers that hamper their

effectiveness?

4. To what extent are the stages of procurement vulnerable to the incidence of corruption?

a. What are the adverse effects on each respective stage?

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b. What solution is best suitable to curb the incidence of corruption within the IP process?

5. What are the impacts of corruption constructs on the procurement process and how can they be

mitigated?

1.2.2 Research Aim

The aim is to explore the dynamism of corruption in the public IP of developing and developed regions,

using Ghana and Hong Kong to develop a dynamic framework to mitigate its prevalence.

1.2.3 Research Objectives

Thus, to provide relevant and appropriate responses to the stipulated research questions as well as

realize the aim of the study, the following objectives are established:

1. Examine the forms of corruption and their respective causes that instigate or propel corruption

in infrastructure procurement (IP);

2. Examine the procurement irregularities in the developing context;

3. Investigate the effectiveness and the barriers to effectiveness of the anti-corruption measures;

4. Examine the IP stages' susceptibilities to corruption, associated forms and respective strategic

measures;

5. Develop a dynamic model to mitigate corrupt practices in the IP process.

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 Chapter 1 – Introduction

Figure 1.1 Interconnections of research objectives

Figure 1. 1 presents the relational interactions among the individual objectives of the study. The entire

study commences with objective 1: where a thorough review of the forms of corruption is conducted

together with the associated causal factors. An empirical assessment is performed on the constructs to

ascertain the individual levels of criticalities of both the corruption forms and the associated causal

factors. This cycle is repeated for objectives 2 and 3 to ascertain the criticalities of the identified

procurement irregularities, the effectiveness of anti-corruption measures, and the criticalities of the

barriers that hamper the effectiveness of the extant ACMs. In objective 4, a review and an empirical

assessment will again be conducted on the various methods, stages, an activity of the procurement

process to determine their vulnerabilities to corruption. Lastly, Chapter 5 culminates all the preceding

chapters to measure the impacts of the corruption constructs that will be ascertained in objective 1-3 on

the activities and stages of the procurement process in chapter 4 to determine the impacts of the

constructs on the procurement process.

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 Chapter 1 – Introduction

1.3 Research Focus

In a theoretical setting, this research focuses on the dynamic manifestations of the various forms of

corruption in public project procurement. Particularly, this research focuses on the thematic constructs

of corruption, which include forms of corruption and their causal factors, the procurement irregularities,

ACMs, and associated barriers that hinder the efficacy of stipulated ACMs in public project

procurement. Moreover, the evaluation of these constructs centers on the stages and activities within

the procurement process. This is owed to the supposition that the procurement process is the most

vulnerable globally, and also the construction industry responsible for executing infrastructure and other

related projects is considered as the second most corrupt industry globally (Krishnan 2010; Kottasova

2014). As it is later discussed in the succeeding chapters, a series of comprehensive reviews are

conducted to identify the principal variables underlying the mentioned constructs. Geographically,

Ghana, and Hong Kong are selected for this comparative study.

1.4 Research Methodology

Research methodology refers to the comprehensive approach of the design process, commencing the

theoretical underpinning to the gathering and analyzing of data (Collis and Hussey 2003; Thurairajah

et al. 2006). This research employs the needed tools, techniques, and theories to help address the

concerns of the study. This includes 1) the definition of the problem, identification of the relevant

literature for the study. 2) framing of research questions, formulating the research aim and objectives.

3) Deciding on the technique that would be needed to gather the data and determining the tools required

to analyze the gathered data and finally establishing answers to the detected problems (Brewer &

Hunter, 2006; Sapsford & Jupp, 1998). To make a genuine contribution to knowledge, Kumar (1995)

pinpointed the significance of reviewing previous methodologies. Reviewing earlier methodologies

gives the researcher a complete understanding of both the past and present knowledge on the

foundations of the employed methods. Wahab (1996) also, in his study, concurred with Kumar’s (1995)

findings.

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 Chapter 1 – Introduction

The research approach adopted for this research is discussed in detail in chapter two. However, an

ephemeral description, as well as the flowchart model of the research process, are illustrated in this

section. As established, this research is limited to the examination of the various activities and stages

involved in the processes of public project procurement, their levels of susceptibility to corruption, as

well as the various constructs of corruption, explored in line with public project procurement. The plan

of the study is made up of five stages described below:

Preliminary Phase: The preliminary stage comprises the initial research activities needed to

establish the research questions, aim, objectives, and methods to realize the aim of the study. This stage

of the study was achieved through the review of relevant existing literature, informal discussions with

industrial and academic experts, and an adequate brainstorming session with the academic project

supervisor as well as the project team.

Primary Phase: An apropos and a critical review of the various thematic constructs of corruption, which

include the forms of corruption, causes of corruption, procurement irregularities or risk indicators of

corruption, anti-corruption measures, and the barriers that impede the efficacy of anti-corruption

measures. These reviews are intended to reveal the existing critical variables underpinning the

mentioned constructs. The past and current trends and positions of both Ghana and Hong Kong on

corruption were explored regarding global perspectives and rankings. Analytic considerations involved

legislation, relevant literature review from articles, academic journals, textbooks, newsletters, and

conference papers. Dialogues with pertinent practitioners in the construction and procurement sectors,

anti-corruption institutions, and construction professionals as well as assessments of reports on

corruption observed in Ghana and Hong Kong and related cases in infrastructure projects were also

carried out.

Secondary Phase: The secondary phase includes the development of the study’s questionnaire, a pilot

test of the questionnaire, and an expert survey. Following the findings that were retrieved from the

extensive literature reviews, a questionnaire was developed to solicit experts’ opinions concerning the

identified constructs. The questions, therefore, sought to identify the leading forms and causes of

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corruption prevalent in the public procurement process, the criticalities of the causal factors of

corruption and the risk indicators of corruption. Lastly, the effectiveness of existing anti-corruption

measures and the criticalities of the barriers that impede the efficacy of anti-corruption measures were

also examined. The questionnaire was developed and tested to suit the conditions of both the developed

and the developing contexts. The questionnaire of Hong Kong was developed to enable a comparative

analysis to be conducted to estimate the difference in performance and attitude towards corruption in

both regions. Also, since the construct, ‘barriers to the effective implementation and application of

ACM is an unexplored area, particularly in the developing context, experts’ interviews were conducted

to solicit for rich data regarding this construct. The gathered data were analyzed to develop theoretical

constructs for further testing and validation.

Advanced Stage: The advanced stage consists of statistical analysis and the development of the models.

After the expert survey, the pertinent and pragmatic variables obtained were analyzed to establish the

critical forms and causal factors that auger corrupt practices at the various stages of IP, the risk

indicators, or procurement irregularities prevalent in the developing context, the barriers that affect the

efficacy of the ACMs. A soft computing predictive model is developed to examine and predict the

vulnerability of the procurement process. A model showing the significant relationships among the

barriers impacts on the existing anti-corruption constructs is also developed to reveal the specific

barriers that hinder the efficacy of existing ACMs. The network model is developed to reveal the impact

of all the negative constructs of the various activities of the procurement process. Moreover, it aims to

indicate the significant relationship between the variables under the negative constructs and the

activities. Lastly, a comprehensive dynamic model is developed to illustrate how corruption within the

procurement process can be extirpated. The various tools used to develop all the mentioned models are

discussed in detail in the succeeding chapter.

Closing Phase: The closing phase succeeds the statistical analysis and the development of the models.

A comprehensive review of the entire thesis is conducted to draw up the findings of the study and

propose the needed action to be taken in both the short-term and the long-term run. Recommendations

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 Chapter 1 – Introduction

for future research are provided in the conclusion section of the study. The flowchart model in Fig. 1.2

below shows the overall research process of the study.

Figure 1.2 Flowchart of the entire study

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 Chapter 1 – Introduction

1.5 Research Significance and Worth

Given the number of studies devoted to the assessment of the various constructs of corruption in public

procurement, particularly in developing countries, not much has been done about the empirical

assessment of how vulnerable the procurement process is to corruption. In essence, this is arguably the

first study to conduct a holistic exploration of all the thematic or established constructs of corruption in

public project procurement as well as the levels of susceptibility of the project procurement process. As

a result, all the reviews conducted in this study contributes significantly to the scholarship of corruption-

related studies in both construction management studies and project-management-related studies.

Theoretically, since previous studies have not empirically addressed the constructs of corruption

explored in this research, the findings of this research represent the first to address all the primary

constructs of corruption in public projects as well as the susceptibility levels of the different activities

and stages of the procurement process. Consequently, this research contributes to the existing body of

knowledge (BoK) on corruption-related studies in both construction management and project

management-related scholarships. Moreover, this study provides a richer understanding of the

dynamism and behavior of corrupt practices in the supply chain of the procurement process.

Cumulatively, the research offers anti-corruption institutions, policymakers, and industry practitioners

with the knowledge that may assist in the development and implementation of more effective anti-

corruption tools. This research also serves as a foundation for further empirical studies on the subject

matter to be conducted.

The relevance of this research is not only attributed to the identification of the barriers' criticalities that

need extensive efforts in extirpating their influence but also the significant relationship that has been

identified. In summary, regarding the theoretical contribution to the body of project management

scholarship, this study reveals the relevant areas that need more effort during the development of ACMs

for public projects. Moreover, not only are the constructs and the model developed original to the

contribution of the BoK of project management, but also, this study’s findings represent the first to

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 Chapter 1 – Introduction

reveal the correlational impact of the barriers on the effectiveness of anti-corruption measures. Thus,

making it arguably the first project management-related study to examine these constructs.

Consequently, the outcome of this part of the study also contributes to the existing body of knowledge

(BoK) on corruption-related studies in project management. It contributes to a deepened understanding

of the constructs discussed in the context of project management in developing countries.

1.6 Structure of the Thesis

This thesis is composed of ten chapters, and they are detailed out as follows:

Chapter 1 – Introduction: Chapter 1 introduces the central theme of this research study. It stipulates the

background of this study, an initial review to identify the research gaps, the problem statement, the

research questions, aim, and objectives. Moreover, it presents the research focus encapsulating both the

contextual and geographical scope, the research significance and worth, the plan, and methodology,

also highlighting the approach used.

Chapter 2 – Research Methodology: Chapter 2 details the methodology that is adopted to realize the

aim and the objectives of the research. It explicates all quantitative and qualitative methods employed

throughout the entire process. They include pertinent literature review, structured interviews,

descriptive analysis, content analysis, factor analysis, partial least squares structural equation modeling

(PLS-SEM), fuzzy set theory, social network analysis, and system dynamics. The theory behind the

adoption and application of these techniques to achieve the stipulated aim and the objectives would be

explained in this chapter.

Chapter 3 – The Anatomy of Corruption: Chapter 3 consists of three sections, and they are discussed

below:

Section 1 - The Evolution and Forms of Corruption: This chapter is set to detail out the intricacies of

how corruption in public project procurement has progressed to its present stage. Through a careful

analysis of relevant literature, section one explicates the anatomy of corruption, nature, all identified

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 Chapter 1 – Introduction

forms and their causes or factors that give rise to corruption as well as the vulnerabilities, the cost of

corruption to the individual, the society, the nation and the entire globe as a whole.

Section 2 – The Causal Instigators of Corruption: Analogous to section one, this section of Chapter 3

explores the leading causal factors that trigger the incidence of corrupt practices in project procurement.

A pertinent literature review is conducted at this stage to identify these leading factors, which are tested

empirically in both geographic regions considered in this study.

Section 3 –Anti-Corruption Measures and Associated Barriers: Attempts made to tackle corruption in

public procurement normally exist either under statutory regulations or institutional mechanisms. This

section of the thesis investigates the existing tools, measures, and frameworks established to combat

corruption in public procurement. A thorough review is, therefore, made to identify the existing

measures to fight corruption and anti-corruption measures. Moreover, even though institutions and

governments develop strategic measures to curb the incidence of corruption. As to whether there exists

a pragmatic, methodical process to access the effectiveness of these measures, literature is silent on it.

This section addresses this issue by explicating the factors that serve as barriers to the effective

application of anti-corruption measures.

Chapter 4 – Investigating the Cases of The Developing and The Developed: Chapter 4 explicates the

cases of the developed and the developing contexts, respectively. Regarding the developing context,

Ghana is selected as the specific scope of focus, and regarding the case of the developed world, Hong

Kong is selected. Justifications for selecting both countries are discussed in this chapter, including their

performances regarding the extirpation of corrupt practices within these two contexts. Analogous to the

previous chapter, this chapter is also divided into sections. Section one conducts a thorough review of

Ghana, whereas Section two focuses on Hong Kong. In the cases of both Hong Kong and Ghana, this

chapter explores the underlying constructs of corruption on the general scale and in infrastructure

procurement through a palpable review of relevant literature. In the case of Ghana, a deep review of

relevant literature, as well as other related documents such as the reports of the Attorney-General (A-

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 Chapter 1 – Introduction

G), is examined to identify the possible irregularities or indicators of corrupt behaviors in the area of

procurement and contractual works. Aside from the investigations into the general thematic constructs

of corruption, this chapter explores the vulnerabilities involved in the procurement of infrastructure

works. A similar review is conducted in the case of Hong Kong. However, the aim of the Hong Kong

review is mainly to investigate their best practices adopted for over these four to five decades. This

Chapter 5 – Conceptual Framework of Corruption in IP: This chapter presents the conceptual

framework of a dynamic model for assessing corruption in the IP process. This section of the research

thesis highlights the concept of procurement by clearly elucidating the complexities involved in the

processes of public procurement and their relationship to corruption. Similar to the methods in chapter

three, a detailed review was conducted to identify the systems, procedures, and policies involved in IP.

The theoretical framework was developed to analyze the interconnections between the stages involved

in procurement and their susceptibility or proneness to corruption. Simply put, how vulnerable each

respective stage is to corruption is examined at this phase of the study.

Chapter 6 – Impact of Corruption on the Procurement Process

This chapter presents the empirical analysis of the negative constructs of corruption explored in this

study and their overarching impacts on the various activities captured under the four respective stages

of the procurement process. They include the causal factors of corruption, procurement irregularities,

or the risk indicators of corruption within the procurement process and the barriers that hamper the

effective application of anti-corruption measures. The individual criticalities of these negative

constructs are conducted and presented separately within the various sections of this chapter. Moreover,

this chapter concludes with the estimations of the overall significant impacts of the constructs on the

various activities of the procurement process. Using the SNA technique, the developed model reveals

that the overall impacts of the negative constructs of corruption on the procurement process are dynamic

in nature as the criticality affect some activities more than others.

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 Chapter 1 – Introduction

Chapter 7 – Examining the effectiveness of anti-corruption measures and associated barriers

Chapter 7 presents the empirical analysis of the efficacy of the established anti-corruptionn measures

identified within the developing context. This reveals how potent the measures limit or extirpate the

prevailing causal measures as well as the occurrence of corruption in the developing context using

Ghana as the focus of study. Moreover, an effective evaluation index is developed using a soft

computing technique known as the fuzzy synthetic evaluation (FSE). This is developed to help estimate

and predict the effectiveness index of the measures stipulated to limit or extirpate corruption in the

project process. Moreover, this chapter presents the criticality of the identified barriers that hamper the

efficacy of the measures stipulated to curb corruption. With the application of the PLS technique, the

significant relationships regarding the impacts of the susceptible against the measures are hypothesized

and measured. Thus, the results reveal the significant paths that need critical attention.

Chapter 8 – Global Perspectives – Comparative Analysis and Exemplary Lessons

This chapter continues the empirical assessments from chapters 6 and 7 by comparing the generic results

analyzed from the obtained from both the developing and the developed contexts. The chapter reveals

the disparities in some of the critical constructs between the two contexts. That is, the justifications

underlying the suppositions on why the developed contexts perform well when it comes to the matters

of corruption as compared to some of the developing context. The chapter, therefore, reveals findings

on some of the possible exemplary measures that most of the countries within the developing contexts

can learn from the developed context. The lessons are aimed at reducing the impacts of the negative

constructs and effects of corruption in public projects and the mechanisms needed to improve upon the

efficacy of the ACMs.

Chapter 9 – Developing a Dynamic Framework for Checking Corruption

This chapter presents the dynamic model that encapsulates the constructs of all the thematic areas

explored in this study. Unlike the previous chapters that focused on specific thematic areas such as the

causal factors, anti-corruption measures, and barriers, among others, this chapter encapsulates all the

constructs of the various chapters examined in this study. The dynamic model is developed to facilitate

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 Chapter 1 – Introduction

the mitigation and extirpation of corrupt practices within the procurement process by limiting the

impacts of the criticalities posed by the negative constructs of corruption as well improve the efficacy

of the prevailing anti-corruption measures. Similar to the previous chapters, this chapter offers a

comprehensive overview and contributions of corruption-related study to the body of project and

construction management scholarships upon which further recommendations are made in the

succeeding chapter.

Chapter 10 – Conclusions and Recommendations

Chapter 10 concludes this research. Inasmuch as the topic of corruption is noted to be an unending

phenomenon, this research targeted to contribute to corruption-related studies within the domains of

project management and construction management. The overall contributions of this research to

infrastructure management related scholarships and practical implications to the industry are presented

in the chapter. Lastly, the research limitations, in addition to the recommendations for future research,

are presented in this chapter.

1.7 Chapter Summary

This chapter aimed to introduce this study and to present the background of the thesis. It presented both

the theoretical and practical need for this research, the research question, the main aim, and the

objectives this research intends to explore. It also introduces the key methods and tools adopted at the

different stages of the study and presents a comprehensive flowchart diagram of the entire study. Lastly,

this chapter highlighted both the thematic and geographical contexts of the study as well as the

theoretical and practical contributions of this study to both the body of knowledge on corruption-related

studies in project and construction management scholarships and the industry. The succeeding chapter

specifically details out all the tools and methods selected for this study.

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 Chapter 2 – Research Methodology

CHAPTER 2 – RESEARCH METHODOLOGY

2.1 Introduction

This chapter details the research methodology established to achieve the set aim and objectives of this

research. This section discusses the methods for obtaining the required data, tools for analyzing gathered

data as well as methods for developing the models proposed by this study. As suggested by Vogt (2007)

and Steele (2000), to efficiently and accurately realize the research aim and objectives of a study and

validate the findings, it is very expedient to adopt an apropos research methodology. Moreover,

particularly to the field of construction management, Ameyaw (2014) and Walker (1997) mentioned

that the right choice and application of rigorous enables CM based research projects to attain plausible

results as well as contribute enormously to the body of knowledge and industrial practice. Past studies

on corruption in the area of infrastructure procurement have seen the light of the adoption of wide-

ranging methods to identify and explore the different topical constructs. Per the literature studied, the

subject areas that have been predominantly explored include corruption forms and associated causal

factors of corruption. Other include the risk factors or vulnerabilities associated with corruption, ACMs,

and the barriers that prohibit the effective adoption and application of anti-corruption measures in the

procurement process sectors (Shan, 2016; Le et al., 2014; Tabish and Jha, 2008; Soroide, 2002).

Some of the common research methods adopted in these studies include case studies, relevant literature

review, questionnaire surveys and expert interviews (Bowen et al., 2012; de Jong et al., 2009; Boyd and

Padilla, 2009; Zhang et al., 2016). Similarly, this study conducted a structured questionnaire survey and

interviews with potential experts, and this served as the primary data for the study. Other auxiliary

methods are adopted as appropriate. The tools employed for this study would, therefore, be used to

investigate the constructs mentioned. Details with regards to the questionnaire development and survey

are discussed later in section 2.5.2 of this chapter. The analysis of the collated data is conducted with

the help of the following software packages: Statistical Package for Social Science (SPSS 23.0 for

windows), Vensim Personal Learning Edition (PLE) for education and personal use (2016), Smart PLS

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 Chapter 2 – Research Methodology

2.0 M3 and software recommended by experts. Most of the results are descriptively expressed in mean

values, and the numerous variables identified in each topical coverage or context are grouped into a few

important constructs with the help of factor analysis. The risk assessment of the variables identified

under the vulnerabilities to corruption section is performed using the fuzzy synthetic evaluation method

(Shan, 2015; Ameyaw, 2014). Moreover, the interrelationship between the causal factors of corruption,

associated risk factors or vulnerabilities to corruption, the effectiveness of the prevailing anti-corruption

measures, and the barriers to the application and the implementation of the anti-corruption measures

are modeled using the SNA and the PLS-SEM. Lastly, the dynamism or the responsiveness of

infrastructure procurement stages to the causal factors and the anti-corruption measures is modeled

using system dynamics. The justifications underpinning the adoption and application of these

techniques to achieve the stipulated aim, and the objectives are explained in the subsequent sections.

2.2 Research Design and Methods for the study

Pandey and Pandey (2015) defined a research design as the master plan or framework for a study, and

it is used as a guide for gathering and analyzing data. Simply put, it is the blueprint for the entire research

study (Kerlinger, 1971). According to Creswell (2003), a research design may be regarded as the logical

and systematic sequence that addresses a topic under research, and per the study of Shan (2015) and

Creswell (2003), the research design process embodies four distinct parameters for realizing the set aim

and objectives behind a study. They include the questions behind the study, the appropriate data required

to answer the questions, the methods of getting the data, and finally, the modes and techniques of

analyzing and validating the data. A research design is also dependent on the researcher’s personal

experiences, the topic under the examination as well as the targeted audience that the researcher intends

to reach. The formulation of excellent and comprehensive research design, therefore, intends to

integrate the strategies mentioned above (Shan, 2015; Creswell, 2003). The entire research design

process for this study is summarized in Table 2.1 and explicated into detail in the subsequent sections.

Considering the research design as a general framework for achieving the targeted goals, the respective

research methods are therefore proposed to undertake the procedures established in the design. Research

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 Chapter 2 – Research Methodology

methods may include quantitative, qualitative, or mixed methods. Qualitative methods are

predominantly employed to solicit for views in response to open-ended questions, and a researcher may

employ techniques such as conducting an interview, focus groups, participant observation, etc. to collate

or gather the needed data (Grbich, 2002; Patton, 2005; Shank, 2002). Quantitative methods, on the other

hand, make use of instrument-based questions or what is usually regarded as close-ended questions to

solicit for relevant data. Statistical analysis and interpretations are requirements for quantitative-based

data, which is a direct contrast to that of qualitative methods. However, in the case of mixed methods,

also known as methodological triangulation (Lee, 1991), both qualitative and quantitative methods are

combined, and this allows the logic of triangulation, to enhance the validity of the findings (Bryman,

1992).

Based on the strengths of mixed methods stipulated from various studies, for instance, Bryman (1992),

this study adopted the mixed methods approach to provide explicit and well-defined characteristics of

corruption in public IP works in developing countries and, more specifically, in Ghana. Based on the

study of Moffatt et al., (2006), Creswell (2014) and Lee (1991), the mixed methods or triangulation

approach has been postulated as a more powerful and advantageous method than the single approach

where a researcher either adopts the qualitative or the quantitative approach. A typical example that is

often discussed in the literature is that researchers may adopt the qualitative approach to develop

constructive theories and employ the quantitative approach to test the developed theories or vice versa.

The entire design with the respective methods to reach each objective, as well as the aim of this study,

are presented in Table 2.1.

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 Chapter 2 – Research Methodology
Table 2.1: Research Process

RESEARCH DESIGN (RD)

RESEARCH OBJECTIVE DATA COLLECTION DATA ANALYSIS
LR QS EI TA CA MS FA SEM SNA SD MWU FSE
1. Examine the forms of corrupt
practices and their respective causes √ √ √
that auger the practices of corruption
in public infrastructure procurement;

2. Examine the procurement

irregularities in the developing √ √ √ √ √ √ √
context

3. Establish the stages in procurement √ √ √ √ √ √ √

and their susceptibility to corruption
with respective strategic measures to
curb its incidence

4. Investigate the effectiveness and the

barriers to effectiveness of the anti- √ √ √ √
corruption measures

5. Develop a dynamic overarching

model to mitigate corrupt practices in √ √ √ √ √
public procurement
Remarks To General To Qualita Adopted to Apropo Used to An A A modeling A non- A precise
establish survey verify tive make valid s for express effective methodical tool to help parametric tool for
a which is the techniq and replicable determi observed means for process of understand test to handling
theoretic also the findings ue that inferences by ning data assessing examining complex independen complex and
al first-round and focuses coding and the values as relationshi relational problems and t sample t- ill-defined
underpin survey to develope on interpreting signific a ps that structures provides an test fuzzy
ning for solicit for d models identify textual ance of function exist using series approach for employed phenomena
the expert of the ing, material by factors of some among of networks representing to compare resulting
research views using study assessi evaluating (Cheng possible IVs and and in a the dynamic two sample from vague
questionnai ng and texts and Li, causes to their graph relationships means and
res. recordi systematically 2002) determin effects on system between stemming incomplete
ng (eg. Reports, e the DVs characterize variables in a from an data that
pattern papers, most d by edges, system. analogous characterize
s in graphics, etc. significa ties, and (Chasey et al. population. real-world
data nt nodes. 2002). problems
KEYS: LR – Literature review; QS – Questionnaire survey; EI – Expert Interviews; TA – Thematic Analysis; CA – Content Analysis; MS – Mean Score; FA – Factor Analysis; SEM – Structural
Equation Modelling; SNA – Social Network Analysis; SD – System Dynamics; MWU – Mann-Whitney U Test; FSE – Fuzzy Synthetic Evaluation

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 Chapter 2 – Research Methodology

The descriptive statistical tools were employed to ascertain the effectiveness levels of the anti-

corruption measures and the criticalities of the negative constructs of corruption. The EFA tool was

employed to identify the underlying relationships between measured variables and group them into

identical constructs or latent variables, and the CFA was employed to examine how well the measured

variables represent the number of constructs. The impacts of the constructs of corruption on the

activities of the procurement process were ascertained using the network analysis tool. Lastly, the

projected outcome of a less corrupt IP process coupled with effective ACMs were modeled using the

SD tool. This was conducted to reveal the likelihood of how the impacts of corruption can be reduced

and the ACMs enhanced in a given timeframe.

2.3 Methods of Data Collection

Following the suggestions by Jick (1979) and Fellows and Liu (2005), the choice of the appropriate

research methods is usually influenced by considering the anticipated scope and depth. According to

Ameyaw (2015), a questionnaire survey is a far-reaching study, a case study is a deep examination, and

an interview falls in the middle of the two concerning the breadth and depth. A literature review

provides enormous insight into the already available knowledge and practice. It as well highlights

existing gaps in the literature. Tsai and Wen (2005) and Yi and Wang (2013) asserted that to properly

review and analyze a relevant matter in academia, it is expedient that the researcher performs a thorough

and systematic examination of previous works. Because this study examines the encompassing wide

range of characteristics surrounding corruption in infrastructure procurement, primarily in developing

countries, the selected methods of data acquisition are deemed relevant.

Furthermore, based on the exploratory nature of this study as well as the contextual and geographical

scopes used in this study, the amalgamation of literature review, questionnaire, or field survey and

experts’ interviews is deemed appropriate. Therefore, while the experts’ interviews intend to gather

purely qualitative data, the questionnaire survey aims to collate quantitative data. This approach is

known as the mixed methods approach or the methodological triangulation, which has been explicated

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 Chapter 2 – Research Methodology

in the previous section. However, the mixed methods approach has been employed in this study to

enhance the reliability and the validity of research findings (Akadiri, 2011; Creswell, 2014).

2.5.1. Literature Review

A literature review is a thorough and systematic examination of previous works by researchers (Tsai

and Wen 2005; Yi and Wang 2013; Chow 2005). The entire study commenced with a comprehensive

review of relevant previous materials from professional and academic journals, doctoral theses, and

conference papers. Other documents include research reports (both published and unpublished),

textbooks, and relevant information from the internet. These documents were consulted to retrieve every

necessary information for the study and the background knowledge of corruption in public project

procurement. The review of relevant literature enabled the gathering of both previous and current

relevant background knowledge on corruption in both construction management research and the

attributes of corruption associated with the procurement of public infrastructure. The literature review

also formed the foundation for building a very firm theoretical base for the area of research aided in the

establishment of the groundwork for realizing the aim and objectives of the study as well as addressing

the research problems.

Moreover, the literature review was conducted to 1) establish the general theoretical framework of the

study to help comprehend the topical constructs in this study; 2) understand the concept and evolution

of corruption; 3) explicate the characteristics of corruption in the context of public IP and construction

management as well as the geographical stance of corruption in developing context and the developed;

4) examine the causal factors and the forms of corruption in infrastructure procurement; 5) identify the

parties are involved in carrying out the entire public procurement process; 6) understand the anti-

corruption measures that have been developed and reported in past and current studies; 7) identify the

barriers or constraint factors that hinder the effective adoption and application of anti-corruption

measures; and 8) identify the possible methodological approaches for this study and lastly help in the

development of the questionnaire and field survey.

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 Chapter 2 – Research Methodology

This study performed six different reviews and are presented in three chapters. The first review, which

represents Chapter 3 of this study reflected the evolution and forms of corruption in public infrastructure

procurement from the standpoint of both the construction and procurement management research

(Section 1). In Section 2 of Chapter 3, a thorough review of causal factors of corruption was conducted.

Section 3 addressed the Anti-corruption measures (ACM) developed over the year to check and mitigate

the incidences and practices of corruption during the process of infrastructure procurement. As an

exemplary case study model, Chapter 4 reviews the stance of corruption in both Ghana and Hong Kong.

Lastly, Chapter 5 presents the review of corruption in IP and the development of the theoretical

framework.

2.5.2. Questionnaire Development

The data instrument used to solicit respondents’ personal experiences and their views in this study were

the questionnaire. This data collection method was adopted because it provides reliable and valid

information within a manageable or relatively shorter time frame at a reasonable cost (Ameyaw et al.

2017; Hoxley 2008). The use of questionnaires often ensures respondents’ anonymity and data

confidentiality, especially on sensitive matters, such as unethical practices in the management of

construction and engineering projects and corruption (Chan et al. 2018). Most of the variables

encapsulated in the questionnaire were derived from the extensive literature review conducted prior to

the survey and the remaining from the interviews conducted. The 5-point grading scale system was

adopted in most of the cases, and the respondents were asked to grade the variables according to the

modes of presentation.

A questionnaire was therefore developed after conducting the reviews on the various constructs of

corruption in public projects (Causes, forms, ACM, Barriers to effective implementation and

application of ACMs, etc.). The questionnaire was structured in three sections with fifteen questions.

Section A entailed an explicit and understandable cover letter that introduces the survey. Section A

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 Chapter 2 – Research Methodology

requests the personal data of the respondents. This section was constructed in two parts, Section A1 for

construction experts and Section A2 for procurement experts. Section B encompassed five closed-ended

questions on the subject matter, and Section C consists of 2 close-ended or statistical questions (focused

on Ghana). All questions in Section B and C were generated after the comprehensive review of the

germane literature on the subject matter and were verified by ten experts through a pilot test study. The

first question of Section B asked the respondents to rate how the activities within each phase of the IP

process as well as the construction processes are vulnerable to corruption and the associated forms.

Respondents are also asked to rate how the parties or professionals involved are also vulnerable to the

process mentioned above. Question 1B in Section B also sought to retrieve information on the type of

procurement system that is very prone to corruption. Question 2 of the same section, requested

information on the criticality of the identified CFs in IP using the linguistic ratings from 1 to 5.

Question 3 solicited the respondents’ views on the effectiveness of anti-corruption measures, and Q4

sought to find out the criticality of the barriers that hinder the effectiveness of the ACM in IP. Lastly,

Q5 of Section B was established to measure the pressing causal factors that trigger corruption in IP.

This question required the potential respondents to rate how probable the identified variables are to

occur and should in case they occur, how severe is the risk are to the procurement of infrastructure.

This, therefore, represents the entire framework of the questionnaire to be distributed during the survey.

However, in the case of Ghana, an additional section containing two more questions were included to

develop a different questionnaire after identifying an appreciable number of corruption indicators noted

in procurement and contractual works. Explications on how the factors were identified are provided in

Chapter 4. Section one deals with the irregularities identified in procurement and contracts. The second

section consist of recommendations suggested to help in dealing with the irregularities identified in both

procurement and contracts. The final section requires respondents to share their views on how familiar

they are with the legal interventions in the form of Acts, Legislation, and Policies against corruption

stipulated by the Ghanaian government right from independence to date. They are as well required to

rate their level of effectiveness base on how familiar they are with the stipulated interventions.

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 Chapter 2 – Research Methodology

2.5.3. Ranking Scales

The ranking scales adopted in construction management research vary regarding odd numbers starting

from five to eleven. This enables researchers to solicit for the views of respondents concerning an issue

with several variables. The five-point Likert scale ranking system was adopted in formulating the

questionnaire. Several CM based research works on corruption have adopted this system. For instance,

Shan et al. (2016), Le et al. (2014), Bowen et al. (2012), etc. The five-point ranking system was

employed on a number the bases, which included. They include: 1) the ease of presenting items and

speedy administration, the ability to eliminate the problems common to ordinal measurement scale such

as central tendency (Cronbach, 1951; Chan and Tam, 2000). 2) The provision of explicit diversities of

probable opinions to the respondents that can facilitate the structural analysis (Pallant, 2005). Although

this rating system is vulnerable to response bias, according to Revilla et al. (2013), the five-point

categories provide quality data as compared to the other higher point systems such as 7 and 9. Table

2.2 illustrates the scale definitions used in this study. The other ranking systems (e.g., 7-point and the

9-point ranking systems) are known to be complicated and has the potency of putting some respondents

from responding to all the questions (Pitt et al. 2009).

Table 2.2: Ranking Scores Definitions

Ranking Scores (RS) Definition
RS PCPV CF ACM BEA, CC, and Forms
CI
1 Not Vulnerable Not Critical Not Effective Not Risky Bribery Acts
2 Less Vulnerable Less Critical Less Effective Less Risky Fraudulent Acts
3 Neutral Neutral Neutral Neutral Collusive Acts
4 Vulnerable Critical Effective Risky Extortionary Acts
5 Highly Very Critical Very Effective Very Risky Discriminatory
Vulnerable Acts
PCPV: Procurement and construction Process CC: Causes of corruption
Vulnerability CI: Risk Indicators/ irregularities
CF: Corruption Forms BEA: Barriers to the effective application of
ACM: Anti-Corruption Measures ACM

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 Chapter 2 – Research Methodology

2.5.4. Questionnaire Pilot Study

After the initial development of the questionnaire, a pilot study was conducted to assess the entire

comprehensiveness, relevance, and reliability before disseminating to the targeted respondents for their

valuable responses. A total of eight experts from world-renowned institutions and academics were

therefore selected based on their knowledge and experience in the subject matter, as revealed by their

publications and their positions within their various institutions as well as their availability and

willingness to respond to the survey (Shi et al., 2013; Potbhare et al., 2009; Chan et al., 2009).

Specifically, they were consulted to examine the questionnaire’s appositeness with regards to the

lucidity of the questions, wordings, definitions, coherence, structure, and length, factors’ relevance, the

level of complexity as well as the use of technical terms (Oyedele, 2010; Ameyaw, 2015).

Per the feedbacks of the experts, the questionnaire was reviewed and thoroughly revised to enhance its

quality and appropriateness, thus making it more suitable for the main survey. For instance, some

experts suggested to reduce some of the factors, provide either a footnote or an appendix to define

statements that may seem complex and ambiguous to the targeted respondents. In other instances, some

of the factors were merged to form a single factor. An example is a provision of the appendix in the

questionnaire to provide clear explanations of the various forms of corruption. These are just a few of

many revisions that were suggested by the experts to improve the quality of the questionnaire in its

present form.

2.5.4.1 Sampling Size and Sampling Technique

Sampling, according to Strydom et al. (2005) is simply the act of taking a part of the entire population

to represent that exact population. Naoum (2008) stated that when considering a larger population, the

percentage of the sample size needs to be smaller and vice versa, that is, if the entire population is

smaller, the sample size should encompass a relatively larger proportion of the population. To attain an

accurate conclusion and a more concrete prediction, the researcher should consider using a larger

sample than a relatively smaller sample (Polit and Hungler, 1999).

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 Chapter 2 – Research Methodology

Sampling is an essential and necessary aspect of any research study due to the constraint factors posed

by cost and time (Altmann, 1971; Patton, 2005). Kothari (2004) emphasized that for a researcher to

develop a suitable sample for the study, he must take into consideration the following building block:

the demographical pattern for the study, the sampling unit, the source list, the sample size, parameters

of interest, budgetary constraints and sampling procedure.

The sample selected for this study comprises of experts involved in the modus operandi of construction

projects including planning, procurement, and management of projects. Categorically, they consist of

professionals from the construction industry and the procurement sector of Ghana and Hong Kong.

Although the concept of corruption may be regarded as a broad or general topic, only the experts who

are involved in the procurement process were sampled out for both the questionnaire survey and experts’

interviews. There is also no well-defined or comprehensive population to randomly draw out a sample

from. Therefore, a random sampling approach cannot be adopted in this survey. In this situation, the

best approach adopted was a non-probability sampling where the respondents targeted are selected

based on their expert knowledge on the subject matter as well as their willingness to participate in the

survey but not based on random selection (Sandelowski, 2000; Wilkins, 2011; Teddlie, 2007). The

snowball and purposive sampling methods (i.e., non-probability sampling methods) were adopted.

These techniques were used to identify the experts with adequate expertise and thorough knowledge on

the subject matter. Although only one of these two approaches can be suitable for the entire research,

the two sampling techniques were adopted to increase the sample size.

2.5.4.2 Purposive and Snowball sampling

Polit and Hungler (1999) delineate the purposive sampling technique to be a type of non-probability

sampling technique, which involves the mindful selection of certain subjects to be included in the study.

According to Bernard (2002), most types of research design compel the researcher to take decisions

concerning the individual participants who would stand in a position to give the appropriate and needed

data, in terms of both depth and relevance. This type of sampling technique was adopted based on the

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research design, purpose, and practical implications of the study. In simple terms, the researcher agrees

on what he needs to know, and seek to find people who are willing and can provide the needed

information by their experience or knowledge (Lewis and Sheppard, 2006; Tongoco, 2007).

Teddlie (2007), explicates purposive sampling as a technique that involves the selection of certain cases

or units, generally based on a specific purpose rather than randomization. Thus, a combination of

multiple approaches was consulted to identify and retrieve a list of targeted public and private

organizations potential respondents or departments within the targeted institutions. They included the

direct request of information from the public institutions and industry organizations, internet

publications, and related relevant information. After the generation of the list of potential institutions,

invitation letters were officially sent to the senior managers and directors of the institutions to participate

in the survey. They were also requested to nominate their top management staff with experience and

knowledge in the IP process as well as corrupt incidents that pose threats to the processes. This process

is aimed at helping solicit a potential list of expert individuals (Teddlie, 2007; Moglia et al., 2009). The

potential respondents suggested at this level were also be invited and requested to participate in the

survey.

On the flip side, the snowball sampling technique, the experts identified during the purposive sampling

stage were resourcefully requested to share or help identify other potential experts with thorough

knowledge on the subject matter. Therefore, in the quest to select suitable respondents at this level, the

following criteria guided the selection: the respondent should possess deep and pragmatic working

experience in the procurement of infrastructure works, and secondly, the potential respondent should

be involved or up to date with contemporary procurement trends. The selection criteria were framed to

consider respondents who were willing to participate in the survey and at the same time, accessible. A

selection process prescribed above was strictly followed to invite suitable participants to take part in

the survey. This was carried out to ensure reliability and the credibility of the responses. Also, since

this study depended on the experience and knowledge of the experts, it was expedient to ensure first-

rate standings of the potential experts as well as the robustness of the approaches of data collection.

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Regarding the snowball sampling technique, the initially identified experts were opportunistically asked

to share related information concerning other potential respondents (Moglia et al., 2009). Following

criteria guided the choice of potential respondents recommended by their fellow practitioners:

• Have actively been involved in either research or policymaking concerning the subject matter

(corruption) with regards to the construction and engineering sectors.

• Have robust practical or working experience in either the records or happenings of corrupt

activities in the industry.

Since this study is skewed towards corruption-related studies in IP, there was a thoughtful effort ensure

a very apropos representation of experts from different backgrounds who are actively involved in

infrastructure procurement and the nature of corruption (Powell, 2003; Robinson 1991; Ameyaw,

2014). Therefore, the list of the potential participants consulted were made up of a wide range of

professionals from the construction industry and public procurement institutions of Ghana, anti-

corruption institutions in Ghana (NACAP, 2011) and academics or scholars who have expert knowledge

on the subject matter.

2.6 DATA PROCESSING AND ANALYSIS

After gathering the study data, there is a need for data processing and analysis by the stipulated aim and

objectives as well as the established purpose of the study at the initial stage of developing the framework

of the research plan. The need for data processing and analysis is very vital for scientific study and also

to ensure that every necessary and relevant data or information for conducting the anticipated

comparisons and analysis is available. According to (Kothari, 2004), data processing refers to the

practice of data editing, coding, categorization, and tabulation of the gathered data to make the data

amenable to analysis. Analysis, on the other hand, refers to the computation or calculations or

simulations of some measures together with searching for relational or correlational patterns that exist

among the groups of gathered data. It relates to the ways by which answers are found through

interpreting the gathered data (Strydom et al., 2005). Since explaining the raw data is either impossible

or difficult, data description and analysis must first be done, and then the analysis results interpreted

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(Strydom et al., 2005). The analysis here also means ordering, categorizing, summarizing, and

manipulating data to obtain the solutions needed to answer research questions. The statistical methods

employed for data analysis included a mix of both parametric (t-test) and non-parametric (such as mean

score ranking, Factor analysis, Kruskal-Wallis one-way ANOVA test, Kendall’s coefficient of

concordance (W), Mann Whitney U Statistics) among others.

2.6.1. Mean Score (MS) Ranking Technique

The MS ranking technique has been recognized as one of the most important and critical tools employed

by many researchers to determine the significance or the relative importance of individual factors to

enable the easy identification of important factors. In most CM research papers on corruption, Le et al.

(2014) used it to determine the significant causes and vulnerabilities that trigger the incidence of

corruption in the Chinese Construction public sector. Bowen et al. (2015) also employed the MS ranking

technique to assess corruption in the South African construction industry from the perspectives of

construction professionals and clients. Several studies reviewed in this research study also employed

the MS technique in addressing and determining various factors across diverse topics on the subject

matter. The mean score is calculated using the formula below:

5𝑛5 + 4𝑛4 + 3𝑛3 + 2𝑛2 + 1𝑛1⁄

𝑀𝑆𝑛 = 𝑁 Eqn. 2.1

Where MSn = The MS for nth factor, n = respondents’ scores based on a 5-point scale (from 1-5) and

N= the total number of expert respondents. The MS ranking technique was therefore employed to rank

the identified variables within their respective constructs.

2.6.2. Mann Whitney U (MWU) Statistics

The Mann-Whitney U test is conducted to analyze and identify the significant differentials that exist

among the factors ranked by the respondents from the two different jurisdictions (Ghana and Hong

Kong). Chan et al. (2011) emphasized that, as a nonparametric test, the Mann-Whitney U test is

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employed to observe the relationship of ordinal data with two independent samples. The MWU test too

is as well preferred for the following reasons as highlighted by Sheskin (2011): (1) unequal sample sizes

of the two independent jurisdictions, that is, developing and developed contexts and also, the data set

is not assumed to follow any distribution pattern. A predefined significance level of 0.05 is established

for the MWU test to be performed. A significant perception between developing and developed

contexts’ respondents is highlighted to identify in the case where the p-value or the predefined

significance level is less than 0.05 and vice versa situation.

2.6.3. Kendall’s Coefficient of Concordance (W)

Kendall’s Coefficient of Concordance (W) is primarily employed to measure the degree of agreement

between the rankings or ratings by experts (Kendall and Gibbon, 1990). According to Schmidt (1997),

it can also be employed to determine the level of consensus or any level of agreement among or within

the ratings of a group and their relative consensus strength. The following advantages had extended the

application of this tool. This method is reported by several studies to be easy and simple to use, the

simplicity of tool application and interpretation, among others (Shi et al., 2013; Osei-Kyei and Chan,

2015; Lam et al., 2009). The degree or range of Kendall’s W begins from 0 to 1, where 0 symbolizes

no agreement, and 1 represents perfect agreement or concordance. According to Siegel and Castella

(1988), the formula for Kendall’s W computation is given below:

∑𝑛 (𝑅 +R)
𝑛
W=12𝑝2 𝑖=1
(𝑛3−𝑛)−𝑝𝑇
Eqn. 2.2

Where n represents the number of factors, Ri represents the ratings assigned to the ith variable or factor;

R denotes the Ri mean values; p signifies the number of respondents, and T stands for correction variable

or factor for the tied ratings. Siegel and Castellan (1988) indicated that the applicability of Kendall’s W

test is only feasible and possible when the number of attributes or factors is below 7. The chi-square

test value is therefore employed any time the number of attributes is greater than 7.

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2.6.4. Risk Importance Index (Expected Value)

Some risk management scholars see risk as the likelihood that a risk variable or component (for instance

disregard for public procurement act regulations, variations to contract or fragmentary procurement)

happens paralleled with its severity to affect the entire IP or construction process. With this concept, IP

risk is measured as a combined function of occurrence probability as well as severity, which can be

estimated using this formula:

Risk = f (probability and severity) eqn. 2.3

Risk impact (probability × severity)0.5 eqn. 2.4

This technique, also known as expected value, is a well-established approach to quantify risks in

decision theory or calculate average risk (Tweeds, 1996; Carter et al., 1994). As a reliable approach to

risk quantification and analysis, this technique has been adopted by several studies (Shen et al. 2001;

Ameyaw, 2015; Chan et al., 2011). For instance, Ameyaw (2015) employed this technique to evaluate

the importance of risk factors in PPP water supply projects in Ghana. In this study, this technique is

employed to quantify the risk indicators of corruption in public IP.

2.6.5. Reliability Test

The reliability test measures the consistency in the data collected (Memon et al. 2011). There have been

previous tools such as split-half reliability estimate and Kuder-Richardson estimate, which have been

adopted in the past, and the latter still being used. However, the dominant reliability tool employed by

many researchers today is the Cronbach also known as the coefficient alpha. Cronbach’s Alpha is one

of the most popular tools used to estimate the internal consistency reliability and assess the reliability

and consistency of scales. It is used to determine the average internal consistency or the interrelations

of variables in survey instruments to measure the reliability thereof. According to Santos (1999), the

reliability of survey instruments and scales employed to gather responses from experts on a set of

variables or factors is very vital for researchers to identify whether the factors in a survey instrument

will continually yield stable and reliable results over a repeated number of times. The alpha coefficient

is adopted in this study to examine whether the general statements and the variables within the various

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constructs regarding corruption in infrastructure procurement in the questionnaire are reliable to

measure the primary constructs, which this study intends to measure.

The Cronbach’s alpha coefficient is designated by the symbol (α), and its value ranges from 0.00 to

1.00. The range values represent the lowest and highest respectively and have direct relationships with

the degree of reliability. Meaning, the higher the value of α, the higher the scale’s reliability (Cronbach,

1951; Santos, 1999). The reliability of the data set is considered low if the Cronbach’s Alpha (α)

coefficient is below 0.3, which makes the data unreliable. The reliability of the data set is, on the other

hand, considered high if the α coefficient is above 0.7, which is also an indication of high internal

consistency and, therefore, highly reliable and acceptable (Memon et al., 2011; Nunnally, 1978).

According to Meeampol and Ogunlan (2006) also, a reliability coefficient of 0.5 to 0.6 range or more

is very desirable and considered adequate for any form of analysis. According to Li (2003), the value

of (α) is calculated using the formula below:

𝑘 𝑐𝑜𝑣/𝑣𝑎𝑟
(α) = Eqn. 2.5
1+(𝑘−1)𝑐𝑜𝑣/𝑣𝑎𝑟

Where (α) = Cronbach’s alpha coefficient, k represents the number of scale items; var = scale items

average variance and cov = average covariance between scale items. Moreover, when there are

standardization and common variance among the factors, the formula can be simplified, as shown

below:
𝑘𝑟
(α) = ;
1+(𝑘−1)𝑟

where r represents the average correlation among the scale items.

2.6.6. Factor Analysis

Factor analysis (FA) is a collection of methods used to examine how underlying constructs influence

the responses on some measured variables and also with the goal of using a few hypothetical variables

to represent a larger set of variables (Kim and Mueller, 1978; Chan et al., 2010). There are two types

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of factor analysis: exploratory and confirmatory. Exploratory factor analysis (EFA) attempts to discover

the nature of the constructs influencing a set of responses. Confirmatory factor analysis (CFA) tests

whether a specified set of constructs is influencing responses in a predicted way. Factor analyses are

performed by examining the pattern of correlations (or covariances) between the observed measures.

Measures that are highly correlated (either positively or negatively) are likely influenced by the same

factors, while different factors likely influence those that are relatively uncorrelated. It is commonly

employed to examine the relationship among a given collection of observed variables and establish the

probable variables capable of measuring or determining characteristics of the same underlying

principles (Field, 2005; Hair et al., 1998; Norusis, 1993). In which case, the principal factors are

developed out of the large number of variables that have been reduced to smaller components. The

developed principal components can, therefore, be used to represent or explicate the entire data or

intricate phenomena easily and adequately. As a result, FA has recently been one of the statistical tools

developed to become widely accepted and commonly employed in construction management research

(Ameyaw, 2015) as well as topics on corruption in construction (Le et al., 2014).

Moreover, the principal component factor analysis is deemed to be an apropos option among

the various types of FA for data reduction (Yeung et al., 2010). With the stipulated strength of CPFA,

this study employs CPFA to analyze and develop the fundamental groupings of the causes, risk

indicators or vulnerabilities, anti-corruption measures, and barriers against the effective application of

anticorruption measures in public infrastructure procurement. Also, the factor-solutions evolving from

PCFA lay a very strong underpinning for additional complicated analysis, and this adds on to the

significant merits possessed by PCFA. Chan et al. (2004) stipulate four necessary steps involved in

carrying out FA. They include: (i) establishment the significant variables (e.g., Causes of corruption)

involved in public infrastructure procurement, (ii) compute the correlational matrix for the variables,

(iii) extract and rotate every component and lastly, (iv) name and interpret the principal components as

the foundational constructs.

Before carrying out the FA process, a number of tests need to be performed to establish the suitability

or appropriateness of FA for factor rotation. The tests include Kaiser-Meyer-Olkin (KMO) and Bartlett's

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Test of Sphericity (Fox and Skitmore, 2007). Whereas the KMO measures the sample adequacy,

Bartlett's Test of Sphericity is used to determine the existence of relationships among the variables,

which aids in determining whether or not the correlation matrix of the population is an identity matrix

(Hair et al., 1998). An appropriate dataset for factor analysis should have a p-value less than 0.05, which

means that Bartlett's Test of Sphericity is significant, and KMO index should exceed 0.5. George and

Mallery (999) asserted that these suggestions are widely accepted and adopted in construction

management research.

2.6.6.1 Extractions and Rotation of Factors.

According to Nousis (1993), the extraction and rotation of factors are the two primary procedures

involved in FA. The extraction of factors is essential to develop variables by factor solution (principal

component analysis), whereas factor rotation is conducted to enhance how well to interpret the

variables. Usually, the first factor-solution explicates the largest amount or degree of the sample

variance, while the variance-explained that is remaining is shared across the other factor solutions.

Varimax rotation, which is one of the most employed rotation methods in construction management

research, is employed in this study to enable easy clarification and interconnections among the variables

of both observed and latent variables (Oyedele, 2010; Chan et al., 2011). Moreover, with regards to

Eigenvalues, which represent the sum of squared factor loading of the factors, which represents the

degree of variance explained by a factor (Nousis, 1993). Based on the Kaiser criterion, this study retains

only factors with eigenvalues greater than one.

2.6.7. PLS-SEM

According to (Shan et al., 2016), PLS combines the following techniques to simultaneously examine

data and theory: principal component analysis, path analysis, and regression analysis. PLS is made up

of two types of variables, namely observed variables, and latent variables. For observed variables, they

can be measured directly, whereas latent variables are hypothetical or theoretical constructs that are

inferred or contingent from observed variables. The results obtained from PLS are made up of inner

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models, also known as structural models, and outer models also called measurement set. The

measurement models examine the correlation among the observed variables, for example, causes of

corruption and their associated latent variables (the formed constructs or underlying groupings of causes

of corruption). The inner models or structural models assess the interconnections between the latent

variables, which are examined. The PLS process is made up of multiple stages that involve three

prominent or relevant steps, namely: specification of models; inner model evaluation; and outer model

evaluation. In-depth explications have been made in the study of Hair et al. (2014). PLS-SEM is

employed in this research to model the relationship between the causes of corruption and the risk factors,

anti-corruption measures, and the barriers to the effective application of anti-corruption measures. In a

more certain connotation, the technique is adopted to investigate the causal mappings between the

causes of corruption and the indicators (vulnerabilities) to corruption in the Ghanaian public IP

processes.

Moreover, as a multipurpose and multivariate analytical method in statistics, the PLS-SEM technique

is used to simultaneously examine the relationships for correlational mappings among factors in a

theoretical model (Le et al., 2014). This technique has become a very vital and common analytical

technique in construction management research used to examine complete and emerging concepts and

theories. The application of SEM in CM research has been successful because of these basic

underpinnings: its potency to measure the cause and effect relationships among latent variables and it

can also be used to examine the measured latent variables (Chan et al., 2010; Hair et al., 2012). There

are two primary types of SEM, namely Covariance-Based SEM and Partial Least Squares SEM

developed by (Chin, 1998). This study adopts the PLS techniques due to the following stipulations.

As compared to the covariant based SEM, the PLS possesses some advantages that have made it more

successful in its adoption and use and has seen extensive improvement and use in various disciplines in

recent times. According to (Afthanorhan 2013; Hair et al. 2011), some of the most protuberant

justifications made by researchers who adopt the use of PLS are data distribution, the ability to use a

small sample size and the use of formative indicators. Although this study does not anticipate a small

sample size, PLS is still employed should in case a lower rate of the targeted respondents responds to

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the questionnaire due to the sensitivity and nature of the topic. Reinartz et al. (2009) asserted that this

technique is better adopted for a sample size that is relatively smaller and problematic for CB SEM to

handle. This rationale also applies when highly complicated models are involved. These advantages

have paved the way for PLS in recent years to be embraced and used extensively in construction

management research (Le et al., 2014; Shan, 2015).

2.6.8.1 The application procedures of PLS-SEM

In conducting or using the PLS approach, these five procedures are usually followed. Examination of

the data attributes, model specification and estimation, interpretation of the model, and lastly validation

of the developed model.

2.6.8.2 Data attribute examination.

Stage one involves the examination of the sample size and data distribution. There is no need for

distributional requirements in PLS-SEM due to its ability to handle very skewed or lopsided data

distribution (Hair et al., 2012; Shan, 2015). As discussed earlier, this tool can realize very robust and

accurate results even with a very small sample (Darko et al. 2017). The example with a small sample

size of 20 was indicated by the Monte Carlo simulation outcome reported in the study of Chin and

Newsted (1999).

2.6.8.3 Model Specification

At this stage, there is the building or development of measurement models as well as a structural model.

Shan (2015) indicated that the development of the measurement and structural models are usually based

on one’s knowledge and experience in their respective fields being researched, theory review as well as

literature review (Shan 2015, Aibinu and Al-Lawati, 2010).

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2.6.8.4 Model Estimation

In stage 3, the estimation of the theoretical model parameters is conducted that is, the SEM analysis

performs the parameters estimation for the relationships between the measurement items and their

respective loadings, which are the latent variables and paths coefficient which represents the mappings

between the various/different latent variables (Kline, 2010). However, since PLS-SEM takes every

single latent variable as an approximate of its measurement items block. Therefore, the first phase of

the estimation consists of iterative dimensions of simple and different regressions that is contingent on

the specific model. This is conducted until there is an answer that converges on a set of weights used

for calculating the latent variables scores (Shan, 2015). As soon as the outcomes for all the latent

variables are achieved, the stages that follow consist of simple non-iterative applications of ordinary

least squares regressions for obtaining mean scores, location parameters, path coefficients, and loadings

for the measurement items and latent variables (Shan, 2015; Chin 1998). The fourth and last processes,

namely model evaluation and validation, are explicated in chapter nine.

2.6.8. Fuzzy Set Theory (Fuzzy Synthetic Evaluation)1

The FSE technique is regarded as a branch of the fuzzy set theory developed by Zadeh (1965), which

is often employed to quantify multi-attributes and multivariate (Osei-Kyei and Chan 2017; Hu et al.

2016). According to Ameyaw and Chan (2017) and Khatri et al. (2011), the FSE is a fuzzy multicriteria

decision-making approach whereby individual factors of a construct are synthesized into a single score.

Moreover, the opinions on the vulnerability levels of the procurement process by the experts are

considered to be uncertain and typically subjective (Shan et al., 2015). Accordingly, FSE uses linguistic

expressions (terms or variables) to represent and capture experiential knowledge of the survey

respondents (Boussabaine, 2014), which helps to resolve uncertainty and subjectivity associated with

the responses of the survey respondents (Ameyaw and Chan, 2015). The use of linguistic variables

1
This section is fully or partially published in the following journal monograph: Owusu, E. K., Chan, A. P., &
Ameyaw, E. (2019). Toward a cleaner project procurement: Evaluation of construction projects’ vulnerability to
corruption in developing countries. Journal of Cleaner Production, 216, 394-407.

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enables the respondents to qualitatively assess the vulnerability levels of the 21 procurement activities

(Boussabaine 2014).

The FSE technique employs the application of membership degrees in a given set instead of a strict true

or false membership (Tah and Carr, 2000). Simply put, rather than using absolute terms or values such

as 0 and 1 to represent an elements association to a fuzzy set, the FSE tool expresses the element’s

belongingness to a fuzzy set in terms of varying degrees of relation. The degree or extent of membership

can, therefore, consider any value within a closed range of 0 and 1 and the obtained value characterizes

the degree or measure to which the element belongs to a fuzzy set (Ameyaw et al., 2015; Tar and Carr,

2000; Kasirolvalad et al., 2006).

The assessment of the overall vulnerability level of a project to corruption encapsulates the examination

of the individual principal constructs of the procurement process (i.e., pre-contract stage, contract stage,

contract administration stage and the post-contract stage) levels of vulnerability on one level and the

activities within each construct or procurement stage on another level. A similar operation is performed

on the principal constructs and variables of ACMs. In this instance, each primary component or

construct is examined concerning its vulnerability level (in the case of the procurement process). This

leads to the quantification of the overall vulnerability level of the procurement process. The multi-level

fuzzy evaluation technique is often adopted to evaluate these multi-construct and multilevel challenges

inherent in assessing a project’s vulnerability to the incidence of corrupt practices.

Given that the determination of the susceptibility or vulnerability index of an infrastructure project is

by nature fuzzy and often drawn on the subjective judgment of the experts, the FSE technique is deemed

suitable (Boussabaine 2014; Ameyaw et al. 2015). This study also encapsulates three levels of

vulnerabilities, which are: vulnerabilities associated with procurement activities (level 1),

vulnerabilities associated with procurement stages of constructs (level 2), and the overall vulnerability

associated with the entire procurement process (level 3). Inferring from these three levels, it is,

therefore, apropos to employ the FSE technique to develop a vulnerability index and assessment model.

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Lastly, The FSE technique was most preferable as it provides an objective index as compared to the

ordinary weighting method. The steps for developing the vulnerability index are outlined below.

2.6.9.1 FSE Procedure

The FSE decision-making model comprises the following stages (Liu et al., 2013; Xu et al., 2010; Wei

et al., 2010; Ameyaw, 2015):

1. Establishing a set of factors or basic criteria, U= {𝑢1 , 𝑢2 , 𝑢3 ….., 𝑢𝑚 } where 𝑢𝑖 = (i=1,2,3,…..m)

represents the ith factor estimation;

2. Create a set of grade substitutes which are detailed in linguistic terms for the variables V= {𝑣1 , 𝑣2 ,

𝑣3 ….., 𝑣𝑚 } where 𝑣𝑗 = (j=1,2,3,…..m) represents the evaluation grade j. In simple terms, the grade

substitute represents the employed measurement scale.

3. Create a set of weightings by evaluating the weight vectors of the evaluation variables as: W= {𝑤1 ,

𝑤2 , 𝑤3 …..,𝑤𝑚 } where 𝑤𝑗 = (j=1,2,3,…..m) signifies an evaluation factor I weighting and (0 ≤ 𝑤𝑗 ≤ 1);

4. Determination of a fuzzy evaluation matrix R=(𝑟𝑖𝑗 )𝑚 × 𝑛 where (𝑟𝑖𝑗 )expresses the degree to which

an alternative 𝑣𝑗 satisfy the basic criterion 𝑢𝑖 in a fuzzy situation. The matrix of the fuzzy function R

can be expressed as:

𝑟11 𝑟12 ⋯ 𝑟1𝑛

𝑟21 𝑟22 𝑟2𝑛
R=[ ⋮ ⋮ ⋮ ]
𝑟𝑚1 𝑟𝑚2 ⋯ 𝑟𝑚𝑚

5. Estimate the final results of the fuzzy evaluation by taking into consideration the weightings

determined in step 3 and the matrix in step 4 using the equation given below:

D=W●R= (𝑑1 , 𝑑2 , … 𝑑𝑛 ) (2.6)

Where D stands for the final evaluation matrix; W=weighting vector; R= fuzzy evaluation matrix and

● represents the fuzzy composition operator.

Mathematical Functions of FSE

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The effective application of the FSE technique demands the selection of an apropos function that

passably analyses the contents (that is, membership functions and weightings) of the final evaluation

matrix equation (see above, D). According to Lo (1999) and Lai and Hwang (1994), there are four

primary functions of FSE.

M(∧, V), b𝑗 = ⋁𝒎
𝒊=𝟏(𝑤𝑖 ∧ 𝑟𝑖𝑗 )∀ b𝑗 ∊ B (2.7)

M (●, V), b𝑗 = ⋁𝒏𝒊=𝟏(𝑤𝑖 × 𝑟𝑖𝑗 )∀ b𝑗 ∊ B (2.8)

The equations listed above (7.1 and 7.2) are regarded to be more applicable to single-items conditions

due to their consideration of key attributes and ignore or disregard minor attributes. For instance, in

assessing project risks, both equations are deemed unsuitable for processing the contents of Eq. D,

because each attribute should have an effect on the whole index or level or risk.

M (●, ⊕), b𝑗 = 𝑚𝑖𝑛 (1, ∑𝒎

𝒊=𝟏 𝑤𝑖 𝑟𝑖𝑗 )∀ b𝑗 ∊ B (2.9)

M(∧, +), bj = ∑𝒎
𝒊=𝟏(𝑤𝑖 ∧ 𝑟𝑖𝑗 )∀ b𝑗 ∊ B (2.10)

According to Lo (1999), some of the data with leaser weightings are ignored by the min-operation in

Eq. (2.10) and hence produces a similar output as in the cases of equations (2.7) and (2.8). The

application of the FSE tool is demonstrated later in this study. More thorough explications regarding

the adoption and application of the FSE technique are also presented later in the study.

2.6.9. System Dynamics

System dynamics, which was created during the mid-1950s by Professor Jay W. Forrester of the

Massachusetts Institute of Technology, can be defined as “The investigation of the information-

feedback characteristics of (managed) systems and the use of models for the design of the improved

organizational form and guiding policy” (Forrester, 1961). It is a modeling methodology, which is

employed to assist in the understanding of complex problems and provide an approach for representing

the dynamic relationships between variables in a system. With a foundation of decision making,

dynamic relationships, feedback analysis, and simulation, systems can be defined and modeled in a

manner that allows experimentation in a laboratory setting (Chasey et al., 2002). System dynamics is

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concerned with creating models or representations of real-world systems of all kinds and studying their

dynamics (or behavior). In particular, it is concerned with improving (controlling) problematic system

behavior. The purpose of applying system dynamics is to facilitate an understanding of the relationship

between the behavior of a system over time and its underlying structure and decision rules

(Wolstenholme, 2003). The system dynamics modeling technique (Sterman, 1992) can incorporate the

causality links between the variables in a construction system and the activities involved in the

production process. The model explicitly delineates and simulates the relationships between each

variable mathematically. Once the system dynamics modeling technique identifies the critical factors,

the chances of successfully implementing a set of fast-track activities can be greatly increased (Peña-

Mora, and Li, 2001). SD is therefore regarded as a strategic methodology or approach that deals with

the complexity - interrelationships and dynamics - of any social, economic, and managerial system

(Yuan et al., 2012).

The application of SD has extensively been employed in various areas in construction management-

related research over the last two decades, and this has revealed the extent to which SD application has

been adopted to analyze complex issues in CMR. For instance, any complex social systems, particularly

in industrial contexts, economic, social, and environmental systems of all kinds (Rodrigues and Bowers,

1996; Park 2005; Turek, 1995). The next section and diagram represent the processes involved in the

application of SD. However, as indicated in other tools, further explication to the processes is presented

later in this study.

2.6.10.1 Processes Involved in SD

• Conceptualization

• Define the purpose of the model

• Define the model boundary and identify key variables

• Describe the behavior or draw the reference modes of the key variables

• Diagram the basic mechanisms, the feedback loops, of the system formulation

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• Convert feedback diagrams to level and rate equations

• Estimate and select parameter values

• Testing

o Simulate the model and test the dynamic hypothesis

o Test the model’s assumptions

o Test model behavior and sensitivity to perturbations

• Implementation

o Test the model’s response to different policies

o Translate study insights to an accessible form

Following every single step within the four main themes under the SD process, this study employs SD

to help understand of complex nature of corruption in IP processes and also provide an approach for

representing the dynamic relationships between variables within the corruption constructs and the IP

processes as well as the entire IP system as a whole.

2.6.10. Content Analysis

Content analysis refers to a set of both qualitative and quantitative techniques for gathering and

examining data from electronic, print, and verbal communications with extensive applications in

different fields of research ranging from education, construction to nutrition. Textual data from open-

ended questions focus groups, and interviews can be analyzed using content analysis. However, the

selection of methods is largely dependent on the length and type of data to be examined, technological

capabilities, researcher’s preferences, and the desired results (Kondracki et al., 2002). In the field of

construction project management research, content analysis has been extensively employed to analyze

textual information and data in both literature review studies and empirical research as well. For

instance, Chan and Owusu (2017) employed this technique to assess and analyze papers selected for

this section of the review study on forms of corruption in the construction industry.

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2.6.11.1 Procedures and Applications

According to Mayring (2008), the qualitative content analysis process model can be broken down into

four distinct phases. They are discussed below:

1. Material Collection: The material or data to be analyzed is determined, and the analysis unit is

defined;

2. Descriptive analysis: At this level, there is an assessment of the features of materials/data.

This provides a background for the following content analysis;

3. Category selection: Here, there is the selection of structural scoped as well as associated

analytic categories which are needed to be applied to the gathered material;

4. Material Evaluation: the gathered materials are assessed based on their analytic scopes.

The divisions into different process phases or procedures are deemed very crucial aspects of

qualitative content analysis because they allow inter-subjective verifiability and traceability, which

makes it different from most or other hermeneutic or qualitative assessment techniques (Mayring,

2008; Duriau et al., 2007)

2.6.11.2 Validity and Reliability Issues of CA

Analogous to other analytical techniques, the overall aim of this technique (CA technique) is underlined

by its validity and reliability issues. This is done to determine and record at least inter-subjective or

relatively objective features of messages (Neuendorf, 2002). By this, if the outcome of CA is founded

on multiple of different judgments of a sole researcher, then it is clear that the results are rather

contestable. However, by including more than just a few numbers of researchers into the CA technique,

reliability and validity of sampling (literature), as well as the analysis of the data, may be improved

(Duriau et al., 2007; Neuendorf, 2002). Particularly, with regards to text analysis, one may differentiate

the exploration for latent or explicit content. Whereas the former relies on the interpretations of

researchers (mental schemes), indicating a pressing challenge, the latter can easily be assisted by

software tools. As an apropos tool for analysis, CA was employed to analyze the literature review.

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 Chapter 2 – Research Methodology

2.7 Chapter Summary

Chapter two detailed the methodology that is adapted to realize the success of this research. It explicated

into detail all the quantitative and qualitative research methods that are employed throughout the

research process. They include germane literature review, case study, structured interviews, descriptive

analysis, social network analysis, factor analysis, partial least squares structural equation modeling,

analytical hierarchy process, fuzzy set theory, and system dynamics. The theory behind the adoption

and application of these techniques to achieve the stipulated aim and the objectives have been explained

in this chapter.

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 Chapter 3 - Contemporary Review of Corruption

CHAPTER 3 - A CONTEMPORARY REVIEW OF CORRUPTION2

3.1 Introduction

This chapter discusses the foundational constructs of corruption in the context of construction project

procurement and management. As presented in the outline, the main themes include the different forms

or manifestations of corruption and their causal factors, the contextual risk irregularities in the context

of public project procurement. The remaining include anti-corruption tools and measures stipulated to

extirpate or mitigate corruption and the barriers that hamper the effective application of anti-corruption

measures. However, it must be emphasized that since all the different sections of the review followed

an analogous and systematic technique of document retrieval and analysis, all the reviews were

conducted independently based on the construct or the subtopic of corruption under review. For

instance, the papers selected for the review of the forms of corruption were somewhat different from

those selected for the causal factors of corruption and the ACMs. This section is, therefore, dedicated

to the exploration of comprehensive reviews of all the identified constructs in the established order of

presentation.

3.2 Forms of Corruption

Past studies have identified various forms of corruption in the industry (Dorée 2004; Brown and

Loosemore 2015; Bowen et al. 2012; Le et al. 2014; Olawale and Sun 2013; TI 2016). The construction

industry has been identified as the most corrupt sector, and the procurement sector is also branded to be

the most vulnerable sector to the incidence of corrupt activities (TI 2005; Krishnan 2010). A report

issued by the Organization for Economic Co-operation and Development (OECD) (2014) revealed that

corruption had been deemed as one of the primary barriers to sustainable socio-economic and political

development in developed, developing, and emerging economies alike. In all, corruption increases

2
This chapter is fully or partially published in the following journal article: Chan, A. P., & Owusu, E. K.
(2017). Corruption forms in the construction industry: Literature review. Journal of Construction Engineering
and Management, 143(8), 04017057.

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 Chapter 3 - Contemporary Review of Corruption

inequality, reduces efficiency, and is estimated to account for over $2.6 trillion annually, which is

approximated to be 5% of the global gross domestic product (GDP) with over $1 trillion expended in

bribes annually. Bribery has been revealed to be the most mentioned form of corruption in the industry

as it is discussed later in this section. Most recognized anti-corruption frameworks are designed to deal

with bribery cases. One typical example recently developed is the ISO 37001 anti-bribery management

systems by the International Organization for Standardization (ISO) (2016). Noonan (1984) opined that

the first case of corruption ever recorded was in the form of bribery, which occurred around 3000 BC.

Bribery has therefore been regarded as the primary form of corruption that exists to date. However,

because of the evolution of corruption over the years, different forms of corrupt practices have emerged,

and more money is being expended in these newly generated forms.

The continual research on corruption over the last two decades has revealed varying forms of corruption

in the studies available, but there is no literature to date that presents a comprehensive review of the

forms of corruption prevalent in the context of the construction, engineering, and the procurement

sectors. Therefore, this section aims to fill the gap by presenting a comprehensive review of the various

forms of corruption present in the mentioned sectors. The objectives of this section are to identify the

forms available and present a conceptual framework for easy identification of the identified forms.

Grasping an in-depth understanding of the various forms of corruption is very crucial to the

development of anti-corruption measures (Bowen et al. 2012; Søreide 2002; Tanzi 1998; Le et al. 2014;

Shan et al. 2016).

Therefore, this section provides vital information to industry practitioners, policymakers, and anti-

corruption institutions in various ways, such as the formulation of anti-corruption measures and easy

detection or identification of corrupt practices. To the academic and industry researchers, this section

offers them the basis of delving into deeper research works with regards to forms of corruption. With

the identification of new forms of corruption, innovative frameworks can be formulated in a more

specific manner to tackle corruption from all angles, thereby leading to the reduction of these practices

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 Chapter 3 - Contemporary Review of Corruption

in the short term and hopefully eradicating their existence in the long-term run. The aim and the

objectives of this section are discussed the subsequent sub-sections.

3.2.1 Findings from Studies on the Analysis of Corruption Forms

An appreciable number of publications have identified and explicated different forms of corrupt

activities that take place in the construction sector, although comparatively small regarding total

identified publications retrieved for this review. An unstructured review of different publications was

also conducted randomly to find out if there were other forms of corruption peculiar to construction that

was not identified in the selected publications for this review. It was discovered that all the identified

forms in Table 3.1 constituted the forms identified in other publications, thereby justifying the

suitability of the selected papers for this section of the review. Conversely, forms of corruption that did

not have a direct correlation with the construction industry were discovered; for example, the

identification of plagiarism in the education sector. This notwithstanding and based on the comparative

study of the identified forms in Table 3.1 and the randomly selected publications, the forms of

corruption in construction identified in this study are considered comprehensive because they captured

all the forms of corruption captured in the random papers.

At the end of this section’s review, 39 publications were identified to explicate the forms that do occur

as corrupt practices in the construction industry. Also, from these 39 publications, a total of 28 different

forms of corruption in the construction industry were captured. As presented in Table 3.1, the numbers

1–39 represent the papers retrieved for the review and the markings with the symbol (x) represent the

frequency of an identified form among the publications. For example, publication number 8 is a paper

authored by Tsai, J. S., and Chi, C. S. In this paper, the authors captured two forms of corrupt practices;

similarly, bribery as a form of corruption was identified by 27 different publications as shown in Table

3.1. Also, from Table 3.1, the evolution of corruption over the years has led to the emergence of many

other forms in the industry. The most identified CFs in the selected papers included bribery, collusion,

fraud, collusion, embezzlement, nepotism, and extortion. All the forms are briefly described to provide

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 Chapter 3 - Contemporary Review of Corruption

some information to stakeholders and industry practitioners. After the identification of the CFs, it was

realized that some of the forms were identical based on the definitions and classifications done in other

studies. A conceptual framework of CFs categories was then developed with the aim of providing easy

identification of CFs and clear direction in the application of anti-corruption measures (ACM).

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 Chapter 3 - Contemporary Review of Corruption
Table 3.1: Corruption Forms (CF) Identified in the Literature
Form Publication
1 2 3 4 5 6 7 8 9 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 Total
0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9
Bribery x x x x x x x x x x x x x x x x x x x x x x x x x x x 27
Fraud (Falsification) x x x x x x x x x x x x x x x x x x x x 20
Collusion x x x x x x x x x x x x x x x x x x x 19
Embezzlement x x x x x x x x x 9
Nepotism x x x x x x x 7
Extortion x x x x x x x 7
Conflict of interest x x x x x x x 7
Big rigging x x x x x x x 7
Kickbacks x x x x x x 6
Professional negligence x x x x x 5
Front/ shell companies x x x x x 5
Favoritism/ Cronyism x x x x 4
Dishonesty x x x x 4
Facilitation payments x x x 3
Price fixing x x x 3
Guanxi x x x 3
Patronage x x x 3
Client abuse/ clientelism x x 2
Ghosting x x 2
Influence peddling x x 2
Money laundering x x 2
Lobbying x 1
Intimidations and threats x 1
Coercion x 1
Cartels x 1
Blackmail x 1
Solicitation x 1
Deception x 1

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 Chapter 3 - Contemporary Review of Corruption

3.2.2 Categorization of the Corruption Forms

As presented in Table 3.1, the review conducted revealed the prevalence of several forms of corruption

that exist in the construction industry. However, to better understand these forms, it is expedient to

categorize them into constructs to set out the differences that exist among them. The classification was

done purely on two premises: (1) the relationship and the commonalities that exist among the variables

(by definition), and (2) from previous studies that classified some of the variables. For instance,

Powpaka (2002) classified kickbacks as a form of bribery act in his studies. Similar classifications by

other studies were followed to develop the framework as presented in Fig. 3.1. The discussion section

reveals other examples of the classification. Fig. 3.1 presents a conceptual framework of the

classification of CFs into identical constructs based on their definitions.

3.2.3 Corruption Forms Constructs

The constructs are bribery acts, fraudulent acts, collusive acts, extortionary acts, discriminatory acts,

and unclassified acts. The bribery acts construct like other constructs were framed based on the

commonalities of the variables with regards to their definition and also based on the classifications of

other previous works. Because of word and space limitations, all the forms are briefly discussed within

their primary constructs.

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 Chapter 3 - Contemporary Review of Corruption

• Fraud • Bribery
• Deception • Solicitation
• Ghosting
Bribery Acts • Lobbying
• Front/ shell
• Facilitation payments
companies
• Kickbacks
• Dishonesty
• Influence Peddling
• Money laundering
• Collusion

Extortionary
Fraudulent Acts • Client abuse/
Acts clientelism
Corruption Forms • Intimidations and
threats
Collusive Acts • Coercion
• Blackmail
Unclassified

Discriminatory
• Cartels
Acts
• Bid rigging
• Price Fixing

• Favouritism
• Patronage
• Professional
• Guanxi
negligence
• Nepotism
• Conflict of interest
• Embezzlement

Figure 3.1: Conceptual Framework for CFs classification

3.2.4.1 Bribery Acts

Based on the relationship s that exist among the variables within the construct, bribery acts consist of

bribery, kickbacks, facilitation payments, influence peddling, lobbying, and solicitation. These are

briefly discussed as follows. Bribery refers to a corrupt act that may involve giving, promising,

soliciting, accepting, or offering a benefit to lure or entice someone to act in an unethical or illegal

manner. Enticements can be in the form of rewards, fees, loans, gifts, or any supplementary advantage

such as donations, special treatment, or services. Any act of this form in the construction industry or

procurement is deemed bribery (Le et al. 2014; Meduri and Annamalai 2013; Wang et al. 2000;

Loosemore and Lim 2016; Zhi 1995). As mentioned by Noonan (1984), bribery acts constitute the first-

ever corruption case. Although there have been countless mention and identification of this form in the

industry, according to this review, the first mention of a bribery case was recorded in construction

projects was by Stuckenbruck and Zomorrodian (1987). Bribery was identified by 27 out of 39 different

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publications constituting over 70% of the entire publications reviewed. Therefore, this ranks bribery as

the topmost recorded form of corruption in the industry. The next mentioned bribery act is a kickback.

Per the study of Sohail and Cavill 2008; Adams 1997; Brown and Loosemore 2015, kickback may refer

to an illegal act where a secret payment is demanded by an individual in a coercive position from another

party in search of an advantageous or a biased decision. Kickbacks, per Powpaka (2002), are effectively

described as bribes, although it can also be regarded as extortion. Kickbacks were identified by 6 out of

39 publications. Solicitation is the act of enticing, ordering, influencing, or asking another party to

indulge in the act of bribery or other corrupt behaviors (TI 2016). A typical example of this form is

shown in the thematic responses by the respondents involved in a study by Bowen et al. (2012).

However, the form is not mentioned in their study. Facilitation payments are regarded as small bribes

that can also be termed as grease or speed payments normally made to speed up or secure an action to

which the briber already has authorized or other rights to (Liu et al. 2004; Kenny 2012; TI 2016). This

form of corruption is not new to the industry. However, only three studies identified facilitation

payments as a CF in the industry. Lobbying refers to any corrupt act that is undertaken to influence the

decisions and policies of an institution to favor an outcome or a course. These acts may turn out to be

very misleading if there are inconsistencies in the existence of different stages of influence by

individuals, organizations, associations, or different institutions (TI 2016). Influence peddling is

described as the use of one ’s status or influence on behalf of another person for a special advantage in

return for financial favors or other benefits. For instance, during a contract award stage of a project, if

a senior procurement officer manipulates the process by using his power to unfairly influence the

decision to favor a contractor in return for a percentage of the contract sum, the act is termed as influence

peddling and the official involved is known as the peddler. The actor is often regarded as an influence

peddler (Bowen et al. 2012; Stansbury 2009).

3.2.4.2 Fraudulent Acts

Fraudulent acts in the construction industry consist of fraud, collusion, front/shell companies,

dishonesty, ghosting, money laundering, and deception. However, under collusive acts that are

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classified as fraudulent acts, the variables consist of bid-rigging, price-fixing, and cartels. These are

briefly described as follows. Fraud simply refers to the act of deception with the intention to cheat. This

takes place when a party deceives another person with the aim of gaining an illegal or unfair advantage

(contract award, financial, political). Some countries consider this offense as a felonious act or violating

civil laws (Le et al. 2014; Meduri and Annamalai 2013; Wang et al. 2000; Tsai and Chi 2009) Ghosting

refers to an entity (either an individual or a unit) made-up for the purposes of fraudulent act or deception

(Bowen et al. 2012; Brown and Loosemore 2015). Front/shell companies refer limited liability

companies or corporations that have no corporeal existence regarding jurisdiction, no commercial

activities, nor are they made up of any real employees.

They are typically established within secrecy or tax haven jurisdiction with the primary purpose of

shielding the actual beneficial proprietor from either disclosures or taxes or both (Bowen et al. 2012;

Brown and Loosemore 2015; TI 2016). Dishonesty can be described as an act of lying, stealing, or

cheating with the primary aim of acquiring, converting, or disposing of either tangible or intangible

property to obtain an upper hand or a benefit. It can be defined as fraud in criminal law and can include

either pretense or act deceitfully to obtain a benefit. Deception refers to the act of presenting wrongful

information to mislead another person concerning a situation that in itself is true (Stansbury 2009).

Collusion is regarded as an undisclosed arrangement that exists among the parties involved, either in

the private or public sector or both, who meet to conspire to commit deceitful or fraudulent acts to gain

illegitimate rewards such as financial gains. The participants who normally engage in collusive acts are

known as cartels (Dorée 2004; Shan et al. 2016). Money laundering refers to the act of concealing the

ownership, source, or the end point of money obtained in an unlawful of a dishonest manner and secretly

placing it in legitimate ventures or projects to make them look lawful (Stansbury 2009; TI 2016).

3.2.4.3 Collusive Acts

Under the collusive acts construct, the factors identified were cartels, bid-rigging, and price-fixing. A

cartel, also regarded as a form of collusive act and similar to bid rigging, transpires when two or more

firms arrange or enter into an agreement to limit the flow of materials or fix the prices of goods they

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control in a specific industry (Stansbury 2009). Bid rigging refers to a collusive act where consenting

participants settle on the results of a bid process beforehand. For instance, in some cases, a bidder

specifies a very limited time for the preparation of tender documents with the sole aim of controlling

the number of prospective bidders. Therefore, only those who were given prior notice of the upcoming

bid stand the chance of submitting adequate tender documents (Dorée 2004; Bowen et al. 2012; Brown

and Loosemore 2015; Sichombo et al. 2009). Price fixing is a collusive act analogous to big rigging.

With this act, a sect of competitors or tenderers colludes to either manipulate or fix prices rather than

observe an open market competition (Tabish and Jha 2011a).

3.2.4.4 Discriminatory Acts

Discriminatory acts simply depict the actions of showing more concern or favors that are ethically and

professionally wrong. They include nepotism, favoritism, patronage, and guanxi. Favoritism refers to

the act of offering special treatment to either an individual or a group of persons, and it often takes the

form of awarding a contract, honoring, hiring, benefits, among others, even though the person may not

necessarily be qualified for the position or the contract offered. It is regarded as a comprehensive term

because it manifests itself in the form of cronyism, nepotism, and patronage (Wang et al. 2000; Ling

and Tran 2012; Wibowo and Wilhelm 2014). Nepotism refers to an act where an individual in a position

grants favor to either a relative or a friend without suitable regard to qualification (Willar et al. 2016;

Corvellec and Macheridis 2010). Patronage is regarded as a form of favoritism where an individual is

offered a job, award contract, or other benefits regardless of their entitlement or qualifications and it is

normally due to either the individual ’s connections or affiliations (Waara and Bröchner 2006; Brown

and Loosemore 2015; TI 2016). Guanxi is a Chinese term for nepotism, although not all guanxi may be

termed unlawful. In some cases, it turns to favor the parties that have good connections in a local

domain, but it becomes unlawful when the favor is granted to a party or group of persons not deserving

the favor (Weisheng et al. 2013; Ke et al. 2011; Xu et al. 2005).

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3.2.4.5 Extortionary Acts

Extortionary acts are forceful acts that induce fear in the victim intending to make the victim act against

his will or to benefit the oppressor, who is mostly of a higher status. They include extortion, client

abuse/clientelism, intimidations and threats, coercion, and blackmail. Brief descriptions are given as

follows. Extortion refers to the direct or indirect act of using one ’s power, knowledge, or status to

coercively threaten others in the form of demanding unmerited benefits, compensations, or benefits

(Transparency International 2018). Intimidations and threats are regarded as a form of extortion where

an individual intentionally induces a sense of subjection, inferiority, or fear into another person or group

of persons to frighten them into making them do what the intimidator wants. Blackmail can be described

as a condition or act when a party threatens another party if the latter party does not render some

privileges or advantages demanded by the former party and the threats are usually in the form of

punishment or a mean act as observed in the act of coercion. This was revealed by Smith (2009), but it

is rarely mentioned in the industry. Coercion is regarded as a direct or indirect act of committing harm,

prejudice, or threats to negatively influence the actions of another person often to favor the coercer

(Sichombo et al. 2009). Client abuse/clientelism refers to a biased arrangement of exchanging goods,

favors, or resources on a manipulative affiliation between a powerful party and a punier client (Zhang

et al. 2016; TI 2016).

3.2.4.6 Unclassified Acts

This construct is named unclassified because no literature classified them. Although there is a

commonality among the three variables of a negative professional attitude, no literature has classified

them, and hence they are left unclassified. They include embezzlement, conflict of interest, and

professional negligence and are briefly discussed as follows. Embezzlement refers to an act where an

individual misappropriates, traffics, or uses either goods or funds of an organization or an institution

entrusted in their care for personal benefits. For example, when a contractor diverts construction

materials allocated for execution of a project, the contractor is said to have embezzled the client’s goods

because the client is most often the financier of the project (Sohail and Cavill 2008; Tsai and Chi 2009;

Bowen et al. 2012). Conflict of interest in the construction industry refers to the situation where a

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professional of the industry is challenged with a choice of deciding between the demands and duties

required by profession and their respective personal interests (Ho 2013; Bowen et al. 2012).

Professional negligence was insinuated as corrupt conduct in the construction industry that occurs when

professionals fail to provide the duty of care that a reasonably careful, and prudent professional would

offer given the same conditions. For example, some recorded negligence acts include inadequate

supervision, deficit in material quality, or insufficient requirements regarding safety (Ho 2011, 2013).

3.3 Causal Factors of Corruption3

Corruption is known for breeding cynicism, dents societal values, demeans those involved, hinders

decision-making and degrades the quality of projects. Hence it reduces the lifespan of buildings,

depriving most inhabitants of quality living. Most importantly, it results in the loss of human lives and

properties among other devastating and damaging effects (Lewis, 2003; Transparency International

2005; Boyd and Padilla, 2009). It is therefore deemed to be very deadly, even more, deadly than a

disease and it is necessary that all participants of the industry including professionals, clients, and the

government except for the corrupt, concur on a cooperative effort to tackle this issue and should not be

viewed as a competitive issue (Boyd and Padilla, 2009). Researchers and anti-corruption institutions

have played active roles in examining some of these negative drivers, which are referred to as the causes

of corruption according to this section. The incessant devotion to corruption research in the construction

industry over the years has, therefore, revealed several causal factors that contribute to the incidences

of corruption. However, little efforts have been made to systematically review all the causes of

corruption in the construction industry and IP, even though they are vastly identified in different studies

and contexts. This section, therefore, aims to fill the gap and add on to the existing body of literature

by presenting a thorough review of the causal factors of corruption in the construction industry, which

is vital and needed for further research.

3
This chapter is fully or partially published in the following journal article:Owusu, E. K., Chan, A. P., & Shan,
M. (2017). Causal factors of corruption in construction project management: An overview. Science and
engineering ethics, 25(1), 1-31.

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 Chapter 3 - Contemporary Review of Corruption

The main aim of this section is to review the body of literature dedicated to the causes of corruption in

the construction industry regarding the existing causal factors of corruption, the annual trend of

publications, and the thematic categorization of the variables. However, in the quest to realize the set

aim, 34 carefully identified publications were consulted as highlighted in the preceding section, and 44

distinct causes of corruption were identified. After the identification of the variables, the authors

recognized the similarities and the identical relationships among some of the variables. This led to the

categorization of the variables under five newly developed constructs forming the basis for the

conceptual framework for the causes of corruption in the construction industry. The succeeding sections

explicate the annual trend and the constructs into details.

3.3.1 Findings of Corruption Causal Factors

Following a comprehensive review of selected 34 publications, all the identified causal factors of

corruption are presented in Table 3.3. In short, 44 distinct factors were identified as causal factors of

corruption in the construction industry. The references for the identified factors are presented in the

third row of Table 3.3, and full details for the references are captured in Appendix A. The relationship

considered between the second column from the left representing the causes of corruption and the third

column labeled publications is the frequency or the number of publications that cited a particular causal

factor. For instance, the lack of rigorous supervision identified as the six factors were identified by five

different publications (2,7,17,18 and 24). This same was done for each factor to highlight the number

of factors from the resulting publication. After the identification of the variables, they were categorized

into five constructs, namely Psychosocial-Specific Causes, Organizational-Specific Causes,

Regulation-Specific Causes, Project-Specific Causes, and Statutory-Specific Causes, which are

discussed in the next section.

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Table 3.2: Causal factors of corruption in construction

No Causal Factors of Corruption Publications
1 Poor professional ethical standard [2]; [16]; [17]; [19]; [20]; [21]; [24]; [25]; [26]; [27]; [30]; [34]
2 Over close relationships [1]; [2]; [5]; [6]; [7]; [8]; [9]; [15]; [18]; [25]; [26]; [31]
3 Negative industrial and working conditions [2]; [7]; [12]; [16]; [17]; [30]; [33]
4 Negative role models [2]; [7]; [12]; [18]; [25]; [32]
5 Personal greed [11]; [12]; [16]; [17]; [24]
6 Lack of rigorous supervision [2]; [7]; [17]; [18]; [24]
7 Inadequate sanctions [2]; [7]; [12]; [18]; [33]
8 Flawed regulation system [2]; [12]; [16]; [17]
9 Deficiencies in rules and laws [2]; [3]; [14]; [18]
10 The nature of infrastructure projects [18]; [32]; [34]
11 Over competition in tendering process [11]; [16]; [24]
12 Low wage level [2]; [18]; [29]
13 Great project complexity [2]; [32]; [34]
14 Multifarious licenses or permits [2]; [7]; [18]
15 Lack of pro-active steps by funders to limit corruption on projects [18]; [33]
16 Absence of efficient and responsible administrative systems [10]; [28]
17 Government influence [10]; [34]
18 Insufficient legal punishments and penalties [14]; [33]
19 Fierce competition [16]; [17]
20 Weak procurement / contractual structures [12]; [16]
21 Absence of control mechanism [12]; [33]
22 Transition of governments or economies [22]; [28]
23 The nature of corruption being a secret activity [16]; [34]

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24 Complex contractual structure [18]; [34]

25 Appointment of a local representative who acts on behalf of the firm to obtain contracts [29]; [34]
26 Economic Survival [16]; [34]
27 Inappropriate political interference [2]; [11]
28 Delaying the payment of workers’ salaries [22]
29 Lack of legal awareness [4]
30 Lack of coordination among Government departments [4]
31 Poor documentation of records [4]
32 Insufficient transparency in the selection criteria for tenderers [11]
33 Complexities of institutional roles and functions [11]
34 Asymmetric information amongst project parties [11]
35 Lack of standardized execution in construction projects [13]
36 Negative encouragement [16]
37 The influence of guanxi [16]
38 Absence of project anti-corruption systems [18]
39 Subjecting workers to job insecurity [22]
40 A feeble semblance of public interest [23]
41 Misrepresentation of qualification certificates [24]
42 Monopoly [25]
43 Lack of frequency of projects [34]
44 Deregulation in the public construction [2]
1=Dorée (2004); 2=Le et al. (2014); 3=Zhang (2005); 4= Iyer & Sagheer (2009); 5= Ling and Tran. (2012), 6= Yow et al. (2004); 7=Brown & Loosemore (2015);
8= Ning (2014); 9= Ling et al. (2014); 10= Stuckenbruck & Zomorrodian (1987); 11= Sohail & Cavill (2008); 12= Bowen et al. (2012); 13= Tabish & Jha (2011);
14= Bologna & Nord (2000);15= Chan et al.(2003);16= Zhang et al.(2016);17= Le et al.(2014);18= Tanzi (1998);19= Liu et al.(2004);20= Moodley et
al.(2008);21= Zarkada-Fraser & Skitmore (2000);22= Alutu (2007);23= Porter (1993);24= Shan et al.(2016);25= Damit (1983);26= King et al.(2008);27= Fan &
Fox (2009);28= Shan et al.(2015);29= Boyd & Padilla(2009);30= Hartley (2009);31= De Jong et al.(2009);32= Krishnan (2009);33= Stansbury (2009);34=
Locatelli et al. (2016)

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3.3.2 Categorization of Variables

Following the studies of Zhang et al. (2017); Le et al. (2014); Tabish and Jha (2011) and Zou (2006),

and with the help of thematic analysis approach, the 44 variables causes of corruption identified from

the review were categorized into five primary constructs. Le et al. (2014) identified ten causes of

corruption in the Chinese public construction sector and categorized them into two main constructs,

namely flawed regulation system and lack of positive industrial climate. Similarly, Zhang et al. (2017)

also identified 24 causes of corruption in the Chinese tendering process and classified them into six

unique construction. Other studies as well have developed similar constructs, which are mostly

regulation-specific causes, industrial-specific causes, project-specific causes, etc.

This section followed the same approach to construct categorization. However, since the review process

included a vast range of CM publications, a high number of variables (44 in number) were identified,

and the thematic analysis approach was employed to factorize the newly identified variables. A

thorough reading on each of the variables was made to draw out their main themes to aid in the

categorization process. At the end of the process, the five different constructs that were developed are

Project-Specific Causes, Regulation or Legal-Specific Causes, Statutory-Specific Causes,

Organizational-Specific Causes, and Psychosocial-Specific Causes. These constructs serve as the

extension of the body of knowledge devoted to corruption research in the construction industry. After

the formulation of the constructs, a conceptual framework (Fig. 3.3) of the causes of corruption in the

sector was developed. This framework enlisted all the five newly formulated constructs.

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Figure 3.2 Conceptual Framework for causes of corruption

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Fig. 3.3 represents the framework developed for the identified variables within their respective

constructs. They include Project-Specific Causes, Regulatory-Specific Causes, Statutory-Specific

Causes, Organizational-Specific Causes, and Psychosocial-Specific Causes. It should be noted that the

generated constructs are not independent of each other since they can all directly or indirectly affect the

construction processes and projects. For instance, regulation specific matters can apply to projects as

well, although, from the categorization, there could be an assumption that project-specific causes are

only related to construction projects. Explanations to each one of the constructs are discussed in the

succeeding section. The intensity of their occurrences based on the number of times mentioned in the

literature is determined using the mean score approach.

3.3.2.1 Psychosocial-Specific Causes (PSSC)

PSSC construct was developed out of the thematic analysis approach. It represents the psychological

and relational or social causes of corruption in the CM. Psychosocial relates to the interconnections of

social factors such as relationships and psychological attributes and their influence on the environment,

in the workplace or the process of work execution, etc. (Heiser, 2001; Greitzer, 2013; Merriam-Webster,

2017). Also, per the definition and its theoretical underpinning, a total of 7 causal factors were classified

under this construct. As compared to the other constructs, PSSC was ranked the first construct with a

mean score of 5.43 per the frequency of the individual factor citations recorded in this review and was

also rated the second construct with the least variables of seven. However, the top three variables under

this construct were revealed to have very high scores as compared to the other causal factors.

Moreover, the mean score obtained by the PSSC construct demonstrates that the psychological issue or

causal factors of corruption in the CPM are very critical and require psychological or ethical

interventions since these causal factors are human-oriented. Examples of PSSC include poor

professional, ethical standard, over close relationships, negative role models, personal greed and

negative encouragement (Moodley et al. 2008; Shan et al., 2016; Dorée 2004; Le et al., 2014; Brown

and Loosemore, 2015; Bowen et al., 2012; Tanzi, 1998). Other PSSC variables include weak impression

of public interest or what may be termed as the lack of public interest in corruption issues and the

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influence of guanxi, which is a Chinese word for nepotism or favoritism (Sohail and Cavill, 2008;

Bowen et al., 2012; Zhang et al., 2016).

Poor professional, ethical standard, negative role models, and Negative encouragement are all inherent

psychological issues that directly or indirectly affect not only junior staff within the industry or working

environment but other senior professionals as well. Setting an example as a corrupt leader can create a

league of corrupt followers, and the cycle continues until most, if not all, the professional becomes

corrupt. It is sometimes hard to bring to check a senior professional who has tasted the benefits of

corruption since early beginnings as junior staff. Setting a negative standard as a role model as well as

offering negative encouragement, in the authors’ opinion, can be termed as the mother of all forms of

corruption. The statement is based on the postulation that all forms of corruption have to commence

with parties with negative intentions to engage in corruption (Henry, 2009), and the topic of corruption

is as well skewed towards the concept of negative human ethics. Although this argument may be

arguable, it is psychologically indicated that positive leadership or role models, as well as positive

encouragement, are likely to create a positive working atmosphere (Bass, 1985; Jung and Sosik, 2002).

Also, Personal greed, which is another psychological issue of human ethics, refers to the extreme selfish

desire of a person to acquire wealth, which is often presented in the form of money or other valuable

resources (Dhiman, 2008). And the desire to want more causes professionals to engage in corruption

(Sohail and Cavill, 2008; Bowen et al., 2012). On the side of relational instigators, overclose

relationships have contributed immensely to the evolution of varying forms of corrupt or discriminatory

acts in the CPM such as favoritism, nepotism, cronyism and patronage and guanxi as described in the

Chinese context (Wang et al., 2000; Ling and Tran, 2012; Wibowo and Wilhelm, 2014; Weisheng et

al., 2013; Ke et al., 2011; Xu et al., 2005). The variables within this construct have also led to the

eruption of other forms of corruption identified in tendering processes such as collusion acts which may

include cartels, bid-rigging and price-fixing (Dorée, 2004; Bowen et al., 2012; Brown and Loosemore,

2015; Sichombo, 2009; Stansbury, 2009). Moreover, deep research is needed, especially in the area of

corruption in the CM, to ascertain practical measures on how to effectively deal with the high rate of

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overclose relationships in the industry. Lastly, in a general setting or public domain, where there is a

feeble semblance of public interest, or a large percentage of the population fails to report corrupt

practices of any form, there is a high possibility of corruption to flourish in that particular environment.

3.3.2.2 Organizational-Specific Causes (OSC)

OSC are causal factors that emanate from organizational structures or institutions. In other words, they

are corrupt institutional influences from both the public and private construction sectors that negatively

affect the entire industry and create room for corruption to occur. They include negative industrial and

working conditions, over competition in the tendering process which encourages some contractors or

construction firms to engage in corruption to be awarded the contract (Brown and Loosemore, 2015;

Bowen et al., 2012; Zhang et al., 2016; Hartley, 2009). Others, which include inadequate sanctions, low

wage level, economic survival of institutions and the absence of efficient and responsible administrative

systems, among others are briefly discussed in the succeeding section (Le et al., 2014; Brown and

Loosemore, 2015; Bowen et al., 2012; Tanzi, 1998; Stansbury, 2009; Sohail and Cavill, 2008).

OSC construct is ranked second highest among the constructs with a mean score of 2.64, and the

construct is as well made up of 11 out of 44 variables, just as observed in the case of PSC construct,

making it also one of the leading constructs with most variables. Therefore, as encountered in the

situation of the causal factors associated with project initiation, execution, and completion,

organizational causal factors also tend to have adverse effects on the commencement and completion

of a project. For instance, bidders representing their various construction institutions may be pushed to

ask for a favor from the contract awarding body due to the excessive numbers of bidders who have all

tendered in for a project (Zhang et al., 2016; Shan et al., 2016). This, in turn, places the contract-

awarding body in a position to accept bribery from capable contractors and at the end, rigs the entire

bidding process. This variable, over competition in the tendering process, is also regarded as one of the

leading causes of bid-rigging in the infrastructure procurement process (Le et al., 2014; Stansbury,

2009).

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The struggle for economic survival also forces some construction and consulting firms to engage in

corruption (Zhang et al., 2016; Locatelli et al., 2016). Resorting to corruption in situations like this can

sometimes remain the only or last option for some industries to survive and stay competitive in declining

economies. Such firms would do whatever possible to keep them surviving rather than to get out of

business. Also, when there is fierce competition in the construction market or over competition in the

tendering process, unethical professionals from both the contracting or bidding firms and contract

awarding body may manipulate or rig the entire process to favor the ‘briber' (Sohail and Cavill, 2008;

Le et al., 2014; Shan et al., 2016). This action from the two corrupt parties or institutions most often

succeeds because of the nature of corruption is a secret activity (Zhang et al., 2016). In the instance of

Negative industrial and working conditions such as low wage level, underpaid staff may also

supplement their remuneration earnings with petty facilitation payments and see either very little or no

need to refrain from such acts. Also, when they realize that their leaders are misappropriating monies

or resources that could have been used to increase their wages or better their living conditions, they tend

to help themselves out through corruption (Tanzi, 1998; Boyd and Padilla, 2009).

Moreover, delaying the payment of workers’ salaries can result in the same condition described above

(Alutu, 2007). Poor documentation of records and the complexity of institutional roles and functions

are other problematic subjects encountered in other organizations that create the vacuum for corruption

to thrive (Iyer and Sagheer, 2009). On the issue of the absence of efficient and responsible

administrative systems and Inadequate sanctions as OSC variables, Bowen et al. (2012) revealed that

without effective policing strategies and adequate sanctions to check corruption in awarding

government contracts, the whole process is can be rigged. The authors opined that these were some of

the cases recorded in South Africa (SA) construction industry. The absence of political will to combat

the incidence of corrupt practices in SA poses the difficulty in imposing discipline or adequate sanctions

to corrupt parties in the SA construction sector. This, therefore, creates more room for the frequent

occurrence of corrupt practices since those involved are occupied with the notion that they will go

unpunished even when caught in the act (Krishnan, 2009; Bowen et al., 2012; Stansbury, 2009).

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3.3.2.3 Regulatory or Legal-Specific Causes (RSC)

The RSC construct consists of causal factors that are skewed towards regulations, norms, or principles

guiding modus operandi and the activities of the CPM or, to an extent, legal matters associated with the

CPM. The composing variables of this construct are very critical in every project management in

construction since every project and activity within the industry is guided by contracts, regulations,

principles, bonds, and others. Per the assessment of this review, the RSC construct is ranked 3rd with a

mean score of 2.22 with nine causal variables. The leading variables within RSC are flawed regulation

system (FRS) of most construction public sectors, (Le et al., 2014; Bowen et al., 2012; Zhang et al.,

2016), deficiencies in rules and laws and multifarious licenses or permits (Zhang, 2005; Bologna and

Nord, 2000; Tanzi, 1998). FRS was identified by Le et al. (2014) as one of the leading causes of

corruption, the Chinese construction public sector. In any setting, whether the private sector or public

or even in the execution of a project, when the entire regulatory system intended to guide the effective

implementation of activities is flawed, there is a possibility for corruption to happen.

The departments within the public construction sector as well that of the private are expected to ensure

a sound set of regulations or principles governing every single activity and behaviors of professionals

are in place and active. Prominent causes the RSC Include insufficient legal punishments and penalties,

weak procurement / contractual structures, the absence of effective control mechanism, lack of legal

awareness on the part of professional or construction workers, the lack of project anti-corruption

systems and deregulation in the public construction (Le et al., 2014; Brown and Loosemore, 2015;

Tanzi, 1998). Right from the conception of a project to its realization, the identified RSC variables may

lead to adverse consequences that can either halt the execution of a project or terminate it entirely.

Compromising on any of the set laws or regulations guiding the industry or project execution may lead

to adverse consequences in the industry, and it is necessary that industry practitioners and project

executioners conform to laws, principles, and regulations guiding a project. Conforming to rules and

regulations is very critical, not only in the CM but other sectors as well and, most importantly in the

public sectors (Brown and Loosemore, 2015; Bologna and Nord, 2000).

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3.3.2.4 Project-Specific Causes (PSC)

PSC refers to the causal factors or instigators that lead to corrupt activities in a construction project.

Although the list within this construct may apply to other situations as well, attributed explicitly to

construction projects, in other words, without construction projects, some of the causes within the PSC

construct would not be in existence. Transparency International (2005) identifies two forms of

construction projects, namely minor and major projects, as well as two primary types of corruption,

namely petty and grand corruption, and argue out that. In contrast, minor projects are susceptible to

petty corruption; large projects or contracts are liable to grand corruption. The principal variables noted

under this construct include Lack of rigorous supervision during project execution, great project or

infrastructure complexity as well as the complex contractual structure involved in projects (Le et al.,

2014; Brown and Loosemore, 2015; Tanzi, 1998; Shan et al., 2016).

Other notable variables include the lack of pro-active steps by funders to limit corruption on projects

and also the lack of standardized execution in construction projects (Krishnan, 2009; Locatelli et al.,

2016; Krishnan, 2009; Locatelli et al., 2016). In all, 12 causal factors were classified under the PSC

construct. As indicated in the previous section, other variables under the four other constructs may

directly or indirectly affect a construction project, although the PSC construct is specifically made up

of related variables. Per the review, PSC construct is ranked 4th with a mean score of 1.83, due to the

low-frequency rate of the citations of its variables in the retrieved papers, it is regarded as a highly

important construct because it recorded the highest number of 11 out of 44 variables, same with the

OSC construct. This depicts how the nature of construction projects tend to record a high number of

corruption cases. According to the review, the lack of rigorous supervision during project execution

happens to be the leading variable under this construct. This variable has been regarded not only as a

causal factor of corruption in project works but also threat to timely execution of projects, increases the

overall intended cost, and affects the quality of projects, which represents (the three main objectives of

any construction project). Failing to ensure adequate and rigorous supervision of construction projects

from the side of the client’s representatives tends to create a loose end for the contractor or suppliers to

make use of inferior materials or misappropriate the quality materials provided by the client (Brown

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and Loosemore, 2015; Tanzi, 1998; Shan et al., 2016). The situation, in either the short or long term,

could lead to early deterioration of the projects and reduce the lifespan as well (Le et al., 2014).

The following three, which include Great project complexity, Complex contractual structure, and the

nature of infrastructure projects are all complications that evolve as a result of the inability of some of

the key members of a construction project to appreciate the whole nature of both projects and contracts.

This inability, therefore, creates a space for corruption to flourish. Whereas simple projects tend to yield

fewer complications and difficulties with regards to the project itself and its associated contracts,

complex projects and contracts do not only need to make use of professional experts who understand

the nitty-gritty of the entire project, but must also involve other skilled professionals outside the project

team such as professional audit team that understand the project and contracts. Therefore, awarding

contracts for bidders who find it tough to appreciate the nature of the project, as well as the contract and

the requirements involved, could be a possible cause of corruption. This is just one out of the many

examples of how the complexities of projects and contracts may lead to corruption in either a

construction process or other industrial activities in general.

3.3.2.5 Statutory-Specific Causes (SSC)

SSC construct is attributed to the government or state-driven factors that propel corrupt practices in the

public construction sector. The definition of corruption lends itself to public ventures as compared to

that of the private sector (Chan and Owusu, 2017). The public officers are often reported to be the

perpetrators of any possible corrupt incident in the construction industry Tabish and Jha (2011). The

noted causal variables under the SCC construct include inappropriate political interference and

government influence in the award of contracts. Other factors include the appointment of a local

representative who acts on behalf of the firm to obtain contracts, the transition of governments or

economies, lack of coordination among Government departments and subjecting workers to job

insecurity, especially in government and public enterprises (Le et al., 2014; Sohail and Cavill, 2008;

Boyd and Padilla, 2009; Stuckenbruck and Zomorrodian, 1987; Locatelli et al., 2016). The SSC factor

was identified to be the least rated construct in terms the frequency of citation and the least number of

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individual constituting variables, with a mean score of 1.67. However, the variables within this construct

were also identified to be very critical in the developing countries and may even represent the leading

causal initiators of corruption in the public construction sectors of some developing countries (Osei-

Tutu et al., 2010; Tabish and Jha, 2011).

The influence of Government in contract award can either be regarded as a positive act or a corrupt act.

In the stance of the positive view, government representatives may choose to award a contract to a

contractor or supplier firm due to their long stand reputation in executing quality projects. On the other

hand, government representatives may choose to award a contract to a firm based on either political

affiliation or any relationship, which depict a typical example form of corruption such as favoritism,

nepotism or cronyism. This, to an extent, can be likened to inappropriate political interference (Sohail

& Cavill, 2008). Also, the transition of governments or economies does not only creates enough room

for corrupt practices to occur but also serves as a common leading cause of project abandonment in the

developing world. An outgoing government may choose to abandon ongoing projects and embezzle

public funds in economies that do not have adequate systems to detect such practices. Osei-Tutu et al.

(2010) reported that an outgoing government could be subjected to a strict audit and accountability

process in the case of any hint of corruption.

However, the audit process is required to be executed by highly qualified independent auditors, an anti-

corruption institution with such expertise. Lastly, lack of coordination among government departments

and workers subjected to job insecurity, especially in the government and public domains just as in the

case subjecting workers to low-level salary in OSC construct, puts employees in the position to secure

as much as possible and through any means, whatever financial needs needed to secure a healthy future

(Alutu, 2007). This then puts the public worker in a position to embezzle public funds through any

possible and vulnerable medium.

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Figure 3.3 Graphical presentation of the constructs mean score

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3.4 Anti-Corruption Measures4

Developing practical and innovative techniques for combating the pervasiveness of corruption in CPM

is essential to the good image, profitability, timely execution, and delivery of high-quality projects. The

past years have seen appreciable contributions toward the body of knowledge on corruption in CPM.

This development has led to an increase in literature on the subject matter, including anti-corruption

measures and frameworks developed to tackle corruption in CPM. However, a comprehensive and

systematic assessment of both existing and past research on the subject matter, which is vital for future

endeavors, is not available. Also, existing studies show the lack of a unified view of the ACMs and

frameworks developed over the past years for the management of construction projects. This section,

therefore, reviews the anti-corruption measures (ACMs) developed to mitigate the pervasiveness of

corruption in CPM using a two-stage review process to identify the publications and the measures.

The following sub-objectives were set to realize the aim: (1) to review the pattern of publications

devoted to ACMs in CPM, (2) to identify the ACMs in CPM, and (3) to develop a conceptual framework

to facilitate easy identification of the ACMs and also to set as a guide to enhance existing measures and

future development and implementation of more stringent ACMs. The findings contribute to an in-

depth understanding of ACMs in CPM. Moreover, this review section is vital to industry practitioners

and anticorruption institutions because it renders excellent support to their corruption-free work, thus

benefiting the practice. Lastly, this article contributes to the body of knowledge by conducting a

comprehensive review of current anti-corruption measures applied in the day-to-day modus operandi

and management of construction and engineering projects. Research gaps are identified and discussed,

and suggestions are made for future research directions. The checklist and framework developed in this

review section are useful for further empirical studies and discussions. The subsequent sections

explicate the details of the aim and objectives of this section.

4
Owusu, E. K., Chan, A. P., DeGraft, O. M., Ameyaw, E. E., & Robert, O. K. (2019). A contemporary review
of anti-corruption measures in construction project management. Project Management Journal, 50(1), 40-56.

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3.4.1 Preventing Corruption

Several preventive and reactive measures commonly referred to as anti-corruption measures or

strategies have been formulated by researchers, anti-corruption institutions, policymakers, etc. They

include transparency mechanism, ethical code, administrative reforms stringent rules and legislation,

rigorous technical auditing system, whistle-blowing mechanism, contract monitoring, among many

others. These measures have been concurred by several empirical studies to be effective anti-corruption

strategies formulated to mitigate corruption in the construction sector (Sohail and Cavill, 2008; Boyd

and Padilla, 2009; Ho, 2012; Bowen et al., 2015; Shan et al., 2015; Hartley, 2009; Le et al., 2009; Zou,

2006).

Also, these are some of the noted ACMs identified from literature known to be effective against

corruption. For instance, Zou (2006) purported three approaches to dealing with corruption in the

construction industry. They are stipulated as follows: (1) the development of ethical and honest

construction culture, (2) establishing a policy of regular and random inspections, and lastly, instituting

construction works and processes supervision throughout the lifecycle of a project. The author pointed

out the first approach as a long-term measure, while the following two were regarded as short-term

strategies. Although substantial efforts to thwart the incidence of corruption have been stipulated by

researchers in the construction field, other notable international organizations such as the United

Nations, World Bank, TI, OECD, and the GIACC among many others have as well played active roles

in helping to fight corruption either directly or indirectly in the construction industry. These efforts are

rarely reported in studies, and as part of the identified preventive measures, this section presents the

efforts made by the international organizations in the next subsection. This information may guide

researchers as a source of reference to develop further anti-corruption measures or enhance the already

existing ones to tackle the causes of corruption identified in the construction industry. However, a

detailed list with respective references has been provided in the next section.

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Table 3.3: Overview of selected organizational initiatives

Organization Effort Origin Year of effect Reference

World Bank Institutional integrity activity USA 2001 Henry (2009), World Bank
(2008)
United Nations United Nations Convention against Corruption Mérida and 2005 de Jong et al. (2009).
New York
OECD Convention on Combating Bribery France 1997 & 1999 OECD (2016), de Jong et al.
(2009).
GIACC Provides resources to assist in the understanding, identification, and prevention of UK 2008 Stansbury (2009).
corruption in the infrastructure, construction, and engineering sectors.
GIACC promotes the implementation of the Project Anticorruption System PACS
Transparency International Openness of the decision-making processes Germany 2007 Henry,2009).
TI produced a suite of anti-corruption tools and reports in 2005. Krishnan (2009).
And in 2007 published a Project Anticorruption System PACS for the construction
sector.
International Standard ISO 37001 - Anti-bribery management systems Switzerland 2016 GIACC, 2016
Organization (ISO)
FIDIC Developed a practical tool, namely a comprehensive Business Integrity Switzerland 1998 Boyd and Padilla (2009); Henry
Management System BIMS for consulting firms. (2009); GIACC (2016)
In recognition of the multifaceted nature of corruption, in 2007, a parallel Switzerland 2007 Boyd and Padilla (2009).
Government Procurement Integrity Management System GPIMS was developed for
organizations that procured consulting services.
ASCE Set up of Task Committee on Global Principals for Professional Conduct GPPC USA 2004 Henry (2009).
World Economic Forum Partnership against Corruption Initiative Switzerland Henry (2009); GIACC (2016)
World Federation of Anticorruption Task Group - It has formed an Anti-Corruption Standing Committee, France 2005 Henry (2009); GIACC (2016);
Engineering Organizations which is tasked with promoting anti-corruption actions internationally. WFEO (2016)
(WFEO)
Union of Pan-American Anticorruption task group and anti-corruption committee Brazil 2009 Henry (2009).
Engineering Societies
(UPADI)
The Global Anticorruption a training guide, a train-the-trainer kit, and numerous other training materials USA 2006 Smith (2009).
Education and Training designed to reduce corruption
Project ACET
CIECI – Construction The sole purpose of CIECI is the promotion and advancement of ethical conduct and USA 2008 WFEO (2016)
Industry Ethics & compliance in the construction industry.
Compliance Initiative
CoST – Construction Sector promote increased transparency in international construction projects, South Africa 2012 Krishnan (2009); WFEO (2016)
Transparency Initiative and the UK

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Regarding this review, thirty-eight papers were finally considered valid and relevant and were selected

at the end of the two-stage search and after a thorough visual examination. The papers were analyzed

in terms of annual publication trends, identification of the ACMs developed, developments of constructs

by variable classifications, and explications to the constructs and their composing variables. Regarding

the papers devoted to the subject matter in this section, it is quite unfortunate to realize that few papers

have empirically dealt with the issue of corruption, particularly on the measures required to deal with

corruption over the years. This low record, therefore, calls for critical attention and research on ACMs

and more innovative frameworks to tackle corruption in CPM.

Despite the groundbreaking advancements made in construction management research, the industry still

lacks innovative approaches to dealing with the corrupt practices identified in the management of

construction and engineering projects. This is evident from the annual trend of publications, which has

not been very encouraging even though the body of knowledge devoted to corruption, in general, has

increased in the past decade. For example, the years 2009 and 2012 recorded the highest number of

publications as compared to the previous years and decades. One of the reasons for this increase stems

from the special issue on corruption in the CPM raised in 2009 by the Journal of Leadership and

Management in Engineering (Owusu et al., 2017). Moreover, it is interesting to note that while

corruption has engendered considerable scholarly attention, studies on pragmatic ways to deal with this

menace seem to be relatively few—a situation that should be addressed sooner rather than later. The

primary lesson to draw is that more research on corruption should be encouraged on an annual basis

with respect to developing pragmatic and innovative measures to reduce the alarming rate of corruption

in CPM.

3.4.2 Findings from Studies on Anti-Corruption Measures

Although the research studies on ACMs in construction in the selected journals are quite sporadic

regarding the number of publications, some of the identified papers conducted comprehensive

explications on the identified measures. Table 3.6 shows the findings of the 38 selected publications,

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accumulating and displaying the number of times each ACM appears in a publication. For example,

rigorous technical auditing systems and contract monitoring were identified by 13 and 12 different

publications, respectively, and the indications [1] and [2] and the numbers represent the individual

publications that identified the ACMs. From Table 3.6, it is clear that several anti-corruption measures

have been developed or proposed to combat corruption in CPM. However, the most identified measures

are ethical code, transparency mechanism, training and development initiatives, raising awareness,

rigorous technical auditing systems, and contract monitoring. The remaining identified ACMs are

presented in Table 3.6 and explained within their respective constructs. The references for the measures

have been presented in the Appendix following the Conclusions section.

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Table 3.4: Findings on Anti-Corruption Measures

No. Anti-corruption Measures Reference (Order of frequency) Total
1 Ethical code [1]; [2]; [3]; [4]; [5]; [6]; [7]; [8]; [11]; [13]; [14]; [15]; [16]; [19]; [21]; [22]; [23]; [25]; [29]; [30]; [32] 24
2 Transparency mechanism [1]; [2]; [3]; [4]; [6]; [7]; [8]; [13]; [15]; [16]; [18]; [19]; [20]; [21]; [22]; [24]; [25]; [27]; [28]; [29] 21
3 Training and development initiatives [2]; [5]; [6]; [12]; [13]; [17]; [19]; [20]; [21]; [23]; [24]; [25]; [29]; [31]; [32]; [33] 16
4 Raising awareness [7]; [12]; [13]; [17]; [21]; [22]; [23]; [24]; [25]; [26]; [29]; [33]; [34] 13
5 Rigorous technical auditing system [1]; [2]; [4]; [5]; [6]; [7]; [16]; [23]; [24]; [25]; [27]; [29]; [33] 13
6 Contract monitoring [6]; [7]; [8]; [10]; [12]; [14]; [15]; [20]; [23]; [24]; [25]; [26] 12
7 Comprehensive rules and regulations [2]; [3]; [5]; [6]; [12]; [13]; [23]; [24]; [25]; [27]; [29]; [30] 12
8 Harsh punishment or penalty [1]; [3]; [5]; [7]; [12]; [13]; [19]; [21]; [22]; [26]; [31]; [34] 12
9 Whistle-blowing mechanism [7]; [12]; [17]; [19]; [20]; [22]; [23]; [24]; [25]; [26] [29] 11
10 Compliance to fairness and transparent procedures [2]; [3]; [4]; [6]; [7]; [11]; [15]; [21]; [23]; [24] 10
11 Education [5]; [19]; [20]; [24]; [27]; [29]; [31]; [32]; [33] 9
12 Increase in accountability [4]; [6]; [7]; [15]; [23]; [24]; [25]; [28]; [29] 9
13 Access to information [2]; [16]; [18]; [19]; [21]; [23]; [24]; [25] 8
14 Corporate governance [1]; [4]; [10]; [20]; [21]; [23]; [25]; [29] 8
15 Financial disclosure / Disclosure [7]; [16]; [19]; [23]; [25]; [26]; [29] 7
16 Contractual compliance [2]; [11]; [12]; [13]; [20]; [23]; [25] 7
17 Good Leadership [1]; [2]; [5]; [23]; [24]; [29]; [33] 7
18 Professional associations [7]; [11]; [16]; [28]; [29]; [33] 6
19 Debarment/ Promoting fair debarment procedures. [1]; [7]; [13]; [19]; [21]; [22] 6
20 Procedural compliance [2]; [6]; [20]; [23]; [25]; [27] 6
21 Rigorous supervision among others [2]; [3]; [18]; [19]; [23]; [25] 6
22 Compliance to code of conduct [6]; [7]; [19]; [23]; [25]; [29] 6
23 Integrity pacts [1]; [4]; [5]; [7]; [13]; [24] 6

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24 Well-structured project governance [13]; [14]; [23]; [24]; [25] 5

25 Strengthening of professional institutions [7]; [22]; [24]; [25] 4
26 Existence of procurement rules and legislation [5]; [23]; [24]; [25] 4
27 Publication of contract and implementation details [2]; [15]; [23]; [25] 4
28 Enhanced due diligence [7]; [12]; [16]; [29] 4
29 Administrative reforms [15]; [18]; [23] 3
30 Effective investigation, court proceedings, [22]; [23]; [26] 3
departmental disciplinary action
31 Development of strong political and ethical will to [30]; [33]; [34] 3
enforce existing anti-corruption policies and laws
32 Checks and balances [23]; [29] 2
33 Enhance communication [7]; [23] 2
34 Oversight [7]; [15] 2
35 Dismissal from employment or other disciplinary [21] 1
action]
36 Anonymous assistance [17] 1
37 Adherence to professional standards [33] 1
38 Efficient reporting system (Independent hotline) [33] 1
39 Information technology [1] 1
1= Le et al. (2014a); 2= Le et al. (2014b); 3= Zhang et al. (2016); 4= Bowen et al. (2012); 5= Tabish and Jha (2012a); 6= Tabish and Jha (2012b); 7= Sohail and Cavill
(2008); 8= Valdes-Vasquez and Klotz (2012); 9= Ho (2012); 10= Shen and Song (1998); 11= Hartley (2009); 12= Krishnan (2009); 13= Boyd and Padilla (2009); 14=
Sohail and Cavill (2006); 15= Kenny (2012); 16= Sichombo et al. (2009); 17= Rebeiz (2011); 18= Hawkins and McKittrick (2012); 19= de Jong et al. (2009); 20= Stansbury
C. (2009); 21= Stansbury N. (2009); 22= Bowen (2007); 23= Zou (2006); 24= Tanzi (1998) 25= Søreide (2002); 26= Suen et al. (2007); 27= Tashjian (2009); 28= Ling et al.
(2014); 29= Brown, J., & Loosemore (2015); 30= Porter (1993); 31= Alutu (2007); 32= King et al. (2008); 33= Powell (2006); 34= Shakantu (2006)

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3.4.3 Constructs’ Development

Table 3.6 presents the variables identified in the 38 papers selected for this section of the review study.

All the 39 ACMs were categorized into six distinct constructs. The development of the categories was

done following the studies of Tabish and Jha (2012) and Narasimhan (1997) and employing the thematic

analysis approach to extract the main theme of each variable to facilitate the categorization process

(Owusu et al., 2017). Previous studies identified and categorized ACMs into two main constructs—

namely, proactive and reactive measures (Zou, 2006). Proactive measures represent the ACMs that are

strategically developed to prevent or safeguard public and private institutions from the possible

occurrence of corrupt actives, whereas reactive ACMs are established to deliver justice or required

punishment to offenders or culprits liable to the corrupt offense. The constructs developed in this review

further develop the two constructs identified in the studies of Zou (2006), Tabish and Jha (2012), and

Narasimhan (1997).

The thematic analysis approach was adopted to facilitate the groupings of the variables into their

respective constructs. The approach considered the core theme and meaning of each respective variable.

Moreover, other categorizations of some of the successful ACM models developed globally were

examined to enhance the constructs’ development process. For instance, the Independent Commission

Against Corruption of Hong Kong uses a three-pronged approach: law enforcement (regulatory

measures), prevention (proactive measures), and education (promotional or publicity measures). Under

these three categorical themes exist specific objectives and variables aimed at mitigating corruption in

Hong Kong (De Speville, 2010; ICAC, 2016). Thus, following the developments on previous studies

and the thematic approach adopted, six main constructs were developed: regulatory measures,

managerial measures, probing measures, compliance measures, promotional measures, and reactive

measures. Fig. 3.5 represents the conceptual framework encompassing the developed constructs.

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Figure 3.4 Conceptual framework of ACMs in CPM.

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3.4.4 Discussion

Fig. 3.5 illustrates the conceptual framework made up of the developed constructs and their respective

variables: regulatory measures (RGM), managerial measures (MAM), probing measures (PBM),

compliance measures (COM), promotional measures (PRS), and reactive measures (REM). Even

though the categorization was developed based on past studies and thematic explications of each

variable, it should be emphasized that these constructs are not independent of one another. Inasmuch as

the variables have been grouped under specific constructs, some of them may be applicable to other

constructs. For instance, ethical codes under regulatory measures can be applied to managerial

measures, since administrative bodies and policymakers formulate or develop ethical codes to govern

the effective administration of institutions, bodies, and persons involved in CPM. However, ethical

codes are better classified as regulatory measures, which cover a broader scope and may apply to both

statutory and institutional domains. Depending on the nature or characteristics of the project at hand,

specific measures within each construct can be employed to either limit or extirpate the proliferation of

corrupt practices at any of the stages involved in the construction process.

However, the application could be based on the empirical determination of likely forms or causes of

corruption capable of distorting any phase of the construction process (Chan & Owusu, 2017; Le et al.,

2014a; Owusu et al., 2017). The development and explication of each construct are discussed in the

subsequent sections. Analogous to the study of Chan and Owusu (2017), the weightings of each

variable, based on their number of citations in the papers selected for this section of the review, are

determined using the mean score approach. It should be noted that the mean score of each construct

does not represent any specific cultural or institutional background, but only indicates the attention

given to the explications and application of each variable with its corresponding construct. The mean

score of each category is therefore determined by the summation or total frequency of citation of each

ACM within its specified category, divided by the specific number of variables, n, forming the category.

For example, the mean score of the PBM category was determined, as indicated below:

∑(𝑃𝐵𝑀1 + 𝑃𝐵𝑀2 + 𝑃𝐵𝑀3 … + 𝑃𝐵𝑀8)⁄ ∑(13 + 12 + 11 + 6 + 6 + 2 + 1 + 1)

𝑛= ⁄ = 6.50
7

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The calculations for the remaining five categories were determined using the same technique, and the

results of each category are presented in Table 3.7 and Fig. 3.6, respectively.

3.4.4.1 Managerial Measures

Managerial measures refer to the proactive administrative ACMs set to guide the effective

administration of the internal structures of an institution and the relations with other external influences

against corrupt practices that possess the potential to distort the managerial systems of an organization.

In other terms, these may be regarded as organizational-specific measures. This construct came third,

with a mean score of 7.11. The term management here does not only refer to organizational or

institutional administrative departments but also stretches to the public-sector management boards. The

ACMs identified under this construct, therefore, relate to both public-sector boards in charge of

infrastructure procurement as well as other institutions concerned with the construction and

management of infrastructure projects. Athanasouli and Goujard (2015) pointed out that corruption

decreases aggregate efficiency by weakening stable management practices.

Therefore, to increase administrative or managerial efficiency, it is expedient to develop and implement

strategic managerial measures to mitigate or expunge the practices and effects of corruption effectively.

Under this construct, the transparency mechanism variable was identified as the leading variable (de

Jong, Henry, & Stansbury, 2009; Hawkins & McKittrick, 2012; Ling et al., 2014). A total of 21 out of

38 publications identified transparency mechanism as a significant approach to combat corrupt practices

exposed to administrative units involved in CPM (Bowen et al., 2012; Le et al., 2014a; Shen & Song,

1998; Sohail & Cavill, 2008; Zhang et al., 2016). TI (2016) defines transparency mechanism as a

distinguishing feature of individuals, organizations, companies, and governments of being more open

in carrying out daily operations and processes as well as the dissemination or disclosure of information,

plans, and rules. Transparency mechanism is considered one of the main pillars of ACMs in construction

procurement (Sohail & Cavill, 2008; Zhang et al., 2016). Developing countries such as Vietnam, the

Philippines, Zambia, and Tanzania are believed to have made significant efforts in incorporating

initiatives regarding transparency to help eliminate corrupt practices in the management of construction

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projects (Goldie-Scot, 2008). A study conducted by Sohail and Cavil (2008) also suggests that adopting

a transparency mechanism in providing the public with any information regarding construction projects

is necessary to monitor project performance and to hold decision-makers accountable for their

decisions. Consistent exposure of implementation details and contracts was regarded by Kenny (2012)

as a conventional method to enhance the transparency of a project.

Other managerial measures include corporate governance, which represents the regulations, practices,

and procedures by which an institution is controlled or directed professional associations and the

strengthening of professional institutions integrity pacts and enhanced due diligence (Krishnan, 2009;

Sichombo et al., 2009; Owusu et al. 2018). Studies assert that no successful management or

administrative authority can happen without good leadership. Good leadership is, therefore, considered

one of the pivotal components of every thriving and successful management board. Le et al., 2014a;

Powell, 2006; Tanzi, 1998) and may serve as motivation for encouraging good or acceptable ethical

behaviors and, to a large extent, ACMs. According to Wallis (1989), administrative reform refers to an

induced, perpetual enhancement in the administration of an institution. There are numerous objectives

behind administrative reforms.

However, for this review, AR aims to create an ethical environment and a positive industrial climate,

coupled with enhanced productivity, and this can only be achieved through good leadership (Hawkins

& McKittrick, 2012; Kenny, 2012; Zou, 2006). Checks and balances represent a system that enables

different arms of authority to check, veto, or amend acts of another arm or branch of authority to prevent

that branch from abusing or exerting “more than necessary power” (Brown & Loosemore, 2015; Zou,

2006). This system was reported to be an effective ACMs where equally or a more powerful external

force is put in place to check the powers delegated to any of the project teams for a project. Ranging

from the public procurement body to consulting and contracting teams, external agencies can be put in

place to ensure that consenting parties do not abuse nor exert too much of the power delegated to them.

This system, in turn, increases transparency and accountability and can prevent the abuse of power,

which is seen as the central focus of corruption (Brown & Loosemore, 2015; Zou, 2006). Lastly, to

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enhance the performance and strength of management in its dealings or to fight against corruption, the

International Standard Organization (ISO) has developed a new set of standards to help organizations

fight bribery and promote an ethical business culture. The document is called the Anti-Bribery

Management Systems—ISO 37001 (GIACC, 2016). As a flexible managerial anti-corruption tool, the

ISO 37001 can be adapted by any institution, private or public, small, medium, or large; in any country,

depending on the nature and size of the institution as well as the degree of bribery risk to which it is

exposed.

3.4.4.2 Probing Measures

Probing measures are proactive measures that are set to facilitate an effective investigation or auditing

process as well as ensure an operative recording and reporting system (Hindess, 2005; World Bank,

2011). The PBM construct came in fourth place with a mean score of 6.50 and eight variables. Because

of the clandestine nature of corrupt practices, corruption remains one of the toughest criminal acts to

investigate. Unlike other criminal cases, there is no crime scene, no left-over impression, no fingerprints

or observers to follow up.

According to Wai (2016), corruption investigations can be categorized into two main variants: (1)

probing previous corrupt offenses and (2) present case(s) or investigation(s). The author identified eight

fundamental conditions to ensure a very potent corruption investigation procedure: (1) getting

acquainted with nature and processes involved in corruption; (2) full investigative authority; (3)

adequate resources; (4) freedom from external forces; (5) confidentiality; (6) professionalism; (7)

international shared support and (8) effective reporting system. Moreover, a corrupt act transpires or

follows the following procedures: weakening or distorting required standards and stipulation of a

process; demanding or giving an offer, generally in the form of a bribe; sourcing for the offer (bribe);

payment of the offer (bribe) and lastly, disposal or utilization of bribe. These actions stem from or result

in abuse of power. The duty of an investigator or a probing agent such as an auditing officer is to gather

adequate evidence to prove that the process indicated above has taken place. Therefore, the investigator

is required to prove “what,” “who,” “where,” “when,” “why,” and “how” in every case, if possible.

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Moreover, there is a need for the investigator to be familiar with adequate probing techniques to be

competent and successful (Wai, 2016). The author listed some essential ones based on the ICAC success

model. They include aptitude in identifying and tracing the persons behind the corrupt act, the

companies and properties involved, good interview techniques and thorough scrutiny of documents.

Others include financial investigation, being able to act as an undercover or disguised official,

protecting witnesses, and adopting or employing physical and technical surveillance. Different

jurisdictions may possess or use different probing or investigative manuals to facilitate the investigation

of corruption. For instance, the Anti-Corruption Investigation and Trial Guide (USAID, 2005) in the

US, the Asian-Pacific Economic Cooperation (APEC, 2014), the OECD Investigation And Prosecution

Of Corruption offenses, the Contract and Procurement Fraud Investigation Guidebook (Piper, 2017),

among others. Every strategic and effective anti-corruption tool should encompass comprehensive

probing measures to facilitate corruption investigation.

3.4.4.3 Compliance Measures

To comply simply means to act or adhere to stipulated norms, regulations, demands, requests, and

principles. The compliance measures’ construct was ranked fifth with a mean score of 6.20. It

encapsulates five distinct variables, which are contractual compliance, procedural compliance,

compliance to code of conduct, adherence to professional standards, and lastly, compliance to fairness

and transparent procedures. The development of an anti-corruption framework or policies without

necessary compliance measures to check the adherence of the developed framework may render the

entire anti-corruption system (framework) ineffective. (Owusu et al., 2017). However, complying with

stipulated ACMs appears to be problematic, not only in the literature but also in real life. This is evident

in developing countries where there are numerous reported cases of procurement professionals not

following the laid-down principles for conducting effective procurement (Osei-Tutu, Badu & Owusu-

Manu, 2010; Tabish & Jha, 2011; Zou, 2006). This may be attributed to the assumed psychological and

philosophical notions that anti-corruption measures or other ethical and legal structures ought to be

followed once developed and enforced.

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This concept is sometimes assumed without drawing up practical compliance measures to inform parties

on how to comply with the measures and risks involved, should one decide not to consent to the

stipulated measures. The compliance measures that were captured in this review include compliance

with fairness and transparent procedures, contractual compliance, procedural compliance, compliance

to a code of conduct, and adherence to professional standards (Le et al. 2014; Bowen et al. 2012).

Worthy, John, and Vannoni (2017) identified five types of public compliance that can be applied in

institutions or the private sector: noncompliance, lesser compliance, partial compliance, full

compliance, and concordance. These were intended to facilitate or encourage effective compliance with

stipulated regulations regarding ACMs. Noncompliance can be regarded as non-adherence to statutory

law or regulations of an institution governing the procurement and contractual works. In the case of

lesser compliance, an attempt is roughly made to comply with the laid-down laws. Partial compliance

offers systematic adherence to the stipulated laws but occasionally occurs in an informal or ad hoc way.

Full compliance creates the systems and procedures needed for strict adherence to and observation of

legal obligations. Lastly, in concordance, the public and private entities embrace and support the laid-

down principles beyond what is required by the law (Burt & Taylor, 2009; Ritcher & Wilson, 2013;

Worthy et al., 2017). It is necessary to develop a strategic plan that will aid in establishing an atmosphere

of concordance or full compliance. A typical example of a compliance tool is the Anti-Corruption Ethics

and Compliance Handbook for Business that was jointly produced by the Secretariats of the OECD, the

United Nations Office on Drugs and Crime (UNODC), and World Bank (2013).

3.4.4.4 Regulatory Measures

Regulatory measures refer to stipulated statutory laws, decrees, or acts and institutional regulations

developed to prohibit illegal practices and encourage an ethical working atmosphere. It promotes

healthy and acceptable relationships among professionals, stakeholders, and developed structures such

as working procedures (Bowen et al., 2012; Shan et al. 2015a; Zhang et al., 2016). As a proactive

measure, the RGM category recorded the highest mean score of 11.00, placing it first. This means the

variables within the RGM construct had relatively higher citations as compared to others. For instance,

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“ethical code,” one of the RGM variables, had the highest frequency of 24 and “comprehensive rules

and regulations” with 14 citations. Other variables within the RGM construct are “the existence of

procurement rules and legislation” and “the development of strong political and ethical will to enforce

existing anti-corruption policies and laws.” TI (2016) defines an ethical code as a set of guiding

standards based on moral principles, norms, and central values that influence behavior and conduct in

institutions, societies, and government. Morals in this regard refer to how good or bad a person is at

differentiating right from wrong (Boyd & Padilla, 2009; Kenny, 2009). An ethical code is deemed to

be one of the most important of all the ACMs. Most studies aver that, as a proactive measure, an ethical

code represents every institution’s framework of dos and don’ts. It represents the primary regulations

for how a worker should carry out him/herself, which will auger not only the success of the institution

but also protect the moral values and preserve the good name of the institution. An institution without

any form of a regulatory framework or ethical code is susceptible to corruption and other unethical

practices (Fan, Ho, & Ng, 2001; Sohail & Cavill, 2008). According to Goldie-Scot (2008), it is

necessary to reward ethical behavior for constructing a more positive atmosphere in the industry. Not

integrating an ethical code as a standard behavioral checker can endanger the existence of an

organization or a procurement sector by making it prone to corrupt practices. Although different

jurisdictions may have different regulatory measures or legally binding stipulations, the United Nations

Convention Against Corruption is the only legally binding universal anti-corruption instrument.

3.4.4.5 Promotional Measures

Promotional measures are described as ACMs designed to propagate or publicize other developed

ACMs and strategies to combat corruption in CPM to persons under the influence of the stipulated

regulations as well as provide education on the topic of corruption. In other words, PRS can be described

as the connecting link between ACMs and the population that is under the influence of the stipulated

ACMs. The population involved could be industry professionals, public servants, or to a large extent,

the general public. PRS informs professionals and other stakeholders about the preventive (proactive)

measures that are already in place and how they are to be observed. PRS also tends to inform parties

about the possible punishments (reactive) measures that will be meted out to a culprit who is caught in

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corrupt activities. Sichombo et al. (2009) opined that stakeholders need to establish and promote ACMs

to mitigate unethical practices and to uphold high standards of ethics in the construction and engineering

sectors. With a mean score of 7.88 in the second position, variables under the promotional or advertising

construct were considered vital in developing or employing anti-corruption tools in construction project

management. This review identified nine different promotional measures (Table 2). They include

training and development initiatives, such as the Global Anticorruption Education and Training Project

(ACET) (Smith, 2009); raising awareness on incidences of corrupt practices and the probable reactive

measures meted out to offenders. Others include educating professionals and the general public about

the nature of corruption and the necessary procedures to take in the case of a situation regarding

corruption (Alutu, 2007; Tanzi, 1998; Tashjian, 2009). Tabish and Jha (2011) prescribed training as an

essential tool to encourage the consciousness of rules and issues concerning ethics among civil servants.

According to Doh, Rodriquez, Uhlenbreck, Collins, and Eden (2003), training and development as a

single variable is considered a normal extension of the principles and codes of institutions that may aid

in responding to costs that are either directly or indirectly related to corruption. Other promotional

measures include raising awareness on the general notion and characteristics of corruption through

education, workshops, conferences, and so forth ( Rebeiz, 2011; Sichombo et al., 2009; Tabish & Jha,

2011). Other promotional factors may relate to specific projects or organizational structures. For

instance, disclosing or publicizing vital documents such as contract and implementation details and

financial statements pertaining to a project or the public procurement spending on infrastructure projects

increases transparency and builds public trust (Le et al., 2014b; Sohail & Cavill, 2008; Suen et al.,

2007). Access to such vital information also contributes to an increase in accountability (Hawkins &

McKittrick 2012; Ling et al., 2014; Tanzi, 1998). Also, practical tools such as enhanced communication

can be adapted to effectively communicate or publicize ACMs internally among top management,

employees, and stakeholders, and externally among professional associations (Sohail & Cavill, 2008;

Zou, 2006). An example is the Korea Online E-Procurement System (KONEPS), a comprehensive,

integrated, end-to-end electronic procurement system that covers the entire cycle of the procurement

process electronically (OECD, 2016).

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3.4.4.6 Reactive Measures

Reactive measures refer to control mechanisms meted out to culprits or offenders found guilty of

committing or engaging in corrupt practices. REM came in the sixth position, with a mean score of

6.00. It was also one of the categories with the fewest composing variables. Depending on the

geographical (statutory/institutional) jurisdiction, reactive measures may vary as a result of disparities

in the legal structures binding a specific group of people or institutions. For instance, according to the

studies of Owusu et al. (2017) and Shan et al. (2017), although developed countries have stricter systems

or measures in place to check on corruption, the condition is opposite in the developing world as most

countries from the developing world fail to render stern measures to offenders. This is regarded as one

of the leading causal instigators of corruption in developing countries such as India (Tabish & Jha,

2011, 2012), China (Le et al., 2014b), Ghana (Osei-Tutu et al. 2010), and Zambia (Sichombo et al.,

2009). Moreover, even though under this construct, there are measures such as harsh punishment or

penalties debarment/promoting fair debarment procedures and dismissal from employment or other

disciplinary actions, their level or degree of enforcement varies from place to place.

No matter the number of proactive measures established and promoted in an organization, some

individuals will still take advantage of the secret nature of corruption. Reactive measures are stipulated

for these kinds of people. There is a need for effective investigation, and if a party is found culpable,

court proceedings or departmental disciplinary action can be arranged, depending on how intense the

corrupt action may be (Bowen et al., 2007; Suen et al., 2007; Zou, 2006). Harsh punishment or penalties

such as sanctions, criminal conviction (fines and imprisonment), debarment, and other possible punitive

measures can be meted out to offenders (Alutu, 2007; Boyd & Padilla, 2009; Shakantu, 2006). Hence,

after putting down preventive measures and informing employees of the rights and wrongs and what

constitutes corrupt activity, it is expedient that corrective actions be stipulated to serve as checks to

reduce the incidence of corrupt acts. These corrective actions may take the form of rendering

punishment to culprits, debarring offenders (individuals or institutions) from taking up any further

contracts, dismissing the culprits from employment, or other disciplinary actions that are deemed to be

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lawful and appropriate. Effective reactive measures are recommended to be in place to ensure proper

behavior from employees who may consider getting involved in corruption.

Figure 3.5 Graphical illustration of individual constructs’ Mean Scores

3.4.5 Factors Influencing ACM Formulation

Formulating strategic and comprehensive ACMs take several internal and external factors into

consideration (Wai, 2006), just as developed models such as the United Nations Convention Against

Corruption and Hong Kong’s ICAC three-pronged approach, which is globally recognized as a success

model, were developed and enforced taking into consideration some internal and external factors (Wai,

2006; Rooke & Wiehen, 1999). Thoughtful and pragmatic consideration should be given to examining

external factors such as political, legal, social, and economic environments. Moreover, Owusu et al.

(2017) identified more than 40 causes of corruption in construction project management and thematized

the variables into legal-specific, psychosocial specific, statutory specific, and organizational-specific

causes.

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Even though Wai’s (2006) suggestions on ACM formulation focus on general corruption (criminology

and public-sector corruption), the thematic constructs from the review study of Owusu et al. (2017) in

construction project management share a degree of agreement among the areas of focus. Furthermore,

internal structures, such as organizational systems, staff, adequate expertise, structure, strategic

corporate plan, shared values, and the management style to be adopted, require extensive examination

with regard to the development of ACMs.

3.5 Barriers Affecting Effective Application of Anti-Corruption Measures5

This section is introduced to explore just a single question, and that is, why are anti-corruption measures

intended to help extirpate or mitigate corruption often identified to be ineffective? Corruption continues

to be one of the topmost barriers to socioeconomic development and has lived with humanity for the

past five millenniums (Noonan 1984). Despite the proliferation of corrupt practices in the public and

private sectors which include the procurement and engineering sectors, the needed pragmatic efforts to

prevent corrupt practices have been enforced by several public entities and institutions such as

procurement boards and authorities in diverse contexts. However, the effectiveness of these measures

remains questionable (Shan et al. 2015a; Owusu et al. 2017; Ameyaw et al. 2017).

Anti-corruption measures in this context can be defined as the realistic, systematic, and strategic

measures developed, enforced, and applied to mitigate or expunge the pervasiveness of corruption and

its detrimental effects in the supply chain of infrastructure procurement and the management of project

execution. Numerous studies have reported on the susceptibility of the procurement stages to the

incidence of corrupt practices (Tabish and Jha 2011; Le et al. 2014; Locatelli et al. 2017), especially in

public infrastructure procurement. Moreover, due to the large sums of monies and resources expended

5
This chapter is fully or partially published in the following journal article: Owusu, E. K., & Chan, A. P.
(2018). Barriers Affecting Effective Application of Anticorruption Measures in Infrastructure Projects:
Disparities between Developed and Developing Countries. ASCE Journal of Management in Engineering, 35(1),
04018056.

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in infrastructure projects coupled with its complex nature, the procurement process has been tagged as

the most vulnerable process to corruption globally (Krishnan 2010; Chan and Owusu 2017; TI 2005).

Right from the conception stage where the requirements of a project are defined through to contract

close-out, diverse forms of corrupt practices are recorded, such as clientelism, solicitation, bribery,

among others (Chan and Owusu 2017). Researchers and policymakers have contributed immensely

towards the investigations of leading topical constructs regarding corruption in construction project

management, such as forms and causes of corruption, risk indicators, and anti-corruption measures.

This has, therefore contributed tremendously to the body of knowledge concerning corruption research

in construction project management.

The developments or formulations of effective anti-corruption measures, therefore, tend to focus on the

inferences of the identified constructs. It was somewhat surprising to discover that only a handful of

studies that have highlighted or made mention of some barriers that hinder the practical applications of

developed and enforced measures without any thorough empirical justifications. Therefore, whereas no

empirical investigations on this subject matter are available, 19 studies (Table 3.8) have either directly

or indirectly pointed out some encountered obstructions that derail the full potency during the

enforcement and application of developed measures in diverse contexts. Owusu et al. (2017) and Le et

al. (2014) pointed that most enforced anti-corruption measures would have achieved tremendous results

should there be appropriate measures to check the barriers that hinder their effectiveness.

The mentioned studies, moreover, recommended that future research should pay critical attention to

exploring these barriers as that will contribute to the development of more stringent and strategic ACMs.

This section, therefore, presents the critical barriers that obstruct the intended effectiveness of anti-

corruption measures developed overtime to mitigate corrupt practices in construction project

management. This section primarily contributes to a deepened understanding of corruption research in

construction project management, especially under the construct of anti-corruption research. The

findings reveal the criticality of the identified barriers and serve as a knowledge base for practitioners,

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policymakers, anti-corruption institutions, academic and industrial researchers to incorporate or refer

to during the development of anti-corruption measures. Thus, rendering tremendous support to the

enhancement of already existing or yet-to-be-developed anti-corruption measures to guide the day to

day procurement, execution, and management of construction and other infrastructure-related projects.

3.5.1 Anti-corruption Efforts and Identification of the Barriers

Efforts towards the development of realistic anti-corruption measures are initiated, implemented, and

enforced consistently to yield the desired results of mitigating corruption (Shan et al. 2015a). However,

one of the many queries raised on the topic of corruption lies in the effectiveness of anti-corruption

measures that are developed and enforced to tackle diverse forms of corrupt practices in different

contexts (Ameyaw et al. 2017; Le et al. 2014a, b; Owusu et al. 2017). From the perspectives of industrial

and academic researchers, some of the anti-corruption measures developed to check corruption in

project management include an increase in accountability, comprehensive rules and regulations,

effective investigation and court proceedings, departmental disciplinary action and rigorous supervision

among many others (Zou 2006; Suen et al. 2007; Tanzi 1998; Shan et al. 2015a, b; Hawkins and

McKittrick 2012).

Moreover, the contributions from top global organizations include International Organization for

Standardization (ISO) 37001 document, also known as the Anti-bribery management systems (ISO

2016; GIACC 2016), Transparency International’s Project Anticorruption System (Boyd and Padilla

2009), FIDIC’s Business Integrity Management System for consulting firms among many others

(Krishnan 2009; Boyd and Padilla 2009). However, despite the efforts and inputs from all these units,

corruption continue to be prevalent in construction and other infrastructure-related projects and their

management, especially in the context of the developing world. This is reported to be partly attributed

to the factors that impede their full functionality after enforced into effect. Even though not many, the

limited number of studies that have been conducted on this subject reveal critical barriers that are worth

the need for thorough explorations to come up with means with which they can be thwarted. This is as

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well envisioned to facilitate the development of new or strategic modifications of existing anti-

corruption measures towards the fight against corruption in construction project management. This

section of the review, therefore, intends to commence the discussion and encourages significant

contributions in future studies on the topic.

As it may be inferred from the previous section, barriers against the effectiveness of anti-corruption

measures in this context can be defined as the hindering factors that impede the effective enforcement

or application of the anti-corruption measures that are already in existence and these barriers to an

extent. One of the initial studies to report on the barriers in the area of construction management was

conducted by Bowen et al. (2012). The study examined the experiences of construction professionals

and clients in the South African construction industry. The respondents who participated in the study

shared their sentiments on the procedural difficulties in applying the stipulated anti-corruption measures

in the South African construction industry, such as reporting of corrupt cases. Among the many recorded

and reported barriers included structural and political barriers coupled with a number of psychological

constraints, which included an induced fear of victimization, social misrepresentation, fear of being

marginalized, social or occupational stigma, and rejection, among many others. Ameyaw et al. (2017)

also explored the pervasiveness of corruption in the Ghanaian construction industry, and one of the

listed constructs in their study explored the factors that cause prevailing anti-corruption measures to be

ineffective. Barriers such as fear of insecurity, which includes fear of losing job, and personal attitude,

for example, lack of will to become involved in fighting corruption among others, were identified. Other

studies have as well highlighted or reported similar constraints in different contexts. All the identified

barriers the valid publications have been summarized and presented in Table 3.8. Table 3.8, therefore,

presents a total of 17 barriers to effective anti-corruption measures identified in literature after a

comprehensive and systematic approach in selecting the needed valid papers as well as extracting the

barriers from the retrieved publications. Even though the factors representing the barriers have been

captured under this section, a thorough discussion of the constructs and the categorical constructs have

been discussed in Chapter 8.

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Table 3.5: Barriers to Effective Anti-corruption measures

Code Barriers References
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
B1 Political and structural barriers. x x x x x x x x x x
B2 Fear of insecurity which includes fear of losing job, x x x
B3 Fear of losing life x x
B4 Social misrepresentation, x
B5 Fear of being sidelined or marginalized, x x
B6 Fear of being caught reporting, x x
B7 Social or occupational stigma and rejection, x x
B8 Bureaucratic process of reporting corrupt cases, x x x
B9 Lack of independence x
B10 Fear of victimization, x
B11 Inappropriate co-ordination of internal structures of an x x x
institution/ interagency relation
B12 Perception of no better end result, distrust in system, x x
B13 The lack of political will by government officials and statutory x x x x x x
professional councils to fight corruption.
B14 Lack of knowledge and understanding of their one’s rights x x x
within a contractual environment coupled with the difficulty in
giving tangible evidence in the event of corrupt activity.
B15 Inappropriate staffing x x
B16 Lack of knowledge or non-familiarity with ethical codes/ x x x x x
organizational codes of ethics
B17 Personal attitude, for example, lack of will to become involved x x x x
in fighting corruption.
1 = Ameyaw et al. (2017); 2 = Tabish and Jha (2011); 3= Locatelli et al. (2017); 4= Owusu et al. (2017); 5= Chan and Owusu 2017) 6 = Bowen et al. (2007).
7= Zou 2006; 8 = Le et al. (2014); 9= Porter (1993); 10 = Bowen et al (2012); 11= Iyer & Sagheer (2009); 12 = Stansbury (2009); 13 = Osei-Tutu et al
(2010); 14 = Shan et al. (2015a); 15 = Shan et al. (2017); 16 = Sohail and Cavill (2008); 17 = Krishnan (2009); 18 = Tidey (2013); 19 = Alutu (2007).
Note: Further details to the references have been presented at the appendix section

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3.6 Regional Perspectives of Corruption: The Developing and The

Developed Contexts6

Explicitly, there are disparities across different cultures when we consider the happenings and outcomes

of the variables identified, and the underlying categories developed. Whereas many European countries

have stricter anti-corruption measures with corresponding enforcing strategies to deal with the causal

factors identified, other regions such as the Middle East, some parts of Asia, and Africa struggle to

enforce strict ACMs to deal with these factors. Hence, these causal variables are still reported to be

pressing in the regions mentioned. For instance, Le et al. (2014b) conducted a study investigating the

causal relationships between the instigation of corruption and the risk indicators of corruption in the

Chinese public construction sector. They reported that the most pressing causal construct that fuels

corrupt practices in the Chinese region has to do with regulatory-specific causes. Nguyen and Chileshe

(2015), also pointed out that corruption (basically PSC) was one of the leading factors of project failures

in Vietnam.

In Africa, Bowen et al. (2012) reported the leading causes of corruption in the South African

construction industry are lack of transparency in the award of public contracts and also lack of a positive

operating environment. Other leading forces that the authors reported had to do with the barriers that

impeded the effective reporting of corruption cases. This factor is reported by other studies focused on

developing countries such as Ghana Osei-Tutu et al. (2010), Zambia Sichombo et al. (2009), and other

investigations. It should be emphasized that different cultures reveal different patterns of causal

mappings as well as measures adopted to tackle these issues. In developed countries such as Singapore,

The USA, UK and cities like Hong Kong, corruption in CPM is somewhat checked by measures or

systems such as e-procurement, raising awareness, rigorous technical auditing system, contract

6
This chapter is fully or partially published in the following journal article: Owusu, E. K., Chan, A. P.,
Ameyaw, E. E., & Robert, O. K. (2020). Evaluating the Effectiveness of Strategies for Extirpating Corrupt
Practices in Infrastructure Project Procurement. ASCE Journal of Infrastructure Systems, Ref.: ISENG-1519R5.
(in press)

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monitoring, comprehensive rules and regulations, education, access to information, stringent

supervision among others (de Jong et al. 2009; Le et al. 2014a, b; Tabish and Jha 2012; Zou 2006;

Vaidya et al. 2006; Neupane et al., 2014). Particularly, Hong Kong, one of the world’s finest cities, has

gone a long way in dealing with corruption and has made tremendous efforts in its fight against

corruption in CPM. The establishment of ICAC in 1974 revealed that Hong Kong.

3.6.1 Developing Countries – Ghana as a Case Study

The issue of corruption in the developing context is not only reported in the extant literature and reports

but also evident in everyday life of the societies, people, and the public projects within this context (Le

et al. 2015; Ameyaw et al. 2017). The problem of poor administration or misappropriation of

government funds – corruption – has been very pervasive in emerging economies due to several causal

mechanisms, also referred to financial irregularities (Bardhan 2006; Doig, 2012; Tabish and Jha, 2011).

Over the years, the country has seen misappropriation of public funds due to the presence of

irregularities presented in this chapter. These amounts are intended to be directed to the development

of public infrastructure, social amenities, education, among many others. However, either less or no

practical efforts have been taken to annul these unprecedented misfortunes.

In the Ghanaian public sector, some of the impacts of the prevalence of these irregularities or corruption

indicators experienced are stifled and abandoned projects, late delivery of projects, the use of cheap

inferior materials leading to the execution of construction projects of low-quality standard, etc. (Osei-

Tutu et al., 2009). There is an increasing consensus that one of the key impediments in public

administration of developing countries for the effective socioeconomic service delivery is corruption

(Vian et al., 2012; Svensson, 2005). Governments and donors have therefore responded to this menace

thwarting their growth and development with a comprehensive range of interventions aimed at

strengthening accountability in the public sector (Bardhan, 2006; Rose-Ackerman, 2005) and Ghana is

no exception. Specifically, in the public sector, the Attorney-General (A-G) of Ghana is vested with the

power to conduct effective audits of government enterprises partly to determine the causal factors

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triggering the incidence of corruption in the country. These audits performed by the A-G reveals the

irregularities prevalent in the public sector and are reported in the Ghana Audit reports. The

irregularities are reported by Tabish and Jha (2011) and Le et al. (2014) as the indicators of corruption

in the public sectors. They, therefore, need immediate attention, and elimination once detected because

they negatively affect the administration of public funds and lead to misappropriation of the funds.

However, no research study to date has systematically assessed these causal measures that trigger the

misappropriation of the public funds, the impact on the economy and public administration as well as

the solution measures needed to thwart or hopefully curb these financial irregularities in the Ghanaian

public sector. This section of chapter four fills that gap by assessing procurement and contractual

irregularities that trigger the misuse of public funds, determining the legal measures and other

regulations in place, and lastly, recommending measures aimed at curbing the incidence of financial

irregularities in the Ghanaian public sector. The areas identified with the incidences of the irregularities

are therefore skewed towards public financial records of the public departments, ministries, public

agencies, corporations, boards and other institutions of the State in their procurement and contractual

works.

3.6.1.1 Defining Corruption in the Ghanaian Context

Corruption exists in several forms and shapes and triggered by many causal factors (Tanzi, 1995; de

Jong, 2009; Shan, 2015). For instance, while TI (2017) identifies the following forms of corruption:

bribery, collusion, conflict of interest, embezzlement, nepotism, etc. prevalent in most public sectors,

other studies such as Le et al. (2014); Søreide (2002); Stansbury (2009) have also identified several

causal instigators identified in most sectors such as the procurement and construction sectors. Gupta et

al. (2002) there is a reported increase in poverty and income disparity as a result of the presence of

corrupt practices in the public sector. Identified by Dreher et al. (2007), the adverse effects which are

observed as a result of corruption on the global economy are: stifled investments, reduced services

provision, increased disparity, truncated economic growth, and others. Shah (2011) blames corruption

as both the leading cause and the outcome of global poverty. This unethical behavior is experienced at

all levels of the general public, and the only causal effect it leaves behind is extreme poverty on the side

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of citizens. Just as opined by NACAP (2011) and Osei-Tutu et al. (2009), the endemicity of corruption

in the Ghanaian context emanates from history and has been a severe setback to the country’s political

and socio-economic advancement since 1957’s independence.

The severity of corruption in Ghana in both private and public sectors is owed to its secretive and

ubiquitous nature and the ability of permeate in every economic sector (NACAP, 2011) even though

Section 239 of Act 29, also referred to as the Criminal Offences Act, prescribes it. Several reports have

indicated the pervasiveness of corruption in the Ghanaian public sector. From international bodies to

local reports and empirical surveys. For instance, as of the year 2005, a study conducted by GII showed

that 90% of the respondents considered corruption to be a far-reaching problem in Ghana whiles 92.5%

believe that corruption is highly rampant in Ghana. On the international scale, the World’s Bank

Country Policy and Institutional Assessment (CPIA) on transparency, accountability, and corruption in

the public-sector rating concur with similar findings. For the sake of explicit clarifications, the

performance of Ghana’s corruption perception index by Transparency International is briefly discussed

below.

3.6.1.2 Ghana’s Performance on the Global Scale

According to TI (2017), there is not a single country that got closer to the perfect score that represents

the corruption perception index of the just-ended year 2016. This applies to the case of Ghana. Over the

years, Transparency International, a world-renowned anti-corruption agency, conducts a global survey

to assess the performance of world economies regarding corruption perception. Fig. 3.7 indicates

Ghana’s performance over the past decade.

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CPI of Gh an a
100
90
80
70
60
50
40
30
20
10
0
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Ghana 33 37 39 39 41 39 45 46 48 47 43
Bechmark 100 100 100 100 100 100 100 100 100 100 100
Passmark 50 50 50 50 50 50 50 50 50 50 50

Figure 3.6 CPI of Ghana for the past decade (Adapted from TI, 2017)

Fig. 3.7 presents the performance of Ghana between 2006-2016. Comparing this data to the previous

year is not later than 2006, it was identified that Ghana had improved in the global ranking. However,

to date, Ghana cannot be considered as a clean country per the results of TI simply because there has

never been a moment that the country attained a score of more than 50, which represents the pass mark.

Countries found within the region of 50-100 are regarded as clean countries, and per the latest results

released by TI (2017), 54 out of 176 countries are ranging from Denmark, 1st, to Slovakia, 54th were

captured in the clean region. This indicates that per the number of countries identified by TI, only

30.68% lies in the clean region.

However, it should be realized that even among the 30.68%, not all of them are regarded as very clean.

This indicates how challenging corruption is in the global context. Ghana attained a score of 43 in the

most recent ranking, obtaining a position of 70 out of 170 countries. There was a drop of 4 points as

compared to 2015 results. The performance of Ghana with regards to corruption on the global market

is a direct reflection of the irregularities or corruption indicators identified by the A-G over the years.

Ghana’s public sector has been hit with plagues of corruption cases to the point that the executive

opinion survey conducted by the World Economic Forum (WEF, 2016) identified corruption as the

second most problematic factor for conducting business in Ghana. Moreover, although there are both

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direct and indirect causal factors that instigate or propels the incidence of corruption in the public sector,

the A-G stipulates that the irregularities identified and reported over the years represent direct indicators

or corrupt practices. Therefore, drawing and enforcing proactive and reactive measures taking these

irregularities into consideration are deemed necessary to thwart the frequent occurrence of corrupt

practices in the short term and annul its incidence in the long term. Many efforts have been given by

successive governments to strengthen and safeguard public sectors from corruption since the attainment

of independence till date.

Fig. 3.8 and 3.9 also highlight Ghana’s performance in Worldwide Governance Indicators (WGI),

Corruption Control, and GCI on Government Integrity by the World Bank and the World Economic

Forum, respectively. Per the indications read from both graphs, Ghana has been within the range of 50-

60 for WGI on corruption control and 30-48 for GCI on government integrity, which has not been that

encouraging. The years from 2013 to 2016 saw a steady rise in performance on government’s integrity

which measures corruption, the massive decline from 48 (Ghana’s best score over the two decades) to

35.5, does not depict a sign of any real hope for the future. Ghana, however, has never achieved the

pass mark of 50 and above for the past two decades, which partly demonstrates poor public

administration regarding government’s integrity. The case shown by WGI on corruption control is quite

similar to the first instance. There is, therefore, the need for long-term practical measures to be put in

place to check the irregularities or corruption instigators prevalent in the country.

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WGI on Corru p t i on Con t rol

70
60
50
40
30
20
10
0
2000 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Ghana 58 47 49 50 46 59 59 57 60 60 59 56 57 51 53

Figure 3.7: Worldwide Governance Indicators, (WGI) on Corruption Control

Source: World Bank (2016)

G CI on G overn men t In t egri t y

60
50
40
30
20
10
0
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Ghana 33 33 35 34 39 33 36 40 33 37 39 39 41 39 40.4 46 48 35.5

Figure 3.8: Global Competitiveness Index (GCI) on Government Integrity

Source: World Economic Forum (2017)

3.6.1.3 Decadal Point Interventions

The government of Ghana has set not only several legal frameworks and structures to mitigate

corruption within the public sectors in place but also the private sectors as well. The framework below

depicts the legal structures in the form of acts, legislation, and policies set by successive governments

since the independence of Ghana. The interventions are stipulated and illustrated in decadal periods as

presented in Fig. 3.10. Further explications to their fight against corruption in their respective

designated areas are presented after the illustrations. The framework was adapted from A-G Reports

used for this review and also from NACAP (2011) Global Insight (2016); Constitution (1992); Osei-

Tutu et al. (2009).

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Figure 3.9: Decadal Efforts on Legal Anti-Corruption Frameworks.

Source: Owusu et al. (2020)
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The effect of these legal provisions is to create the foundation from which the anti-corruption fight

can be developed. To fulfill these constitutional provisions, the State, through the legislature, has

enacted various pieces of legislation to combat corrupt activities of any form.

3.6.1.4 Corruption in Public Projects

In Ghana, corruption has been noted as a key impediment to the successful completion of vital public

projects. For instance, Ameyaw and Chan (2015) identified corruption the second most critical risk

indicator against public-private partnership (PPP) water projects in Ghana. A similar study conducted

by Osei-Kyei and Chan (2017) also revealed corruption to be the topmost risk indicator to PPP projects

in Ghana. The list goes on and on as Damoah and Kumi (2018) recently reporting corruption to be one

of the vital contributors to public project failure. The issue of corruption in the developing context,

particularly in Ghana, has always been on the rise with limited efforts expended in exploring this

menace can be tackled. The explorations of the negative constructs are mostly conducted to reaffirm

the notion or supposition that corruption is prevalent in the developing context. Lastly, with limited

efforts expended on how to address the ineffectiveness of ACMs, the significant relationship of the

factors causing the ineffectiveness of the existing ACMs are yet to be explored not only in the

developing context but also within the scholarship of corruption-related studies in public projects.

3.6.1.5 Irregularities in Public Project Procurement

Government procurement has been one area of attack regarding corruption (Ateljevic and Budak, 2010).

Krishnan (2010), Soreide (2002), and Transparency International (2005) reported that public

procurement on the global scale stands to be the sector that is most prone to corruption. Simply put, the

tendency for corrupt practices to occur at any stage of the procurement process is extremely high as

compared to other sectors and industry such as the manufacturing sector. According to Tabish and Jha

(2011), Public Procurement encompasses all the outsourcing activities of a state or a government. In

other words, it includes the overall process of purchasing or acquiring goods, works, and services by

the government (Thai, 2008; Tabish and Jha, 2011).

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The stages may include the procurement planning stage, the preparation, and processing of procurement

requests, which includes carrying out a market survey or research. Other stages include the development

and review of requirements documents, planning for the evaluation, or tender assessment stage through

to the awarding contract to the successful bidder to the signing of contract and administration of the

contract. The processes involved in a typical public procurement may include more comprehensive

stages than what has been stipulated above. Due to the complexities of the stages as well as the number

of parties involved, the whole process gets exposed to corrupt practices. Contract irregularities can be

referred to as corruption indicators or anomalies peculiar to contractual negotiations and processes.

Most governments face similar challenges when it comes to procuring infrastructure or construction

works (Tabish and Jha, 2011). Table 3.9 stipulates the irregularities identified in procurement works.

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Table 3.6: Irregularities in Procurement

REFERENCES (REPORTS)
No. Irregularities 1 2 3 4 5 6 7 8 9 10 11 12
1 Institutions not following correctly the Public Procurement Act regarding √ √ √ √ √ √ √
obtaining minimum quotations, exceeding authorized threshold limits and
unauthorized sole sourcing of suppliers.
2 Lack of adequate supervisory control over procurement transactions and √ √ √
management
3 Payments for uncompleted works √ √ √ √
4 Non-application of sanctions √
5 Poor supervision of subordinate officers √
6 Disregard for Public Procurement Act regulations √
7 Procurements not taken on ledger charge √ √ √
8 The procurement of goods and services by the administration without adequate √ √
recourse to procurements committees of the various public institutions, which
diverges from the provided regulations.
9 Variations to contract √
10 Outstanding mobilization advances owing to non-observance of stipulated √
regulations
11 Fragmentary procurement √
12 Little evidence of value for money spent √ √ √ √
13 Sourcing of proforma invoices from the same supplier (Single sourcing) √
14 Overpayment of purchases √ √
15 Lack of proper coordination among the major departments of the Company √
and apparent internal control weaknesses reconciliation on Association
16 Lack of consistent monitoring and review of procurement activities √
17 Lack of whole-of-government and corporate procurement planning for √
significant purchases
18 Lack of audit trails or verification data √ √ √

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3.6.1.6 Explicating the Findings on Procurement Irregularities

Table 3.9 provides an overview of financial irregularities recorded by the A-G of Ghana over the last

decade. These irregularities are regarded as the indicators of corruption by Tabish and Jha (2011) and

Le et al., (2014). As recorded in some countries and institutions, the prevalence of these irregularities

is very noticeable in developing countries (Ivanyna and Shah, 2011). Moreover, that has been one of

the most significant impediments to growth as well as infrastructure and other vital developments. The

occurrence of this situation evolves and revolves around these irregularities identified but uncared for.

These practices do not only crop up financial drain in the public sector but tarnish the image of the

economy as well.

Most of the reports stressed out on the issue of public officials ignoring the application of the required

stipulations set by law to rather conduct procurement in a manner that will benefit them. This has been

the peril of not only Ghana but other developing countries such as Nigeria (Alutu, 2007; Alutu and

Udhawuve, 2009), India (Tabish and Jha, 2011), Zambia (Sichombo et al., 2009) and many others.

Another causal factor that enables these incidents to flourish is owed to the anti-corruption agencies

who are not connected to governmental projects to scrutinize the whole procurement process. Since

most of the powers have been vested in the procurement board, top officials of the board may abuse

their powers by manipulating the entire procurement process. This cripple the administration of the

entire procurement process since these are the same officials who top administrative positions.

Moreover, it indicates the vulnerability of the country to corrupt practices and adversely leaves the

whole administrative system flawed. (Doig, 2012; Schatz, 2013; Sööt and Rootalu, 2012).

The audit service of Ghana examines part of their duties and only reports some of these irregularities to

which in most cases. However, nothing is done about it, so they are left to report the same events and

incidents over and over again, and that was identified in the reports. Again, since most of the audit

officials may not be conversant with the procurement process, they are left to report superficial but not

in-depth cases owing to the non-palpability of their mode of examination. Kenny (2009) indicated that

audits performed by professionals with the appropriate expertise or background yields better and quality

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results. Therefore, in this case, it will be apropos for the audit in the procurement sectors be undertaken

by an auditor with a professional procurement background. Uncompleted works are also paid for

without any proper examination of work progress. When culprits are found breaking the regulations

stipulated in the Public Procurement Act (PPA), no equal sanctions are meted out to them. This

encourages young public officials follow the same footprints with the notion that those unethical

practices are the activities of the day and has therefore been mended into the institutional culture of

public offices. Public officials as well purchase items in the name of the government yet unable to

provide full proof of receipt of purchased items, and in most cases, very little evidence of value for

money spent is given. These are all irregularities detailed out in the assessed reports. Lastly, on the

procurement process, identified as part of the irregularities is the absence of proper coordination among

the major members of the departments as well as the apparent weakness of internal control. Probably

the worst of it all but not the most important per the frequency of the irregularities. It is a negative

practice considering the numerous instances of disrespect and disregard for rules by public officials

who have gone through vetting and have acclaimed to hold in high esteem the norms, values, and

regulations of the country. No sanctions are, however, meted out to these culprits; no public

enforcement body makes sure they are brought to disciplinary actions. These are just a few of all the

irregularities and corruption instigators identified among the various procurement units of public

enterprises as addressed by the AG since the last decade.

3.6.1.7 Recommendations by the A-G

In almost all the reports, the A-G suggested that strict adherence to the provisions of the Public

Procurement Act, 2003 (Act 663) to ensure value for money in contract management. This statement

has been persistent in almost all the reports reviewed. As a government challenge, there are many

governments or countries to learn from at the initial stages of dealing with these irregularities such as

Hong Kong, Singapore, Australia, the United Kingdom, etc. These cities and countries have been able

to check these irregularities, which most often appeared as indicators and instigators of corruption, and

pragmatic steps were taken to mitigate their occurrences. For instance, according to studies such as Lo,

(2001), Cheung (2008), De Speville (2010), etc. Hong Kong (HK) was faced with diverse kinds of

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corruption cases, which included some of the irregularities identified in this review. However, practical

measures such as the establishment of the HK ICAC with full autonomy to investigate corrupt cases,

identify the prevailing irregularities, develop a solution, etc. were established in 1974. Decades down

the road until today, Hong Kong is applauded for the massive efforts taken to mitigate corruption. The

same has been done in the geographical locations mentioned above, and according to the studies of De

Speville (2010), Botswana which is regarded as the cleanest country in Africa in terms of TI’s

corruption perception (TI, 2017), adopted the same strategy as HK did. The Directorate on Corruption

and Economic Crime (DCEC) was established in 1994 to deal with the same causal factors identified.

However, before the establishment of the DCEC, Botswana was regarded as one of the most corrupt

countries in the developing world. Adopting the same pragmatic measures, which include investigation,

education, and enforcement, Botswana has been able to check the level of corruption and now regarded

as one of the clean countries in the world. The difficulty encountered here is not with regards to the

adoption, but the processes involved in the adoption of such schemes and frameworks. The fight against

corruption may seem difficult, but it is still possible. Several countries and economies have proven it

with active research, the establishment of anti-corruption bodies, development of strategic anti-

corruption measures, and others to deal with this social canker.

Owing to the identification of these causal measures, better strategic measures can be developed

specifically to deal with these irregularities. Moreover, as Henry (2009); de Jong et al. (2009) asserted,

the fight against corruption should be a collective action of individuals, anti-corruption institutions,

policymakers, etc. except the corrupt and should not be a lone battle left to some few to deal with it. It

is until corruption is checked to a point where it has less influence on the economy that both the

economy and the inhabitants thereof can fully enjoy the nation’s economic resources, active

infrastructure development, and economic growth. Just as NACAP (2011) insinuated, the control of

corruption in Ghana should be the responsibility of each citizen. By this contribution, citizens are

allowed to join hands and tackle corruption in the country to secure and sustain the nation’s

development. The question is, how the populates join hands if they are ignorant of the true meaning of

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what they are going to deal with. From the findings, corruption is rather seen as a more technical,

secretive, and well-calculated menace that may take the expert to identify.

3.6.1.8 Section Summary

This section sought to review the annual audit reports as well as some relevant literature on Ghana to

determine the causal measures behind the irregularities identified in the procurement and contract works

undertaken by the public sectors (also identified as corruption indicators). With the aim of this section

scoping in on the irregularities involved in procurements and contracts, the other areas which include

taxes, loans, payroll and rent need may need to be addressed by other or further studies. The prevention

of public funds misappropriation and irregularities concerning procurement remains one of the most

vital importance to every economy due to the high negative impact on governments. Previous studies,

for example, Doree (2004), Tabish and Jha (2011), Krishnan (2010) reported that to check the

happenings of these irregularities, there is the need for curative measures to be put in place such as

accountability, transparency and reactive measures such as punishments for offenders. However, these

problems cannot be fully tackled when these corrective measures are applied in isolation since these

irregularities occur in different forms and formats.

3.7 Developed Countries 7

3.7.1 The Case of Hong Kong

Unlike the case of most countries in the developing context, notable disparities between the two contexts

show that most countries in the developed countries perform better in the fight against corruption as

compared to the developing countries. In this section, Hong Kong is used as the case study. The past

four to five decades, Hong Kong has been phenomenal regarding the city’s dealings against corrupt

practices (Gong et al., 2015; Moran, 1999). Just like an incurable disease, it is possible to treat

7
This chapter is fully or partially published in the following journal monograph: Owusu, Emmanuel Kingsford,
and Albert PC Chan. "Corruption in Infrastructure Procurement: Addressing the Dynamic Criticalities." (2020).
Taylor and Francis.

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corruption to the barest minimum level but difficult to eliminate. This statement is evident in the

continual assessment of the corruption perception in all the countries in this world (Wong, 2010; Mo,

2001). No country in this world stands perfectly against the happenings of corruption. Even Denmark,

which happens to be the cleanest country in this world according to TI (2017), is not regarded as 100

percent clean because corrupt people will continually exist because of greed, selfishness, and the

lewdness in a person’s heart. Therefore, in as much as there are various formulations and developments

of anti-corruption measures, models, and frameworks, there is the need for psychological and moral

foundations of combatting corruption in every sector of the local government. However, that is not

always the case.

Hong Kong has made bold and pragmatic progressions to dealing with the menace of corruption over

the past 40 years and still moving forward (De Speville, 2010; Quah, 2013). Other countries and

institutions have adapted their strategy as well as their modus operandi in dealing with individual cases,

some are in the pipeline of adopting, and others are yet to adopt (Li, 2004; De Speville, 2010; Gong and

Wang, 2013). This has led to the constant increase in the performance and international rankings over

the years until 2012 to 2015, which recorded a series of decline. Numerous studies conducted on this

subject matter have led to interesting findings, which are discussed later in this section. Since no study

has presently reviewed the overview and characteristics of corruption in the Hong Kong context, this

section presents a thorough examination of corruption in the Hong Kong context.

The findings of this section contribute to a deepened understanding of the dynamics of corruption in

Hong Kong and how emerging economies can learn from. Not only policymakers and anti-corruption

institutions but also law enforcement agencies and researchers in developing strategic measures would

find them useful in dealing with the menace of corruption in our economies. This section serves as an

essential premise for further empirical studies presented later in this study.

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3.7.1.1 Topical Coverage of HK Publications

As noted in the previous sections, the retrieved papers discussed a broad range of topics from both the

private and public domains highlighting on the issues of the control and efforts taken by the Hong Kong

Special Administrative Region (SAR) on the issue of corruption. Other topics cover business and the

rule of law, the ethical concerns, how other institutions and countries can emulate HK in their pragmatic

and consistent efforts. The comparative analysis of HK and other countries and well as HK’s

international corporations, and lastly, the concerns of the populate on the matter of corruption were the

final topics captured in the review. The frequency of these topics over the years is illustrated in Fig.

3.11.

Topical Coverage

Public concerns

International Corporation (ACM)

Emulating Hong Kong

Ethical Concerns

Comparative analysis

Business and Rule of Law

The SAR efforts and control

0 1 2 3 4 5 6 7 8 9 10

Number of publications

Figure 3.10: Topical coverage of corruption-related studies of Hong Kong

Fig. 3.11 depicts the topical indexes of the 44 retrieved papers. Ranging from the least to the most

discussed theme, constitute public concerns and SAR efforts and control respectively. The SAR efforts

and control. It was not a surprising outcome to note SAR efforts and control construct as the topical

area with the highest frequency. Obtaining a total number of ten papers, most scholars seem to have

covered interesting issues on the efforts instigated by the HK SAR to control and maintain a less corrupt

society. For instance, Lo (1999) reported on HK’s experience on minimizing corruption and crime rates

from the years 1950 to the early ’70s, where the condition of the State was a purely autocratic colony

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and a government-driven by business, which looked down on the citizenry. Corrupt activities were

culturally rampant, and the order of the day among senior public officials in the early years, and they

stemmed from Mainland China (Lo, 1999). However, HK began to see a turnaround in the middle ages

of 1970 to the ’90s, which is still in effect until today. The mid ages were the times that the State of HK

was very determined to combat the ‘political-criminal nexus’, and this led to the formation of one of

the most vibrant and effective anti-corruption institutions in the world today known as the Independent

Commission Against Corruption (ICAC). As an absolute independent structure, the ICAC has led HK

to such pragmatic efforts and fight against corruption due to the following characteristics: adoption of

a three-pronged attack approach, which is discussed later in this section; substantial remuneration to

sustain integrity; performance of integrity checks; draconian powers to conduct effective investigations,

etc. (Lo, 1999; Moran, 1999; Lo, 2001). Some major forms of corruption that the ICAC has dealt with

to date include bribery as well as other trans-border crimes, which included counterfeiting, money

laundering, smuggling, and fraud (Moran, 1999). Lastly, per the study of Moran (1999), other variables

that have aided HK’s efforts in the fight and control against corruption lies in the power balance within

the political economy, the rule of law, state’s capacity, etc.

3.7.1.1.1 Business and the Rule of Law

Business and Law as the second leading subject for this review encapsulates not only the corrupt

practices identified under this construct but also the fairness of business transactions and the efficiency

of the legal system in HK. Lee (1995) highlighted that the impartial and efficient legal system of Hong

Kong had been one of the primary drivers for economic success in HK, as well as led to thwarting

corrupt activities in the Special Administrative Region (SAR). Lee’s study drew strong emphasis on the

preservation of HK’s firm foundation of the legal system and how it had been protected from the

Chinese government due to the endemic nature of corruption that was present in China as of that time.

This legacy of the firm support of the rule of law in HK has contributed enormously to what the world

praises HK for. On the premise of business and economic growth, Mo (2001) estimated that a 1% rise

in corrupt practices tends to cause a deficit of 0.72% in a nation’s growth rate. Moreover, political

instability connotes the channel through which corruption can severely attack economic growth. Given

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this background, HK has stood on the grounds to combat any infiltration and determinants of economic

and political instability from other countries, maintaining a competitive business state as well as a State

where the rule of laws applies (Mo, 2001; Lo and Ngan, 2009). Lastly, Lee (2016), identified that

foreign capital could serve as a measure to reduce the incidences of corruption in provincial

governments.

3.7.1.1.2 Ethical Concerns

Ethics, regarded as moral principles that guide the behavior or how a person should conduct himself,

has been one of the principal concerns of HK. Several findings have evolved from the studies conducted

so far. For instance, Ho and Redfern (2010); Snell and Herndon (2000); Donleavy et al. (2008); Scott

and Leung (2012). There have been several developments of ethical codes during the colonial as well

as the post-colonial era (Ho and Redfern, 2010). In the pipeline of attaining independence from the

British in 1997, the people of Hong Kong feared that there was a possibility of the return of corrupt

practices (Snell, 1999). Owing to bribery reports noted in the HK-Mainland cross-border trade, many

were concerned with the achievements of ICAC coming into ruin (Snell, 1999; Donleavy et al., 2008).

To maintain the healthy ethical culture, ICAC organized a conference in 1994 on business ethics and

urged HK companies to adopt ethical codes in their day to day modus operandi and this practice has

been in place to this present day (Snell et al., 1999).

Per the study of Luk (2012), the topic and the concerns of ethical culture have, in recent years, become

more vital in public administration and the government of HK is no exception. However, due to the

pragmatic efforts in maintaining an ethical society, HK has been internationally recognized as one of

the least bureaucratic and corrupt governments in the world, although they still face some challenges.

HKSAR adopts a four-way approach in developing ethical practices in the civil service according to the

study of Luk (2012), and they include prevention, education, sanction and lastly, help from government

departments and other agencies. The Public Service (PS) (Administration) Order, as well as the PS

Disciplinary Regulation, provide a very firm and strong disciplinary action in the case of serious

misbehaviors committed by officers. Although HK enjoys a serene ethical atmosphere, it also faces

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challenges such as, the ethical dilemma (when a person finds it difficult to adjust to organizational ethics

due to family background, educational factors, and religious beliefs), the conversion of ethical norms

(abstract values) into ethical actions (practical actions), the ineffectiveness of some moral mechanisms

etc. (Donleavy, et al., 2008; Ho and Redfern, 2010; Scott and Leung, 2012). All these problems need to

be empirically addressed in detail to enhance the ethical culture of HK.

3.7.1.1.3 Emulating Hong Kong

As a model city that has proven beyond all reasonable doubt that corruption can strategically be dealt

with, HK has become one of the cities in the world whose strategies are worth adopting, whether for

organizations or governments. However, the question raised here is, is it possible to be adopted by every

state or country, institution, etc.? Quite a number of literature has dealt with this issue (de Speville,

2010; Cheung, 2008). Per the review conducted, emulating HK construct happens to be the 5th most

discussed topic. Although the strategies of HK are worth adopting, what are some of the streamlined

processes and paths to be followed? Most of these papers explicated how China could adopt HK’s

effective model in eliminating corruption (Cheung, 2008; Mao, 2013; Hira, 2016).

Mao et al. (2010) assessed the generalizability of HK’s ICAC strategy in the Chinese context. Countries

such as Botswana and Madagascar have adopted ICAC’s strategies in fighting corruption and have

made significant progress (de Speville, 2010). For instance, the Directorate on Corruption and

Economic Crime (DCEC) of Botswana formulated their anti-corruption model by adapting that of ICAC

with some adjustments, and they remain the cleanest country in Africa and forms part of the top 25%

most decent countries in the world regarding corruption (TI, 2017). There have been several scholarly

objections to the replication of HK’s solution in other countries, such as the uniqueness of corruption

cases in the context of Hong Kong and the high cost involved in the establishment and maintenance of

an anti-corruption institution. Others include the intensity of the remedial measures adopted by ICAC

is described to be dangerous to be applied in another place; and lastly, the frontal attack on the notion

of establishing an anti-corruption institution as a medium of fighting corruption. De Speville (2010),

however, concluded that the answer to these objections lies in policy and governance reform. This was

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what happened in the case of Botswana to make it what it is today. Some of the measures that can be

adopted include an explicit, logical and a comprehensive strategy by a well-established anti-corruption

body, skilled and trustworthy personnel, community involvement, confidentiality, protective listening,

prevention, and education, investigating and disposing of complaints and lastly measuring progress (de

Speville, 2010; Li, 2004; Cheung, 2008; Gong and Wang, 2013; Mao et al., 2013; Hira, 2016).

3.7.1.1.4 Comparative analysis

Corruption measurements and comparisons are regarded necessary since it encourages fewer

performing countries or institutions to march up to good or appreciable standards in fighting corruption.

Comparatively, HK ranks 15th in the 2016 global perception index and second after Singapore in Asia

(TI, 2017). This is explicated further in one of the succeeding sections called ‘Hong Kong’s standing

on the global context.' A total number of five different papers dealt with the subject of HK’s

performance against other countries in the world, most especially the countries in Asia (Kim, 2003; Lin

and Yu, 2014; Gong et al., 2015; Warf, 2016). The most mentioned comparative analysis of countries'

performance with regards to corruption measurement is the Corruption Perception Index (CPI) by

Transparency International. Other notable measurement techniques for conducting comparative

analysis are discussed later in this section.

3.7.1.1.5 International Corporation

The belief in international corporations has added enormous positive influence in HK’s fight against

corruption over the past decades. Bishop (1997), highlighted the significance of international

corporation and liaison as a firm approach to surpass jurisdictional blockades in the fight against corrupt

practices and associated criminal acts. As the former assistant operations director of ICAC, Bishop

(1997) indicated that HK’s ICAC was privileged to have established very profound and positive

professional relations with law enforcement institutions that were outside the boundaries of HK. Such

institutions included the Malaysian Anti-Corruption Agency, the Corrupt Practices Investigation

Bureau of Singapore, the Macau Judiciary Police and High Commission Against Corruption, the

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Federal Bureau of Investigation, the Australian Federal Police, the Royal Mounted Canadian Police,

among many others. The list may go on and on, but this clearly shows that the fight against corruption

may need more than just one hand, and HK, seeing the need to uproot the socio-economic menace from

the SAR, had to cross the hurdle to liaising with other countries and agencies (Marquette, 2007; Quah,

2013). Even though, there was a forecast of some of the possible constraints or challenges that could

have cropped up such as bureaucracy, incompatible and divergent national legislation, etc. HK was

ready to pay any price to thwart and finally annihilate the root causal instigators of corruption. The

team-up spirit showcased by HK has proven to be one of the active drivers of anti-corruption measures

adopted by HK (Holmes, 2015).

3.7.1.1.6 Public concerns

Public trust in institutional organizations as well as governmental organizations is very vital to the

effective application of anti-corruption measures and also promotes the willingness of the general

populates to drive their support on issues concerning corruption when needed (Fard and Roastamy,

2007). The concerns of the general public on the issue of corruption should, therefore not be taken for

granted. For instance, one negative outcome reported by Weng et al. (2015) on the issue of public trust

indicated that there was a strident decline in the trust of about 2100 HK residents in the Chinese

government with the notion on the prevalence of corruption. This led to a shortfall in their willingness

to donate to support victims of earthquake disasters in China. Inasmuch as HK is believed to be making

continual and pragmatic progress in the fight against corruption, there are occasions when their

trustworthiness is questioned by the public sometimes.

However, the positive implications attached to is the demand for accountability from the ICAC to stand

in a position to give fair accounts of their day to day activities. For the ICAC to win the trust of the

entire HK populates, there is also the need to hold firm integrity. As recorded by De Speville (2010),

sometimes, the lack of trust on the side of the public may have some very negative implications on the

reliability of information that would be given by a person during investigations. However, on the other

hand, once the general public develops a sense of trust, such as confidentiality of data of persons who

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report corrupt cases, some barriers of effective anti-corruption measures such as fear of being noted as

a reporter can be eliminated. This will add on to the smooth running of the ICAC (Fard and Roastamy,

2007; Speville 2010).

3.7.1.2 Extracts from the ICAC Reports

The ICAC was formulated at the time when corruption in HK was incredibly pervasive, coupled with

legitimacy and moral crisis as a result of the incidences of corruption (Bishop, 1997; Cheung, 2008).

With the adoption of a very comprehensive and pragmatic three-pronged approach, namely, prevention,

enforcement and education, the ICAC has been categorized as not only one of the top anti-corruption

institutions in the world but also a very successful tool against the menace of corruption and dishonest

governance. The focus of information extracted from the ICAC reports was restricted to the complaint

reports made over the past decade as well as the individuals cautioned and prosecuted over the past ten

years.

These three sections were selected based on the following justifications: to find out whether the internal

records by the ICAC have any reflection on HK’s global ranking. From Fig. 3.12, it is revealed that the

year 2000 to 2003 recorded the maximum number of documented cases over the past decade with the

last three years (2013-2015) recording the least number of complaints although the decline began from

2012. Similarly, the years 1999 to 2002 in Fig. 3.13 recorded the highest number of individuals

prosecuted over the years, although the year range for the highest number of cautions is recorded from

2002 to 2004. However, the least reported number of both cautioned and prosecuted persons are also

recorded in 2012 to 2015, just as in the case of the total number of complaints received by the ICAC.

Although a typical relationship that can be drawn here is that the number of complaints has a direct

correlation with the total number of cautioned and prosecuted persons. This hypothesis can be

empirically tested in the future. The issue of concern raised in this section is that, does the reduction in

the number of complaints as well as the total records of both cautioned and prosecuted persons simply

reflect that there is also a decline in corrupt practices? In order words, is there a direct relationship

between the number the recordings of the total number of complaints, cautions and positions and the

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performance of HK in the international ranking? The discussion section explicates this notion after a

thorough assessment of HK’s performance in the global rankings.

3.7.1.3 Reported cases over the last two decades

The graph above depicts the number of complaints recorded by the Independent Commission Against

Corruption (ICAC) of Hong Kong over the last two decades. After the construction of the Hong Kong

Airport in 1998, Hong Kong, though regarded as a clean country regarding corruption incidence, yet

recorded its high level of complaints from 2000 to 2003, a few years just after the construction of the

airport. Afterward, there are still many reported cases that prove the incidence of corruption in Hong

Kong. Also, although the chapter intends to adopt the lessons from Hong Kong to better the systems of

developing countries since they are still trotting their way through corruption, yet, it is expedient that

the state of corruption in Hong Kong is readdressed and strategic measures to curtail its incidence be

rechecked. This chapter is as well placed in that line to fill the gap, although it would be tailored to the

proneness of the stages of procurement to corruption.

Table 3.7: Statistics on corruption in Hong Kong for the past 2 decades

Complaints, Cautions and Prosecutions Cases Global Performances of HK

Year Individuals Individuals Number of Yr CPI TI WGI WEF

Cautioned Prosecuted complaints
20

1996 3086
1997 59 315 3057
1998 64 382 3555
1999 81 504 3561
2000 94 608 4390
2001 85 535 4476
2002 116 604 4371
2003 113 421 4310
2004 132 494 3746
2005 51 356 3685

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2006 45 341 3339 06 86 94 80

2007 49 353 3600 07 83 94 83
2008 54 357 3377 08 81 94 83
2009 54 342 3450 09 82 94 83
2010 30 393 3427 10 84 95 81
2011 54 283 3868 11 84 94 82
2012 27 245 3731 12 77 93 84
2013 28 220 2515 13 75 92 84
2014 26 223 2237 14 74 92 82.3
2015 35 213 2595 15 75 92 75
2016 16 77 74

5000
4500
4000
3500
3000
Axis Title

2500
2000
1500
1000
500
No. of complaints
0

Year

Figure 3.11: Number of complaints recorded by ICAC from 1996-2015

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700 Individuals Cautioned

Individuals Prosecuted
Linear (Individuals Cautioned)
600 Linear (Individuals Prosecuted)

500
Axis Title

400

300

200

100

Year

Figure 3.12: Individuals Cautioned and Individuals Prosecuted recorded by ICAC from 1997-2015

3.7.1.4 Hong Kong’s Integrity and Performance in the Global Context

Integrity refers to the qualification of having very high moral principles that reflect in one’s sense of

honesty and good ethical standards. It is, therefore, a choice of holding oneself to consistent ethical or

moral standards (Cambridge, 2017). This quality is essential for governments because it determines the

level of trust the citizens, as well as foreign donors and investors, can put in the state. Moreover,

according to WEF (2017), one of the units of measurement for a government’s integrity is the level of

corruption prevalent within the government or its public sector. There are several institutions with

various tools to measure the perception of corruption prevalence in countries worldwide. However, to

assess the performance and HK’s government’s integrity by an unbiased and fair judgment, this section

limited the number of institutions for assessing corruption indexes to three, namely, Transparency

International, the World Bank, and World Economic Forum. Transparency International is noted for the

assessment and the rankings of the countries in the world in terms of corruption perception. The World

Bank assesses the control of corruption of individual countries, which form a part of the six worldwide

governance indicators, and lastly, the World Economic Forum investigates the integrity of the

governments worldwide, which as well forms a part of the Economic Freedom Index of countries. These

three assessment tools were identified to evaluate the standing of corruption on the global scene.

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CP I o f Ho ng Ko ng
120

100

80

60

40

20

0
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Hong Kong 86 83 81 82 84 84 77 75 74 75 77
Bechmark 100 100 100 100 100 100 100 100 100 100 100
Passmark 50 50 50 50 50 50 50 50 50 50 50

Figure 3.13: Corruption Perception Index (CPI) of Hong Kong

Source: Transparency International (2017)

WGI on Corruption Control

95.5
95
94.5
94
Hong Kong

93.5
93
92.5
92
91.5
91
90.5
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Hong Kong 94 94 94 94 95 94 93 92 92 92

Figure 3.14: Worldwide Governance Indicators, (WGI) on Corruption Control

Source: World Bank (2017)

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WEF, (Government Integrity)

86
84
82
Hong Kong

80
78
76
74
72
70
68
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Hong Kong 80 83 83 83 81 82 84 84 82.3 75 74

Figure 3.15: Global Competitiveness Index on Government Integrity (2017)

Source: World Economic Forum

Fig. 3.14 illustrates the data collated from Transparency International over the last decade.

Transparency International evaluates the perception of corruption of countries using a 10-point scale.

The range of the figures from 0 indicates an extreme prevalence of corruption within a government, to

10, which indicates either a clean state or a small indication of corrupt activities. In stipulating the marks

for each country, there is a conversion of the points of the CPI raw data into a scale of 0 to 100 by

multiplying the scores of the CPI by 10. Therefore, a country with a raw score of 5.5 for a particular

will attain an overall score of corruption freedom score of 55. However, considering n both extremities,

no country is either achieved a total point of 10 or the least point of 0. Fig. 3.14 represents the CPI

scores of corruption from 2006 to 2016. HK has been doing quite well within TI’s ranking for the past

decade. The reason being that the SAR has never crossed the threshold of 50, which indicates a sign of

weak or poor performance. With a current score of 77, it is justified that HK was better ten years ago

than it is now. From the year 2006 to 2011, HK CPI’s ranged within the ’80s, but there has been a

reduction in the last five years. Although the performance is not bad, the issue generated here is, what

led to the decline, and what pragmatic measures are being taken to resolve the declination?

Fig. 3.15 and 3.16 above illustrate the rankings of Hong Kong by the World Bank and the World

Economic Forum, respectively. World Bank’s assessment is conducted regarding the government’s

control over the incidence of corruption, whereas WEF, measures the integrity of the government. In

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all cases, the maximum threshold is 100. However, one interesting finding that was observed in both

data, as well as that of TI's CPI, was the decline in all the scores from the year 2012 to 2016. In other

words, the performance of HK over the past decade had been magnificent until the year 2012, when

they started measuring a declination in all their performance on corruption control. One effectual

recommendation that can be made here is a thorough throwback investigation of the causal instigators

and the risk factors that led to the decline from 2012 to 2015 to measure the standards that HK enjoyed

up to the year 2011. However, despite the observed shortfall recorded from 2012, HK’s performance

has comparatively been outstanding over the years since the establishment of ICAC. This is because,

although HK is regarded as a Special Administrative Region, it still forms a part of China, which is

ranked very low in the international scene.

For instance, the TI’s CPI ranks China 79 with a score of 4, which is below the pass mark and regarded

as not a clean country by the definition of the CPI. This section highlights the performance of HK over

the past years, and it is observed that the top anti-corruption institutions in the world today ranks HK

as one of the clean cities in the world that other corrupt governments or countries can look up to as an

exemplary model to learn from. This is especially applicable to corrupt developing countries looking at

the history of corruption in HK.

3.7.1.5 The Way Forward for HK

The data representing HK’s performance on the global scene indicated a fall in performance over the

last four years, that is, commencing from somewhere around 2011 and 2012. Comparatively, HK’s

performance in the control of corruption has dropped during the final quarter of the entire decade as

opposed to the early parts of the decade. Also, comparing Fig. 3.12 and 3.13 which represent the total

complaints cases, and the total estimates of cautioned and prosecuted cases from the ICAC report

respectively, it is identified or realized that the number of complaints begun to drop from 2012, the

same year that HK’s performance in the global assessment also dropped to its lowest point (in that

decade). Moreover, an analogy is drawn on the total estimates of individuals cautioned as well as those

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prosecuted. The least of all the total estimates chronicled over the entire decade was recorded in 2012,

although the total number of individuals prosecuted hit the range of 200 was in 2011.

In a logical reasoning spectrum, it may be argued out that the low records of the total estimates of both

individuals cautioned and prosecuted would have indicated that the control of corruption in HK is on

the rise since fewer people are being cautioned and prosecuted as compared to the previous years.

However, the opposite was the case, in these years that HK recorded the least or declined numbers in

the total complaints, persons cautioned and prosecuted, those were the same years that their

performance on the international rankings dropped. What could be the possible indicators of this drop?

Could it be possible that there was a possibility of a decline in the trust in ICAC by the HK populates

that resulted in the decline in the level of complaints, or there could be other possible causal instigators?

These are key issues arising from the comparisons of both the ICAC reports and current literature that

need further investigation to be addressed to cause the needed improvements in corruption control in

HK.

Moreover, although HK’s ICAC is regarded as a success model, the possible reduction in the total

number of complaints, persons cautioned, and prosecuted do not necessarily indicate a reduction in

corruption. On the other hand, the opposite might even be the case, which this section has explicitly

delineated. This could set as one of the shortfalls or possible unidentified challenges to the fight against

corruption or the control of corruption in HK, which needs a thorough investigative study to explicitly

demarcate the possible factors that led to the fall or reduction in the performance.

However, it is no doubt that HK’s strategy to combat corruption remains as one of the top ideal solutions

in the world today, and the ICAC also serves as an excellent exemplary for successful combat and

reduction in corrupt practices. With the constant enforcement of the three-pronged approach, corruption

has reduced drastically in HK now as compared to over a century ago. Countries such as Australia,

Singapore, Botswana, Madagascar, and many others have benefited from this strategy adopted by HK

over the years. This is proven in the number of recorded number of visitors to the ICAC every year. For

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instance, the ICAC had a total number of 4210 visits from 53 different countries in the world and 11

regional and international organizations, including the World Bank (ICAC, 2015). In the case of

Botswana, their testimony explicates that emerging economies can adopt this approach in the fight

against corruption.

Lastly, even though there will be a need for the establishment of independent anti-corruption bodies

just as in the case of HK when the need arises in many countries having no such institutions. Any

country without such body but is determined to obviate corruption in the public sector may follow the

footprint of HK with the motive of establishing an independent anti-corruption agency with the

necessary expertise to run it effectively. It is believed that there would be possible challenges such as

inadequate capital to commence the project, unnecessary bureaucratic challenges as well as other

possible problems. This successful model that has been effectively adopted by Botswana and other

countries can as well be adopted by other emerging economies with the notion that the latter rewards or

benefits will always outweigh the initial challenges of adopting such an approach.

3.7.1.6 Section Summary

Corruption, since time memorial, has been the number one enemy and hindrance to socio-economic

development in every part of the world we live in today, ranging from governments to public and private

institutions. However, HK’s experience has proven that the menace of corruption, in general, can be

efficaciously tackled. This section sought to conduct a thorough review of the overview of corruption

in the context of HK. After conducting an extensive literature search using a powerful academic search

engine called Scopus, 44 valid related documents were retrieved. Another search was conducted to

retrieve all the ICAC reports as well from 1974, and a total of 43 reports were retrieved, making a total

of 87 documents that formed the main database for this review. This review was conducted regarding

the topical coverage over the years, HK’s performance in global rankings, facts from the ICAC reports,

which include the number of complaints cases over the past decade as well as the total number of

persons cautioned and prosecuted. The most discussed subject matters were in the area of the SAR

efforts and control, Business and Rule of Law, Ethical Concerns, Emulating Hong Kong, Comparative

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Analysis, International Corporation, and Public concerns. Moreover, it was interesting to find out that

the reductions in the total number of complaints, cautions, and prosecutions do not necessarily reflect

the improvement improvements in corruption control and, in this review, the opposite was rather the

case.

The three years (2012-2015) that recorded the least number of the complaints cautions and prosecutions

were the same years that HK performed very low in the international rankings. Also, as suggested, there

is a need for empirical research to investigate the causal measures of the decline in performance and the

possible causes of the complaints over the past stipulated years. This will help improve the HK’s

performance in the control of corruption. However, the success model of ICAC was highlighted,

indicating the possibility of other countries, most specifically the emerging economies to adapt their

strategy in the fight against corruption since this approach has yielded positive results in Botswana and

other countries. Hong Kong is therefore advised to keep up with the momentum to constantly battle

down the peril of corruption since other countries continue to look up to them. As an extension on the

topic of corruption, this section contributes to a deepened understanding of the dynamics of corruption

in the context of HK. It would be useful for not only policymakers and anti-corruption institutions but

also law enforcement agencies and researchers in developing strategic measures to deal with the

prevalent peril of corruption in both developed and emerging economies. It also stipulates how to

strategically adapt the footsteps of Hong Kong’s efforts in dealing with corrupt practices. With this,

corruption will not only be thwarted in HK or Asia but also the entire world.

3.8 Chapter Summary

This chapter concluded a thorough contemporary review of the various constructs of corruption

explored under the topic of corruption within the larger scope of construction engineering and

management. Thus, the pressing issues within the sector and the associated activities were reviewed to

determine the extant indicators contributing to the incidence and proliferation of corruption within the

sector and associated activities. Particularly regarding the procurement process of infrastructure works.

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As a result, constructs such as the forms of corruption, causal factors, risk indicators and the

vulnerability of the procurement process to corruption were reviewed. Moreover, the measures

stipulated overtime to check and extirpate the criticalities of the negative constructs were reviewed. A

further search was conducted to determine the factors that impede the effectiveness of these measures.

Lastly, the implications of the various constructs of corruption within the regional settings, particularly

the geographical focus of this study (i.e., Ghana and Hong Kong) were reviewed at this-stage. The

variable and indicators obtained from the constructs and the geographical contexts represented the

foundational indicators for further empirical examination.

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CHAPTER 4 – CONCEPTUAL FRAMEWORK DEVELOPMENT8

4.1 Introduction

Literature is not consistent with the etymology of corruption, for instance, while Hogdson and Jiang

(2007) attributes the root of the word "corruption" to the Latin adjective ‘corruptus,’ which means

destroyed, broken or spoiled, Johnson (1996) also attributes its derivation from the Latin word

‘corruptio’ which signifies a wicked behavior, putridity or moral decay. However, in all instances, one

commonality that exists between the two views, moral decadence, is evident in the industry today

(Henry, 2009; Sohail and Cavill, 2008; Bowen et al., 2012; Shan et al., 2015). Jain (2001) purported

that corruption has many definitions across diverse contexts, but per the suitability of this context, that

is the construction industry, corruption is deemed to be the abuse of entrusted power and construction

project resources for personal gain (Le et al., 2014). Corruption, which may occur in varying forms as

mentioned and can as well transpire in any construction activity and at any phase of the construction

process, that is, from conception to completion (Tabish and Jha, 2011; Boyd and Padilla, 2009;

Stansbury, 2005; FIDIC, 2016).

In the procurement of construction works, FIDIC (2016) opined that corruption might occur in many

instances such as decision-making on claims, payment certificate issuance to contractors, construction

supervision, in tender evaluation, etc. The stages involved in the IP process are, therefore, exposed to

these corruption forms and other examples of corrupt practices due to the causal factors identified in

this section. Although certain stages of the construction process are deemed to be more prone to

corruption than others, no empirical studies show the stage of the construction process that records high

frequency of corruption cases. However, some corrupt practices peculiar to different stages of the

construction process that have been captured in literature over the years have been encapsulated together

to develop Fig. 4.1. Fig. 4.1, therefore, demonstrate some corrupt practices that have been reported in

8
This chapter is fully or partially published in the following journal article: Owusu E. K Chan A. P. C. and
Darko A (2018). Owusu, E. K., Chan, A. P., & Darko, A. (2019). Thematic Overview of Corruption in
Infrastructure Procurement Process. ASCE Journal of Infrastructure Systems, 25(2), 02519001.

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studies (corruption research in construction) over the years. It illustrates the framework for corrupt

practices, formulated for easy identification of the likely incidences of corrupt acts that may transpire

during the project process. Fig. 4.1 was developed from adaptations of the frameworks developed by

Sohail and Cavill (2008); Zou (2006); Stansbury and Stansbury (2008); Bowen et al. (2007; 2012);

Tabish and Jha (2011); Shan et al. (2016), as well as the findings identified by the publications selected

for this review. Most of these studies may mention either one or multiple corrupt practices with their

associated actors and the stage of the construction process where the identified acts are likely to occur.

Therefore, after a thorough assessment of the identified acts, the framework was developed to highlight

some possible acts of corruption in the construction process. Although the acts identified in each stage

are not exhaustive, the framework was developed to inform industry practitioners, policymakers, anti-

corruption institutions as well as researchers about the probable examples of corrupt activities identified

in construction processes over the years and the need to avoid them.

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Figure 4.1: Corrupt practices framework (Adapted from various literature)

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4.2 The Procurement Process

Many public and private enterprises globally regard corruption in IP as an inescapable fact of life. As

pointed earlier, this is not uncommon in the developing countries as corruption adversely influences the

day-to-day modus operandi of the procurement of infrastructure projects, goods, and services. From all

the deductions made so far, corruption in this context can be defined as the abuse of position, regulatory,

legal or political leverage to extract extra costs allocated to the procurement of infrastructural projects.

In this event, the project financier or developer may never recoup the loss incurred, and the perpetrators

mostly deny their involvement thereof (Wang et al., 1999; Shan et al., 2016). According to the World

Bank (2003), corruption has been one of the utmost barriers to socio-economic development, which

does not only result in misappropriation of resources but also, loss of lives and properties (Lewis, 2003).

Corruption destabilizes development by weakening the economic foundations of institutions and

distorting the rule of law (Tabish and Jha, 2011).

In public projects, some of the widely identified adverse effects of corruption include the execution of

substandard construction works and the distortion of the entire procurement process. Corruption does

not only reduce the life spans any infrastructure by 50% or more (Kenny, 2012) but also worsens both

cost and time performance, and the benefits delivered (Locatelli et al., 2017). This is often due to the

criticality, fragility, and vulnerability of the entire procurement process to corrupt behaviors. Bower

(2003) also indicated that a construction project is an intricate process organized through different links

and integrates the interests of many stakeholders to achieve a built facility, possibly at the best price,

highest quality, and within the best specified time frame. Procurement constitutes a very vital

component of realizing every construction project. According to Clough et al. (2000) and Martins

(2009), procurement includes purchasing, sourcing, and every other activity connected to providing

supplies, materials, equipment, workforce, knowledge, management services, and supervision to

accomplish stipulated objectives of an infrastructural project. Procurement usually connects a highly

fragmented supply side, typically professionals in the construction industry, which include contractors,

architects, engineers, suppliers, surveyors, laborers, and builders to a less fragmented demand side

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which includes clients, project representatives, owners and financiers. Bower (2003) highlighted that

since every construction project goes through a procurement phase, there is a high potential for

procurement as a practice to influence project management in a positive direction. Likewise, a possible

flaw in procurement can create an adverse effect on project management. The susceptibility of any

procurement phase to corruption exposes an entire project to the risk and awful impacts of corruption.

There is, therefore, a need to critically and empirically access the vulnerabilities and other associated

risks the procurement process faces regarding corruption.

Over the past two decades, there has been a growing interest in corruption research in IP, contributing

immensely to the increase in the body of knowledge in this subject area. However, there is an absence

of a unified view and a systematic review of research studies dedicated to IP over the years, which is

essential for further studies. This chapter, therefore, aims to conduct a systematic and holistic review of

corrupt practices in IP processes. Moreover, this chapter presents a conceptual framework of a dynamic

model for assessing corruption in IP process and is formulated to serve as a valuable reference for

industrial practitioners and researchers interested in corruption and how to deal with it in IP.

4.2.1 Understanding the Systems, Policies, and Processes in IP

Procurement is defined as an act of purchasing or obtaining goods, works, or services at the best ‘value-

for-money’ rate (Love et al., 1998). Procurement systems, on the other hand, are best described as the

organizational systems that delegate responsibilities and powers to individuals and firms and explicitly

outline all the possible elements in the construction of an infrastructure or a project (Love et al., 1998;

Liu and Wilkinson, 2011). According to Ogunlana (1999), the procurement systems regulate labor

division among the experts or parties involved and controls the modus operandi of all the processes

along with associated rules and the contractual relations. The primary considerations for any

procurement system include the condition of contract, project delivery method, and the price formation

method (Eriksson and Westerberg, 2011; Sutt, 2011). To ensure the success of a building project, one

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of the primary factors to put right is the construction delivery method or system to be adopted (Bennett

and Grice 1990; Chan 2000).

The selection of an apropos procurement system is, therefore regarded as a very vital step in the process

of any construction project. Construction managers or project owners are, however, duty-bound to

determine a suitable procurement system right after the objectives and goals of the project are

determined. Moreover, the person responsible for the determination of the listed criteria should do so

as per the specific needs of the project and the project’s participants' abilities to tolerate risks (Sutt

2011). An independent advisor can be selected to help a client or a project’s financier identify any

potential risks or vulnerabilities associated with the procurement process. Also, in drawing up measures

to check or control any possible procurement risk, there is a need for the procurement entity to develop

suitable and comprehensive risk-mitigating plans that encapsulate measures to deal with any possible

occurrence of corruption at any stage of the IP process (Tabish and Jha, 2011). If a client makes a wrong

choice, the penalty incurred may be time and cost overruns, project’s quality may be compromised and

a possibility of general dissatisfaction to the client (Lædre et al. 2006).

Even though studies have shown that the wrong choice a procurement system for a project may cause

a serious adverse effect on the project, another adverse situation that hinders the success of efficient

delivery of a project is corruption at any stage of the procurement process. The procurement method

selected for a specific project will, therefore, have a direct influence on the stipulated project objectives

and also the level of integration that will exist among the project team members. Other influencing

variables include the nature of the project, client’s resources, the ability to make changes, and other

external factors such as potential changes in interest rates, changes in legislation, and so on. The systems

of procurement that are frequently mentioned and adopted include fixed-price contracting (lump sum

contracting), design and construct, construction management, and on-call contracting. Others include

guaranteed maximum price, full-cost reimbursable, total package options, partnering, public-private

partnerships (PPP), performance-based contracting, and force account. Table 4.1 summarizes and

briefly describes these procurement systems.

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Table 4.1: Procurement systems at a glance

Procurement Description Selection of Construction Party in References
Method contractor supervision charge of
Design
Fixed Price FPC is a TP system that is composed of separate or distinct phases of Open tendering, Architect Client/ (Mearig 2004;
Contracting development of design, tendering stage, awarding of contract, and different selective Owner Touran et al.
(FCP) delivery phase of a construction project. tendering 2008).
Design and In DC, the contractor remains the party responsible for designing and Negotiation Contractor Contractor (Chan
Construct (DC) constructing a project as opposed TP system where the clients appoint a et al. 2002)
consulting team to design the project and a separate contractor to build. In
DC, the client is given the setting a single medium of duty to manage the
entire project with only one point of contact, who is the contractor.
Construction In CM system, works are carried out by different sects of trades or Competition or Construction Client/ (Walker and
Management subcontractors who have direct contracts with the client but are managed Negotiations for Manager Owner Hampson
(CM) by a design contractor who is often called the construction manager (CMr). both direct and 2008; Donohoe
The CMr performs the duties of a consultant to the client and advice the Agency CM and Brooks
client on cost control, construction planning, constructability, coordination, 2007)
and supervision of parties involved in CM.
On-Call Under the OCC system, the project is divided into what is termed as task Negotiation Project Contractor (Walker and
Contracting orders (TO) after the client enters into a contract with a consultant. This is Manager or Hampson
(OCC) usually considered as a master contract and the client issues out the trade owner 2008);
orders to the consultant at different phases of the project.
Guaranteed With the GMP system, there is an agreement established between the client Negotiation Contractor Contractor (Walker and
Maximum Price and the contractor stipulating that the contract sum will not exceed the Hampson
(GMP) capped price established. This system protects the client in a manner that, 2008;
if the contractor exceeds the maximum price agreed upon as the contract Ruparathna
price, the contractor must bear the additional or incurred cost. and Hewage
2013)
Full-Cost In FCR system, the contractor is repaid the definite amount incurred in No competition Contractor or Contractor (Ruparathna
Reimbursable carrying out the construction works, including any additional amount or Architect or and Hewage
(FCR) fee. Also, the client is permitted to retain control over both the design and Owner 2013; Walker

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the construction phases. This system is usually suggested where the design and Hampson
specifications are unknown or keep changing. 2008)
Total Package With the TPO system, an external party enters into a contract agreement Open tendering Contractor Contractor (Walker and
Options (TPO) complete the project and later transfer it built facility or project to the Selective Hampson
client. The external contracted party is therefore responsible for to tendering 2008)
designing, constructing, operating the facility and finally transfers it after
the period specified in the contract.
Partnering Partnership as a procurement system is a very well-organized management Negotiation Contractor or Contractor (Liu and
approach that delivers a win-win outcome for every contributing party of Architect or Wilkinson
the construction team. It does so by enabling teamwork, client or customer Owner 2011; Cox and
focus, mutual objectives, open culture, innovation, long-term commitment, Townsend
and trust. 1998)
Public-Private Under the PPP system, the government or public sector enters into a Negotiation Contractor or Contractor (Oyegoke et al.
Partnerships contractual agreement known as a partnership with the private sector to Architect or 2009)
(PPP) provide infrastructural services. This is usually propelled by the challenges Owner
most governments or the public sector faces such as lack of capital or poor
financial standings and lack of expertise and also the lack of life cycle
property management consideration.
Performance- PBC is regarded as an outcome-oriented contract system rather than a route Negotiation Contractor Contractor (Ruparathna
Based of getting a facility or a project realized. This system characterizes on the and Hewage
Contracting results, quality, output that may be knotted to at least part of the 2013).
(PBC) contractor’s payment, contract renewals and extensions to the realization of
precise, quantifiable performance requirements and standards.
Force Account The FA system is also not regarded as a procurement method but rather No competition Client/ Client/ World Bank,
methods of carrying out works. This method is adopted in public owner owner 2011).
construction works when the project is financed by organizations such as
International Fund for Agricultural Development, International Monetary
Fund, the World Bank, and others alike. Therefore, the equipment and
personnel used belong to the procuring entity.

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4.2.2 The Procurement Process

Different procurement systems may constitute different processes. However, the common ones linked

with IP begins with the determination of what to purchase and end ends with the confirmation that the

procured item or the final product received, whether goods, works or services comply with the stipulated

specifications (ISO, 2008; Ruparathna and Hewage, 2013). The primary consideration of every

procurement system and process constitute the method of price formation, the conditions of contract,

and the delivery method to adopted (Eriksson and Westerberg, 2011). Construction managers or project

owners are, therefore, pushed to decide on the type of procurement system to adopt right after

determining the project’s aims and objectives (Sutt, 2011). According to Lædre et al. (2006), the failure

to select a suitable IP system may lead to adverse consequences of the entire IP process such as time

and cost overruns and poor standards in terms of project’s quality. In the course of strategizing an IP

process, focus should not only be directed to the functional aspects of the process such as performance,

conditions of contracts, law, client and the contract strategy but also external factors such as motivation,

satisfaction, leadership, learning, political environment, sustainability and culture (Rowlinson and

McDermott, 1998). The basic activities that define each stage of the IP process are presented in Fig.

4.2.

Figure 4.2: The IP Process

(Adapted from Lester, 2007; Ruparathna and Hewage, 2014)

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4.2.3 Procedures and Policies

Whereas procurement systems outline the possible organizational structures for carrying out

procurement, procurement procedures, and policies provide the premises for selecting a suitable

contractor to support or carry out the ideal and chosen procurement system. The policies are usually

shaped by client organization values (ISO, 2008). Procurement policies are thematized under three main

constructs, according to Touran et al. (2008). They are value-based procurement, qualification-based,

and low bid procurement. While the primary causes of procurement issues are attributed to low-bid

procurement, procuring units are consequently pursuing value-based and qualification-based

procurement policies. Governments usually aim to achieve the best value or value for money (Langdon

and Everest, 2004; European Commission, 2011). However, due to corruption, this objective is

normally difficult to achieve, although this argument cannot be generalized. Value for money in IP

refers to the realization of the best and ideal amalgamation quality and full life cost to achieve the

demands or needs of the customer. The different types of procurement procedures with their respective

descriptions are illustrated in Fig. 4.3.

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Figure 4.3: Procurement Procedures

(Adapted from ISO 2008; Ruparathna and Hewage, 2014)

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Conventionally speaking, it has been identified that none of the IP stages is immune to corrupt practices

(TI, 2005). The complexity of the procurement process in the pre-contract, contract, and post-contract

phase makes it vulnerable to corruption practices (Heggstad et al., 2010). For instance, during pre-

qualification and tendering phases, it is possible for the client representatives to either bend or amend

procurement rules to favor preferred tenderers in exchange for bribes (Osei-Tutu et al., 2010).

Inescapably, the process of rewarding a contract can also be highly influenced by the power relations

of both economic and political organizations whose aim is to maintain the existing state of affairs

(Sargiacomo et al., 2015, World Bank, 2013 Neupane et al., 2012). Other forms and examples of corrupt

practices are reported in chapter three.

The impact of corruption on the procurement process has been deterring and derailing. Corruption

researchers have identified some negative impacts of this menace that impair the entire procurement

process leading to declining in the lifespans of projects, abandonment of projects, and the collapse of

completed infrastructures, etc. (Osei-Tutu et al., 2010; Boyd and Padilla, 2009). For instance, Wang et

al. (1999) identified this as one of the primary risk factors in Chinese BOT projects. Primarily in

developing countries, several infrastructure projects have been abandoned due to corrupt practices in

the public procurement sector (Mawenya 2008; Bowen et al. 2012). Ameh and Odusami (2009) reported

on a strong correlation between corruption prevalence and poor growth, development, and performance

in developing countries. Therefore, governments wishing to improve their stock of infrastructure

through the PPP strategy must fight corruption in public procurement first before they can succeed in

their quest to establish successful PPPs (Otairu et al., 2014). IP forms the backbone of every economy

globally, and it is very critical to the survival and livelihood of humanity. Ranging from all kinds of

structures (hospitals, roads, dams, etc.) to access to potable drinking water are all forms of

infrastructure, and when budgets allocated to procure these needs of humanity end up being

misappropriated through corruption, the net result is a socioeconomic setback. Researching corruption

in IP is, therefore, crucial. As a result, over the last two decades, scholars from around the world have

conducted and published many studies addressing the issue of corruption in IP. This section of the

research summarizes the topical constructs of corruption-related studies explored in the context of

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project procurement. It introduces how each construct, for instance, the causes of corruption impact the

different activities and stages within the context of projects procurement and execution, how

procurement irregularities or corruption risk indicators negatively influence the influence of corruption

as well as both the positive and negative impacts posed by the various constructs of corruption on the

procurement process. This section, therefore, sets the grounds for the succeeding chapters of this

research.

4.2.4 Causal Mappings with Corruption

Corruption transpires as a result of certain causal factors (Chapter 3). Causes of corruption simply refer

to the factors that give rise or triggers the incidence of corruption. Categorically, the factors include

organizational causes, psychosocial factors, regulatory factors, statutory factors and project-specific

factors (Zhang et al., 2016; Shan et al., 2016; Brown and Loosemore, 2015; Le et al., 2014; Bowen et

al., 2012; Tanzi, 1998; Stansbury, 2009). Under these identified, categorical or thematic constructs lie

most of the causal factors or individual variables that give rise to corruption in the process of realizing

any infrastructural project.

There may be several causal instigators that enable corruption to thrive. Aidt (2003) and Locatelli et al.

(2017) reported three conditions that serve as the breeding grounds for corruption to flourish. They

include discretionary powers, economic rents, and weak institutions. Also, other events, such as

humanitarian emergencies, which may consist of putting up infrastructural projects for deprived or

underdeveloped communities or countries, creates room for corruption to thrive (Saharan, 2015). For

example, in an emergency, the provision of services and amenities such as electricity, public transport,

water, gas, restoration of infrastructure, and others are often provided or done in haste, which may lead

to siphoning of funds (Saharan, 2015). Other causes include excessive greed, low salaries, lack of

supervisory skills and the belief among supervisory staff that the payment to the contractors is

insufficient for them to make a profit (Danert et al., 2003). Other causes include establishing improper

or unnecessary prequalification requirements and then allowing only selected firms to bid (Deng et al.,

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2003); lack of veracity by public servants entrusted with IP, weak accountability, and bad governance.

Lastly, the lack of auditing procedures, political instability, low level of professionalism of the

bureaucracy, lack of transparency and accountability were among other notable causes (Del Monte and

Papagni, 2007; Neupane et al., 2014; Kolstad & Wiig, 2009); monopoly power over a good or service

(Klitgaard, 1988).

According to Boyd and Padilla (2009), this issue of corruption is deeply rooted in the very core of public

enterprises, and in sectors where employees are not satisfied with their remuneration, they tend to

supplement it with proceeds of corruption. These kinds of causal factors are regarded as systemic

corruption and would be difficult to wipe out without palpable and major alterations in government

practice. Analogous to IP, due to the intricate process, systems, and procedures involved, corruption

may be very difficult to identify unless proper auditing and mitigating measures are put in place.

Therefore, to deal with the menace of corruption, it is expedient to deal with it from the causes as listed

above, although taking other factors into consideration, such as the forms of corruption to be dealt with

and others. This notion has underpinned the need for researching corruption purely to identify the causes

behind the act.

4.2.5 Corruption Forms within the Procurement Process

The evolution of corruption over the years has resulted in many different and unique forms of corrupt

practices and can be termed as the different faces or manifestations of corruption (Chan and Owusu

2017). TI (2005) broadly categorizes the CFs into two main constructs, namely petty and grand

corruption. Whereas petty corruption is concerned with smaller contracts, for instance, minor

infrastructural or developmental projects for local governments, grand corruption involves large

contracts usually executed by the state or central governments through self-funding or help from donors

(TI, 2005). Each one of these forms may have their relative causal instigators or common causes, and

their nature and characteristics may also vary widely from one another, although some of the forms

share some common traits.

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For instance, Chan and Owusu (2017) identified some forms pertaining to the construction industry and

IP in general and categorized under five main factors. The variables under these components shared

either common meanings or terms that were used interchangeably. The five main categories of CF in

the construction industry include bribery acts, fraudulent acts, collusive acts, extortionary acts, and

discriminatory acts. Additionally, another construct developed by the authors was unclassified due to

their stand-alone nature. These forms have affected the modus operandi of the construction industry in

general, and it was identified that most of the forms evolved with time, and others grew more pervasive

because measures were not taken to address them the time they were discovered.

The case is somewhat true with the prevalent forms of corrupt practices in IP, although the cases may

be different regarding different geographic contexts. Most of the identified forms of corruption in this

chapter largely center on the appointment of a contractor or suppliers and tender irregularities, and to a

lesser extent on contract administration and closeout irregularities. Deng et al. (2003) has the view that

the most critical and highest forms of corruption normally take place at the project performance stage,

that is, after the contract is awarded. The authors emphatically pointed out that it is at this stage that the

purchaser or the contractor fails to enforce suitable and stipulated standards of the contract objectives.

For example, failure to enforce quality and performance standards; the ability of the contractor to

sidetrack delivered goods meant for a project; resell or divert the project’s resources for personal use;

request for other private rewards or benefits such as trips, gifts, and many others. The authors also

reported that if a bidding procedure is less open, there is a higher risk for the bid to be rigged. Sahara

(2015) indicated that in the process of providing infrastructural projects for humanitarian assistance in

less privileged environments, the common forms of corrupt practices exemplified include

embezzlement or diversion of aid resources, misuse, and abuse of support agency assets, fraud, and

bribery. Ameh and Odusami (2010) also highlighted that bribery at the contract award stage is the most

evident or noticeable CF in IP. On the stance of favoritism, Kaufman (2003) indicated that it is one of

the most noted forms of corruption at the evaluation stage of every bidding process and remains the

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number one corrupt practice in the OECD member countries as compared to the other corrupt public

governance sources.

4.2.6 Anti-Corruption Measures (ACMs) and associated Barriers in IP

After identifying the forms and causal factors of corruption in IP, the third theme that was captured in

most of the papers was ACM. An ACM simply refers to any effective strategy or framework aimed at

suppressing or annulling corruption (any form with associated causal factors). Previous studies

conducted on ACMs classified the variables that emerged under this construct into three different

categories. They are proactive or preventive measures, promotional measures, and punitive or reactive

measures (Tabish and Jha, 2011; Narasimhan, 1997). In simple terms, proactive measures are set to

prevent the incidence of corruption. Promotional measures are made to raise awareness and educate the

entire public and the public servants on corruption. Reactive measures are also set to render punitive

actions to culprit or offenders. Punitive measures are often established and enforced by legal principles,

rules, and approaches for conducting effective and pragmatic investigations, disciplinary actions, and

other deliberate means to daunt corrupt practices. However, the problem identified in adopting and

applying the ACMs in different contexts does not lie in dispensing any of the measures but rather, how

to strategically and effectively integrate and coordinate the three to treat different kinds of corruption

cases in various contexts (Narasimhan, 1997). Confronting corruption in a sustained manner during the

procurement of infrastructure works would require comprehensive and integrative approaches that

combine preventive, public education, and punitive elements. Over the past two decades, different

measures and frameworks have been developed by researchers, anti-corruption institutions, and

policymakers in both public and private sectors, to thwart the incidence of corruption in infrastructure

procurement. Most consulting organizations give their maximum output to develop and define anti-

corruption policies. However, a number of them lack the consistency of daily execution of such

stipulated policies. Others also are unsuccessful in acquiring regular and systematic responses, which

may tend to enhance their transparency management systems. This has resulted in the ineffectiveness

of some of the measures. Not because the measures are impotent to check corruption, but rather, there

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is no one to enforce that the stipulated anti-corruption measures must be observed. This, in itself, forms

a barrier to ACMs that is discussed in the next paragraph. According to Osei-Tutu et al. (2010),

remedying the problem of corruption begins with awareness and recognition of its prevalence.

Raising the awareness of corruption does not only inform the audience about the practices of corruption

but also the reactive measures that a culprit may receive. Also, there is some evidence from construction

and other sectors that improved transparency, especially when combined with thorough oversight, can

improve development outcomes through its impact on the quality of governance (Kenny, 2012). Deng

et al. (2003) also indicated that a well-designed surety system reinforces transparency and restricts the

opportunities for corrupt behavior, while a poorly designed surety system can foster corruption. All

these and many more have been identified either empirically or theoretically by various researchers

with how they can be implemented or adopted and applied to mitigate corrupt practices. On the contrary,

while great efforts are constantly devoted to the development of new and innovative ACMs and

frameworks to help mitigate corrupt practices in IP, there are other factors different from the causal

measure, that hinder the full effectiveness of ACMs. These factors attack ACMs either by hampering

the adoption of the measures of the effective applicative thereof. As an emerging thematic area that has

not been deeply explored yet, one of the early works on this construct was reported by Bowen et al.

(2012). The authors highlighted the barriers that affect the effective reporting of corrupt practices in the

South African construction industry. These identified barriers make it difficult to achieve the full

potencies of ACMs. Some of the identified barriers include the fear of being marginalized, fear of being

caught reporting, social or occupational stigma and rejection, bureaucratic process of reporting corrupt

cases, lack of independence, fear of victimization, inappropriate internal institutional coordination /

inter-agency relations, the perception of no better end result, distrust in the system, inappropriate

staffing, lack of understanding and knowledge of rights within a contractual environment, difficulty in

providing concrete evidence among others were reported in the study of Bowen et al. (2012) in the

South African context.

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4.2.7 E-Procurement as an ACM

Electronic procurement, commonly known as E-procurement, refers to the means of acquiring or

purchasing goods and services through an electronic means (Sun et al., 2012; Neupane et al., 2012).

Simply put, any online transaction aimed at either selling or buying depicts e-procurement. However,

in infrastructure or construction procurement, the introduction of e-procurement was implemented to

facilitate the purchasing transaction of goods, services, supplies and works for either governments or

project financiers and suppliers on any online platform (Vaidya et al., 2006). Even though the notion of

e-procurement has been in operation for some time, it began dominating literature in the early

millennium (Neupane et al., 2012). E-procurement was established on two principles, namely

transparency and accountability in government procurement practices. In the quest of meeting the

transparency and the accountability demands, the United Nations (2006) reported that e-procurement

boots bidding automatization in the tendering process in order to enhance project monitoring, quicken

and ease the procurement process, ascertain and obtain the most desired price and quality ratio,

improves the competition that competitors go through and reduces the interactions and interventions of

the parties involved in the bidding process (Hanna, 2011; Achterstraat, 2011; Kaliannan and Awang,

2009; Magrini, 2006; Zang and Yang, 2011; Khanapuri et al., 2011 Thai, 2001).

Moreover, since accountability, openness and transparency are the principal concerns of public

procurement and also regarded as the indicators for good governance, the lack of these core values

creates the flourishing grounds for civil servants or professionals to exploit their powers for personal

gain (Parigi et al., 2004; Nurmandi and Kim, 2015; Neupane et al., 2014). A situation like this indicates

the presence or possible incidence of corruption (Nurmandi and Kim, 2015). The atomization of the

procurement system via the use of online platforms such as the internet ensures that competition is very

open because every bidder can monitor the tendering process on the internet at any given time. Again,

this lowers the intervention of any human to distract or corrupt the process and also reduce the degree

of personal decisions to influence contract award. This, in turn, builds trust, upsurge market

transparency, limit corrupt or fraudulent practice and encourage public procurement integrity (Neupane

et al., 2012; Vaidya et al., 2006). This, to an extent, affirms the notion of the application of e-

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procurement in public infrastructure procurement processes can serve as a very vital tool to reform

government IP. However, studies on the exploration or examination of how e-procurement can serve as

effectiveness against corruption in the identified systems, procedures, policies, and processes are very

vital for the future of transparent, free, and fair IP by either the public or private sector (Picci, 2011).

4.2.8 Vulnerabilities to Corruption (Irregularities/risk indicators)

Corruption vulnerabilities, as the name implies, refer to systematic loopholes or ‘red-flags’ and are not

necessarily causes of corruption. Neither do they directly trigger the incidence of corrupt practices.

They can be referred to as indirect actions of IP parties that may lead to corruption in the long run. In

order words, parties involved may not have the mindset to initially indulge in corruption, however, due

to systematic loopholes arising from a project, the project parties may involve themselves in practices

that may threaten the entire process of IP and potentially lead to corruption or to a large extent, the

practice may be regarded as a form of corruption in its original status (Le et al., 2014; Tabish and Jha,

2011). For instance, the measurement items such as ‘work not executed as per original specified design’

and ‘sufficient publicity not given to a tender’ identified in the study of Le et al. (2014) as risk indicators

may not necessarily be causes of forms of corruption, but they can serve as ‘red flags’ that may have

the potency to lead to corrupt behaviors if proper investigations are not carried out to determine the

rationale behind the indicators. Moreover, contrasting to the other topical areas (forms, causes, ACMs)

that are more general, corruption risk indicators are more context-specific. In other words, the variables

belonging to this construct vary from workplace to workplace, from institution to institution, and from

country to country. One of the early works to explore this area was conducted on public procurement

operations in India (Tabish and Jha, 2011). The study was conducted to analyze the irregularities in

Indian’s public procurement. The authors identified 61 different irregularities that could be regarded as

‘red-flags’ to corrupt practices in the Indian procurement works. These variables were further

categorized into five main components, namely: transparency irregularities, professional standards

irregularities, fairness irregularities, contract monitoring, and regulation irregularities and lastly,

procedural irregularities.

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However, these variables cannot be generalized since almost all of them identified in a report compiled

by the Chief Technical Examiner of India. In 2014, Le et al. (2014) conducted a similar study to identify

the irregularities in the Chinese construction public sector, and they identified 24 irregularities peculiar

to the Chinese public construction sector. These variables are not necessarily corrupt practices but rather

indicate the potential risks or the possibilities that corruption could occur. The variables can also be

used to measure how prone, vulnerable, or weak an organization or a state institution is to the incidence

of corruption with associated liabilities (Shan, 2015). Thus, the measurement of corruption is required

to attain headway toward its reduction through greater integrity, transparency, and accountability in

corruption-free performance. However, since this thematic of corruption in IP is also not deeply

explored due to its context-specific nature, procurement entities and researchers in different

procurement institutions or state enterprises are encouraged to conduct more research in this area to

reveal the possible indicators of corrupt practices in their respective environments.

4.2.9 Conceptual Framework

After explicating briefly, the systems, policies, procures, and the common processes involved in

infrastructure procurement, this section also identifies some key constructs to create a conceptual

framework for examining the issues of corruption in the context of IP. Categorically, the constructs

consist of the causal factors of corruption, risk indicators and forms of corruption in IP, anti-corruption

measures, e-procurement, and the barriers to effective adoption and application of these measures, and

lastly, the impact of corruption on the IP processes. There is the need to conceptualize how the

constructs noted under corruption affect all the identified constructs in IP. With the help of the identified

tools, series of empirical analyses are conducted to reveal the influences of the corruption constructs on

the respective stages of IP as well as the systems of IP. Fig. 4.4 shows the summary of the identified

factors or variables encapsulated in their respective constructs.

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This review revealed a very important theme, which was briefly discussed by Bowen et al. (2012) but

was hardly identified or noted in other publications known as the barriers to the effective application of

anti-corruption measures. Just as the three constructs above (forms, causes, and ACMs) have been

deeply explored by some studies, there is the need to look into the measures that serve as hindrances to

the effective application of anti-corruption measures. This may be conducted or explored contextually,

for example, in a given private or public sector and during any stage of infrastructure procurement or

project execution. This direction is deemed important because, in some instances, apropos measures

can be put in place to check corrupt practices. However, due to some internal or external constraints,

the measures set may be ineffective. However, the ineffectiveness may not be attributed to the actual

measures per se but rather the constraint forces that have not been explored. It is, therefore, very keen

and vital that a direction is taken to explore and address these constraint forces. Moreover, exploring

the relationships between the major constructs of both corruption and infrastructure procurement is very

vital for the future of procurement practice. The succeeding chapters attempt to answer the questions

raised in this chapter through an empirical survey. There is a need for research to be conducted to map

out and examine how the major constructs under corruption, namely cause, forms, risk indicators,

ACMs, and barriers against the ACMs, influence or affect the systems, policies, procedures, and the

processes involved in infrastructure procurement.

Therefore, in response to these identified gaps, all the identified constructs are empirically tested in the

cases of both developing and the developed context. This is intended to show how the public IP, in

general, is influenced or affected by these variables. Investigating the causal correlations will help

reveal the pressing variables of the various constructs of corruption and their causal effects on the

various categories of IP and how strategic measures or frameworks can be drawn to deal with this

menace in IP. These also influence and inform clients, project financiers, or managers on the best system

and procedure to adopt for a specific project. The findings will help develop the best strategic and

comprehensive measures or framework to adapt to mitigate or help check corruption in these mentioned

systems. The findings will also go a long way to influence the choice of the best system in terms and

procedures to consider or adopt in terms of clean procurement. Other interesting findings may crop up

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that will help the future of infrastructure procurement practice. The identified variables will, therefore,

serve as the data to be tested empirically against the respective IP phases identified, as illustrated in Fig.

4.4.

Figure 4.4: Conceptual Framework

4.2.10 Section concluding remarks

This chapter of the review sought to explore the various constructs captured under the subject matter of

corruption in the context of infrastructure procurement. Following the works on the subject matter

conducted in this area in these past years, there has been a significant increase in the body of knowledge

on this subject matter. With the achievements of such enormous progress, a gap in the unified view of

these constructs and the systematic review of the relevant literature regarding the constructs and their

effects on IP practices, which are vital for future endeavors, remained unexplored.

This reason triggered the direction and the aim for conducting this review study. After a systematic and

comprehensive search for publications on the topic was conducted, 48 relevant articles were retrieved

and formed the foundation for further analysis. The review revealed the prevalent thematic areas of

corruption explored in IP. They included forms, causal mappings, and the risk indicators, the ACMs

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developed so far, and the barriers that impede the effective adoption and application of these measures

in IP. The constructs identified under IP also included the systems, processes, policies, and procedures.

Each of the corruption constructs is composed of individual variables that affect the IP constructs

directly or indirectly. The next chapter commences the first empirical analysis of the data gathered. It

explores the susceptibility patterns of the procurement process and develops the first model to estimate

and predict the susceptibility indexes of the stages of the procurement process in other existing or

ongoing projects.

4.3 Chapter Summary

This chapter commenced with a review of the procurement process of construction and other

infrastructure-related works. The various procurement methods, policies and procedures of the

procurement methods was reviewed to identify the key indicators of the various constructs mentioned.

As a result, the key activities and stages of the procurement process were reviewed. Following the

identification of the various methods and procedures as well as the key stages and associated activities

of the procurement process, the IP process was further reviewed in terms of their vulnerabilities to the

criticalities of corruption. Thus, while the various constructs of corruption were reviewed as standalone

constructs in the previous chapter, this chapter extended it further by reviewing the criticalities of the

constructs and the variables of corruption at the various stages of the procurement process. The

amalgamation of the various indicators underlying the constructs of corruption and the procurement

process formed the conceptual framework for this duty. Thus, this chapter presented the main theoretical

suppositions underlying the two constructs, that are tested later in the study.

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CHAPTER 5 – THE PROCUREMENT PROCESS’ PRONENESS

TO CORRUPTION9

5.1 Introduction

The early detection of the risk factors and the causal factors that propel the incidence of corrupt practices

can help abate the manifestation, proliferation, and the unpleasant effects associated with corruption

(Owusu et al., 2017). However, due to the difficulty in measuring corruption, it may seem impossible

to establish measures to detect the likelihood of a project’s vulnerability to corruption (Le et al., 2014).

Given these shortcomings, this chapter attempts to develop a fuzzy evaluation model for measuring and

predicting the proliferation and likelihood of corrupt practices at different stages of the procurement

process of construction projects. Additionally, the present study maintains that the estimated indexes of

the individual stages of the procurement process can be integrated into an overall vulnerability index to

determine the susceptibility of a construction project to corrupt practices. To develop the model, this

chapter was informed by the following objectives: 1) to identify the various activities that are performed

at the specific stages of the procurement process; 2) to examine the susceptibility levels of the individual

activities within their respective stages, and 3) to develop the measurement model for assessing the

vulnerability level of construction projects using the fuzzy synthetic evaluation (FSE) technique.

Theoretically, this chapter contributes to the body of knowledge regarding the systematic approaches

of measuring the various indicators of corruption in construction and other infrastructure procurement.

It is, arguably, the first study to employ soft computing techniques (i.e., the FSE approach) to estimate

the susceptibility patterns of the various stages of the procurement process as well as develop a

standardized yet straightforward approach to facilitate similar estimations in future works. Practically,

even though a rigorous technique is employed, the model is developed in such a manner that is easily

9
This chapter is fully or partially published in the following journal article: Owusu, E. K., Chan, A. P., &
Ameyaw, E. (2019). Toward a Cleaner Project Procurement: Evaluation of Construction Projects’ Vulnerability
to Corruption in Developing Countries. Journal of Cleaner Production. pp.394-407

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understandable and can be adopted by practitioners (e.g., policymakers and auditors) for detecting and

measuring the vulnerability of the procurement stages to corruption. The model can also form the basis

for researchers to develop more comprehensive tools that extend beyond the boundaries of the

procurement process for predicting, measuring and offering effective prevention measures for corrupt

practices right from the definition of project’s requirements through to contract close-out.

5.2 Research Design

As mentioned in the previous section, expert data were solicited to determine the indicators of the

model. First, primary data regarding the vulnerability of the procurement process were solicited from

experts directly involved in procurement and construction management of construction works. A

questionnaire survey was conducted to solicit views from the experts concerning the constructs and the

indicators that are needed to arrive at the model. Prior to the development of the questionnaire, a

thorough, systematic review of the literature (e.g., Le et al. 2014; Lester, 2007; Ruparathna and Hewage,

2014; Chan and Owusu 2017) was conducted to arrive at the variables or the activities within the

procurement process which are used as the indicators to develop the constructs of the model. Since the

aim of the study is to measure the indicators regarding the susceptibility of the procurement process,

the review conducted led to the retrieval of 21 traditional activities captured under four procurement

stages (Fig. 1). The 21 activities were considered as traditional, because they can be identified in most,

if not all, of the procurement systems, comprising the design and construct method, management

procurement, on-call contracting, guaranteed maximum price, full cost reimbursable, and total package

options among others (Ruparathna and Hewage, 2013).

The survey respondents were asked to rate the levels of vulnerability of each of the 12 activities based

on a five-point grading scale (1 = very low vulnerability and 5 = very high vulnerability). Further, a

section was provided in the questionnaire for the respondents to provide any known critical activity or

stage of the procurement process that was not captured in the questionnaire. Questionnaires were

adopted because they offer a valid and reliable source of information and are less costly (Hoxley, 2008).

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Moreover, a questionnaire survey, to a large extent, warrants anonymity and the protection of

respondents’ data, especially on a sensitive topic of this nature (Chan et al., 2017; Ameyaw et al., 2017).

5.3 Procurement Process’ Proneness Model Development

This section presents the various steps of the fuzzy synthetic technique employed to analyze the

susceptibility index of the procurement process as well as develop the fuzzy model needed to facilitate

the estimations of the susceptibility patterns of future projects. The following section, therefore,

commences with the development of an index system for the variables prior to estimating the overall

vulnerability index.

5.3.1 Developing an assessment Index System

Given the four constructs of the procurement process, the evaluation system for computing the index

can be developed by establishing the construct or stages as the first or primary level index system as

V= (V1, V2, V3… Vm) (Ameyaw and Chan 2015; Shao 2004). In this context, they are labeled as (VPCS,

VCTS, VCAS, and VPCP). The variables or activities within their respective procurement constructs are also

defined as secondary or second-level index system as:

VPCS = {𝑣𝑃𝐶𝑆1 , 𝑣𝑃𝐶𝑆2 , 𝑣𝑃𝐶𝑆3 , 𝑣𝑃𝐶𝑆4 , 𝑣𝑃𝐶𝑆5 , 𝑣𝑃𝐶𝑆6 }

VCTS = {𝑣𝐶𝑇𝑆1 , 𝑣𝐶𝑇𝑆2 , 𝑣𝐶𝑇𝑆3 , 𝑣𝐶𝑇𝑆4 , 𝑣𝐶𝑇𝑆5 }

VCAS = {𝑣𝐶𝐴𝑆1 , 𝑣𝐶𝐴𝑆2 , 𝑣𝐶𝐴𝑆3 , 𝑣𝐶𝐴𝑆4 }, and

VPCP = {𝑣𝑃𝐶𝑃1 , 𝑣𝑃𝐶𝑃2 , 𝑣𝑃𝐶𝑃3 , 𝑣𝑃𝐶𝑃4 , 𝑣𝑃𝐶𝑃5 , 𝑣𝑃𝐶𝑃6 }

The index systems are considered as the input variables for the fuzzy synthetic analysis (Ameyaw et al.

2017). The respondents were therefore required to rank the individual activities using the 5-point Likert

grading system as V= (1,2,3,4,5) where 1= very low (VL), to 5= extremely high (EH). Adopting the

five-point grading scale in this section of the study is consistent with past studies (Shan et al. 2015;

Zhao et al. 2015; Osei-Kyei and Chan 2017). The Likert scale representing the linguistic terms, which

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facilitates the judgment of the experts involved in the study, and the determination of the membership

functions are presented in Table 5.1.

Table 5.1: Input Variables’ Linguistic Terms

Scale Term Degree of capability Constant

1 Very low 0 – 0.25 0.125
2 Low 0 – 0.50 0.250
3 Neutral 0.25 – 0.75 0.500
4 High 0.50 – 1.00 0.750
5 Extremely high 0.75 – 1.00 0.875
Adapted from Ameyaw et al. (2017)

5.3.2 Estimations of Input Variables’ Weightings.

The individual weightings of the variables or activities within the four stages of the procurement process

were determined using the normalization technique. The formula for determining the normalized values

or the specific weighting is given as (Lo, 1999):

𝑀𝑖
𝑤𝑖 = ∑5 , 0 < 𝑤𝑖 < 1, 𝑎𝑛𝑑 ∑5𝑖=1 𝑤𝑖 = 1 (eqn. 5.1)
𝑖=1 𝑀𝑖

Where 𝑤𝑖 represents the weighting of the activities within the procurement stages or constructs i; 𝑀𝑖 ,

represents the mean index or value of the specific activity or associated stage i generated from the

survey analysis. The function set of the weights is thus given by:

Wi = {𝑤1 , 𝑤2 , 𝑤3 ,… 𝑣𝑚 }

(eqn. 6.2)

Therefore, using the ‘check for proof of delivery,’ (𝑃𝐶𝑃4 ), which is the fourth activity in the post-

contract phase and equation (1), the weighting is calculated as follows:

3.76 3.76
𝑊𝑃𝐶𝑃4 = 3.48+3.51+3.48+3.76+3.45+3.39 = 21.07 = 0.178

Using the same formula, the remaining weightings of the individual activities within their respective

constructs are evaluated. The summation of the weightings of a group of activities within the same

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construct must be equal to the value of one. A typical example using the PCP construct is presented

below:

∑ 𝑊𝑃𝐶𝑃 = 0.165 + 0.167 + 0.165 + 0.178 + 0.164 + 0.161 = 1.00

𝑘=1

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Table 5.2: MF for Stages and respective activities of the Procurement Process
Procurement Procurement Activities Code Mean N- Weighting Total mean Weighting
Stages Value of stages of stages
1 Pre-Contract Define requirements, vpcs1 PCS1 2.63 0.00 0.133
2 stage Procurement process planning and strategy PCS2 3.05 0.27 0.155
development, vPCS2
3 Pre-tender survey, vPCS3 PCS3 3.15 0.33 0.160
4 Obtaining necessary approvals, vpcs4 PCS4 3.52 0.56 0.178
5 Soliciting tenders, vpcs5 PCS5 4.02 0.88 0.204
6 Receipt of tenders, vpcs6 PCS6 3.35 0.46 0.170 19.72 0.271
7 Contract Pre-tender meeting (Establishing Evaluation Criteria, CTS1 3.40 0.49 0.182
Stage Evaluation Plan, Evaluation Criteria), vcts1
8 Tender evaluation (review to approve or reject bids), CTS2 4.00 0.87 0.214
vcts2
9 Select contractor, vcts3 CTS3 4.21 1.00 0.225
10 Award contract/Purchase order, vcts4 CTS4 3.74 0.70 0.200
11 Preparation and Signing of Contract, vcts5 CTS5 3.35 0.46 0.179 18.70 0.257
12 Contract Issuing contract amendments, vcas1 CAS1 3.13 0.32 0.238
13 administrati Monitor Progress, vcas2 CAS2 3.39 0.48 0.257
14 on stage Follow up delivery, vcas3 CAS3 2.97 0.22 0.226
15 Administer Progress payments, vcas4 CAS4 3.68 0.66 0.279 13.17 0.181
16 Post File final action Contractor agreement to final claim, PCP1 3.48 0.54 0.165
contract pcp1
17 phase Issue final contract amendment, vpcp2 PCP2 3.51 0.56 0.167
18 Complete of financial audits, vpcp3 PCP3 3.48 0.54 0.165
19 Check for proof of delivery, vpcp4 PCP4 3.76 0.72 0.178
20 Return of performance bonds and close-out, vpcp5 PCP5 3.45 0.52 0.164
21 Ensure completeness and accuracy of file PCP6 3.39 0.48 0.161 21.07 0.290
documentation, vpcp6
Total mean and weighting values 72.66 1.000

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5.3.3 Determining the Membership Functions of the Input Variables for the Activities

Membership functions (MFs) in fuzzy set theory represent the extent or degree (within the range of 0

and 1) of an element’s membership in a fuzzy set (Xu et al. 2010). Thus, regarding the MFs of the input

variables, the FSE technique employs the application of membership degrees in a given set instead of a

strict true or false membership (Tah and Carr, 2000). Rather than using absolute terms or values such

as 0 and 1 to represent an elements association to a fuzzy set, the FSE tool expresses the element’s

belongingness or membership to a fuzzy set in terms of varying degree of relation.

The degree or extent of membership can, therefore, consider any value within a closed range of 0 and

1; the obtained value characterizes the degree or measure to which the element belongs to a fuzzy set

(Ameyaw et al., 2015; Tar and Carr, 2000; Kasirolvalad et al., 2006). They are derived from the

respondents’ assessments of the 21 procurement activities using the Likert scale (as discussed).

According to Ameyaw and Chan (2016), it is appropriate to designate the various levels where the

membership functions are derived. Therefore, as established earlier, the linguistic terms for examining

the input variables (i.e., the procurement activities) against the vulnerabilities constructs were

determined using the 5-point grading system as 𝑙 = (1,2,3,4,5), where 𝑙1 = very low, 𝑙2 = low, 𝑙3 =

moderate, 𝑙4 = high, 𝑙5 = very high. The membership function of a given vulnerability construct was

derived using the formula below:

𝑥1 𝑣 𝑥2 𝑣 𝑥3 𝑣 𝑥4 𝑣 𝑥5 𝑣 𝑥1 𝑣 𝑥2 𝑣 𝑥3 𝑣
𝑖𝑛 𝑖𝑛 𝑖𝑛 𝑖𝑛 𝑖𝑛 𝑖𝑛 𝑖𝑛 𝑖𝑛
𝑀𝐹𝑣𝑖𝑛 = + + + + = + +. . . . + (eqn. 5.3)
𝑙1 𝑙2 𝑙3 𝑙4 𝑙5 𝑣𝑒𝑟𝑦 𝑙𝑜𝑤 𝑙𝑜𝑤 𝑣𝑒𝑟𝑦 ℎ𝑖𝑔ℎ

Where 𝑀𝐹𝑣𝑖𝑛 represents the membership function (MF) of specific activity of the procurement process

𝑣𝑖𝑛 ; 𝑥𝑦 𝑣 (y=1,2,3,4,5) indicates the percentage of a given score y for an activity of a given construct
𝑖𝑛

as assigned by the experts (i.e., 𝑣𝑖𝑛 ); and 𝑥𝑦 𝑣 /𝑙1 denotes the relation between 𝑥𝑦 𝑣 and its respective
𝑖𝑛 𝑖𝑛

grade alternative. Therefore, referring to equation 3, the membership function of a specific construct

can be written as:

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𝑀𝐹𝑣𝑖𝑛 = (𝑥1 𝑣𝑖𝑛 , 𝑥2 𝑣𝑖𝑛 , 𝑥3 𝑣𝑖𝑛 , 𝑥4 𝑣𝑖𝑛 , 𝑥5 𝑣𝑖𝑛 ). (eqn. 5.4)

Therefore, using the contractor selection stage (CTS3) as an example owing to the ratings by the experts

(i.e., 0.00%, 1.60%, 12.90%, 48.40%, 37.10%), the membership function is evaluated as follows:

0.00 0.02 0.13 0.48 0.37

𝑀𝐹𝑐𝑡𝑠3 = 𝑁𝑜𝑡 𝑉𝑢𝑙𝑛𝑒𝑟𝑎𝑏𝑙𝑒 + 𝐿𝑒𝑠𝑠 𝑉𝑢𝑙𝑛𝑒𝑟𝑎𝑙𝑒 + 𝑁𝑒𝑢𝑡𝑟𝑎𝑙 + 𝑉𝑢𝑙𝑛𝑒𝑟𝑎𝑏𝑙𝑒 + 𝐸𝑥𝑡𝑟𝑒𝑚𝑒𝑙𝑦 𝑉𝑢𝑙𝑛𝑒𝑟𝑎𝑏𝑙𝑒

The MF is, therefore, presented as (0.00, 0.02, 0.13, 0.48, 0.37). The individual members within the

function range between 0 and 1, and the summation of the members must be equal to 1:

∑5𝑘=1 𝑥𝑘 𝑣 = 1 (eqn. 5.5)

𝑖𝑛

This was repeated for all the procurement activities within their respective constructs to determine their

respective membership functions. The MF of all the individual activities of the procurement process

were classified under level three, as presented in Table 5.3.

5.3.4 Determination of the Membership Functions for the Constructs/Stages (Level 2)

The next step after the determination of the membership functions at level three was an evaluation of

the membership function at level two. That is membership function for the main procurement stages or

constructs. The derivation of the membership function is derived by the formula below:

𝐷 = 𝑊𝑖 ●𝑅𝑖 (eqn. 5.6)

Where 𝑊𝑖 represents the individual weightings of all the activities within their respective constructs or

stages and 𝑅𝑖 represents the fuzzy evaluation matrix. Following a similar approach used previously in

eqn. (1), the weightings were estimated using the formula below:

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𝑀𝑖
𝑀𝐹𝑣𝑖𝑛 = ∑5 , 0 < 𝑤𝑖 < 1, 𝑎𝑛𝑑 ∑5𝑖=1 𝑤𝑖 = 1 (eqn. 5.7)
𝑖=1 𝑀𝑖

Using CTS as an example, the weightings for the constructs were estimated as follows:

18.70 18.70
𝑊𝐶𝑇𝑆 = = = 0.257
19.72+18.70+13.17+21.07 72.66

The remaining three constructs (i.e., the PCS, CAS, and PCP) were computed in a similar as described

above. In calculating for the individual weightings of the constructs, the mean scores of each stage or

construct were normalized to ascertain their respective weightings where the summations of all the

weightings equate to 1. For instance, the calculation for the four stages or constructs were evaluated as

follows:
19.72 19.72
𝑊𝑃𝐶𝑆 = = = 0.271
19.72+18.70+13.17+21.07 72.66

13.17 13.17
𝑊𝐶𝐴𝑆 = 19.72+18.70+13.17+21.07 = 72.66 = 0.181

21.07 21.07
𝑊𝑃𝐶𝑃 = 19.72+18.70+13.17+21.07 = 72.66 = 0.290

∑4𝑖=1 𝑤𝑖 = 0.271 + 0.257 + 0.181 + 0.290 = 1

Therefore, the weightings can be presented as follows:

𝑤𝑖 = (𝑤1 , 𝑤2 , 𝑤3 , … 𝑤𝑖 ) = (0.271, 0.257, 0.181, 0 .290)

5.3.5 Establishment of the Multi-level and Multi-criteria FSE Model

Given that the evaluation of the susceptibility levels of the procurement process is a multi-criteria (that

is, from activity to activity and stage to stage) and a multi-level (that is, from the activity level to the

construct or stage level), the evaluation involves three primary stages. The first stage deals with the

establishment of the MFs and the estimated weighted functions (𝑤𝑖 ) of the individual activities (for

example, PCS1, PCS2, CTS4, CTS3, CAS1). This is known as the lower level and is based on the

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assessments from the experts’ survey. The second stage also deals with the establishment of the

membership and weighted functions of the individual constructs or stages (PCS, CTS, CAS, and PCP).

The evaluation of the respective impacts of the stages is, therefore calculated at this level. The third and

final stage estimates the overall vulnerability index of the procurement process, which is presented by

a single index or value. Therefore, with the establishment of the MFs and the estimated 𝑤𝑖 of the

individual activities (3rd level) which are obtained from the experts’ responses, the estimations of the

constructs’ indexes (2nd level) and the overall vulnerability index (1st level) are discussed. With

reference to eqn. (6), to determine the vulnerability levels of the respective stages of the procurement

process, 𝐷𝑖 , which represents a fuzzy matrix is first established for each of the procurement stages after

the derivation of the membership functions of the activities within the stages. Therefore, following eqn.

4 [𝑀𝐹𝑎𝑖𝑛 = (𝑥1 𝑎 + 𝑥2 𝑎 + 𝑥3 𝑎 + 𝑥4 𝑎 + 𝑥5 𝑎 )] the membership functions for all the activities

𝑖𝑛 𝑖𝑛 𝑖𝑛 𝑖𝑛 𝑖𝑛

within their respective stages can be demonstrated in a fuzzy matrix presented below:

𝑀𝐹𝑣𝑖1 𝑥1 𝑣𝑖1 𝑥2 𝑣
𝑖1
𝑥3 𝑣
𝑖1
𝑥4 𝑣
𝑖1
𝑥5 𝑣
𝑖1
𝑀𝐹 𝑥1 𝑥2 𝑣𝑖2 𝑥3 𝑣𝑖2 𝑥4 𝑣𝑖2 𝑥5 𝑣𝑖2
| 𝑣𝑖2 | | 𝑣𝑖2
𝑅𝑖 = 𝑀𝐹𝑣𝑖3 = 𝑥1 𝑣𝑖3 𝑥2 𝑣𝑖3 𝑥3 𝑣𝑖3 𝑥4 𝑣𝑖3 𝑥5 𝑣𝑖3 | (eqn. 5.8)
| | | ⋯ ⋯ ⋯ ⋯ ⋯ |
⋯
𝑀𝐹𝑣𝑖𝑛 𝑥1 𝑣𝑖𝑛 𝑥2 𝑣
𝑖𝑛
𝑥3 𝑣
𝑖𝑛
𝑥4 𝑣
𝑖𝑛
𝑥4 𝑣
𝑖𝑛

Where the elements are presented by 𝑥1 𝑣𝑖1 . Using the contract stage (CTS) as an example, the elements

in the fuzzy matrix can be presented through Eqn. 8 as in:

𝑀𝐹𝑣21
0.15 0.13 0.16 0.31 0.26
𝑀𝐹𝑣22 0.02 0.03 0.18 0.48 0.29
| |
𝑅𝑐𝑡𝑠 = 𝑀𝐹𝑣23 =||0.00 0.02 0.13 0.48 0.37||
|𝑀𝐹 | 0.10 0.06 0.08 0.52 0.24
𝑣23
𝑀𝐹𝑣25 0.08 0.11 0.32 0.34 0.15

It must be emphasized that the FSE technique comprises three levels of the membership functions (i.e.,

from the third level to the first level). The computations at this section are used to arrive at level 2. The

derivation of the fuzzy matrix 𝐷𝑖 is arrived with the application of the function set of the individual

weightings 𝑤𝑖 = (𝑤1 , 𝑤2 , 𝑤3 , … 𝑤𝑖 ) of the activities within their respective stages or construct i as

presented below:

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𝑥1 𝑣 𝑥2 𝑣 𝑥3 𝑣 𝑥4 𝑣 𝑥5 𝑣
𝑖1 𝑖1 𝑖1 𝑖1 𝑖1
𝑥1 𝑣𝑖2 𝑥2 𝑣𝑖2 𝑥3 𝑣𝑖2 𝑥4 𝑣𝑖2 𝑥5 𝑣𝑖2
| 𝑥5 𝑣𝑖3 |
𝐷𝑖 =𝑊𝑖 ●𝑅𝑖 =(𝑑𝑖𝑛 , 𝑑𝑖𝑛 , 𝑑𝑖𝑛 , … 𝑑𝑖𝑛 )=(𝑤1 , 𝑤2 , 𝑤3 , … 𝑤𝑖 )● 𝑥1 𝑣𝑖3 𝑥2 𝑣𝑖3 𝑥3 𝑣𝑖3 𝑥4 𝑣𝑖3
| ⋯ ⋯ ⋯ ⋯ ⋯ |
𝑥1 𝑣𝑖𝑛 𝑥2 𝑣𝑖𝑛 𝑥3 𝑣𝑖𝑛 𝑥4 𝑣𝑖𝑛 𝑥4 𝑣𝑖𝑛

=(𝑑𝑖1 , 𝑑𝑖2 , 𝑑𝑖3 , … 𝑑𝑖𝑛 ) (eqn. 5.9)

Where 𝑑𝑖𝑛 represents the grade alternative membership degree, vin with regard to a specific stage of the

procurement process; and ● connotes the fuzzy composite operation (Ameyaw and Chan 2016; Lo et

al. 1999). Taking into consideration the individual weightings of the activities within 𝑐𝑡𝑠 (i.e., construct

CTS), the matrix 𝑅𝑐𝑡𝑠 is normalized using equation 9 above.

𝑀𝐹𝑎21
𝑀𝐹
| 𝑎22 |
𝐷𝑐𝑡𝑠 = 𝑊𝑐𝑡𝑠 ●𝑅𝑐𝑡𝑠 =(𝑤𝑐𝑡𝑠1 , 𝑤𝑐𝑡𝑠2 , 𝑤𝑐𝑡𝑠3 , 𝑤𝑐𝑡𝑠4 , 𝑤𝑐𝑡𝑠5 ) × 𝑀𝐹𝑎23
|𝑀𝐹 |
𝑎23
𝑀𝐹𝑎25

0.15 0.13 0.16 0.31 0.26

0.02 0.03 0.18 0.48 0.29
𝑇ℎ𝑒𝑟𝑒𝑓𝑜𝑟𝑒, 𝐷𝑎𝑐𝑡𝑠 = (0.182,0.214,0.225,0.200,0.179) × ||0.00 0.02 0.13 0.48 0.37||
0.10 0.06 0.08 0.52 0.24
0.08 0.11 0.32 0.34 0.15

= (0.06, 0.07, 0.17, 0.43, 0.27)

The same approach was used to derive the membership function for all the other respective constructs

or stages at level two. Table 5.3, therefore, presents the derivations of the membership functions at both

level two and three.

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Table 5.3: MF for Stages of the Procurement Process

Procurement Code Activities’ MF for Level 3 MF for Level 2 Constructs’ MF for Level 1
Process Weightings Weightings
Pre-Contract PCS1 0.133 0.29, 0.16, 0.23, 0.27, 0.05 0.13, 0.14, 0.18, 0.37, 0.19 0.13 0.09, 0.12, 0.19, 0.41, 0.20
stage PCS2 0.155 0.13, 0.24, 0.19, 0.32, 0.11
PCS3 0.160 0.15, 0.18, 0.23, 0.29, 0.16
PCS4 0.178 0.11, 0.13, 0.11, 0.42, 0.23
PCS5 0.204 0.03, 0.05, 0.11, 0.48, 0.32
PCS6 0.170 0.13, 0.10, 0.24, 0.35, 0.18
Contract Stage CTS1 0.182 0.15, 0.13, 0.16, 0.31, 0.26 0.06, 0.07, 0.17, 0.43, 0.27 0.06
CTS2 0.214 0.02, 0.03, 0.18, 0.48, 0.29
CTS3 0.225 0.00, 0.02, 0.13, 0.48, 0.37
CTS4 0.200 0.10, 0.06, 0.08, 0.52, 0.24
CTS5 0.179 0.08, 0.11, 0.32, 0.34, 0.15
Contract CAS1 0.238 0.13, 0.19, 0.16, 0.42, 0.08 0.11, 0.16, 0.19, 0.41, 0.14 0.11
administration CAS2 0.257 0.10, 0.15, 0.19, 0.40, 0.16
stage CAS3 0.226 0.15, 0.21, 0.24, 0.34, 0.06
CAS4 0.279 0.06, 0.10, 0.16, 0.45, 0.23
Post contract PCP1 0.165 0.08, 0.13, 0.19, 0.42, 0.18 0.07, 0.12, 0.20, 0.43, 0.18 0.07
phase PCP2 0.167 0.05, 0.18, 0.18, 0.39, 0.19
PCP3 0.165 0.08, 0.08, 0.24, 0.47, 0.13
PCP4 0.178 0.05, 0.08, 0.18, 0.45, 0.24
PCP5 0.164 0.10, 0.08, 0.24, 0.44, 0.15
PCP6 0.161 0.08, 0.18, 0.18, 0.40, 0.16
Note: MF connotes membership function

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After determining each of the constructs’ fuzzy matrix, the vulnerability level of each of the

procurement stage can be estimated using the formula below (eqn. 10).

̅ × 𝐿𝑡 = (𝐷′ , 𝐷′ 2 , 𝐷′ 3 , 𝐷′ 4 , 𝐷′ 5 ) × (1,2,3,4,5)
𝑉𝐿𝑖 = ∑5𝑘=1 𝐷 (eqn. 5.10)
1

1 ≤ VLi ≤ 5

Since an analogous formula is employed to estimate the overall vulnerability index for the entire

procurement process, the formula is better explained at the overall estimation section. However, using

the formula above, the individual index for each stage (i.e., the vulnerability level for the individual

procurement stages) is computed as follows:

𝑉𝐿𝑝𝑐𝑠 = [(0.13 × 1) + ( 0.14 × 2) + ( 0.18 × 3) + ( 0.37 × 4) + ( 0.19 × 5)] = 3.34, for the

precontract phase;

𝑉𝐿𝑐𝑡𝑠 = [(0.06 × 1) + ( 0.07 × 2) + ( 0.17 × 3) + ( 0.43 × 4) + ( 0.27 × 5)] = 3.77 for the

contract phase;

𝑉𝐿𝑐𝑎𝑠 = [(0.11 × 1) + ( 0.16 × 2) + ( 0.19 × 3) + ( 0.41 × 4) + ( 0.14 × 5)] = 3.30, for the

contract administration stage; and,

𝑉𝐿𝑝𝑐𝑝 = [(0.07 × 1) + ( 0.12 × 2) + ( 0.20 × 3) + ( 0.43 × 4) + ( 0.18 × 5)] = 3.51 for the post-

contract phase.

5.3.6 Estimating the overall vulnerability Index

The weighted mean method was adopted for this study. It reserves the vulnerability effects of all the

procurement activities as well as constructs, an upper threshold of 1 is needed in the event of the

normalization of both the activities and the constructs, and also the disparities between their respective

weightings are nominal (Hsiao, 1998; Lo et al. 2016; Ameyaw and Chan 2016). This selection criterion

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is as well adopted widely in the domain of fuzzy multi-criteria decision making (Ameyaw et al. 2016;

Yeung et al. 2010). According to Hsaio (1998), the weighted mean {M(●, Ꚛ)} approach is defined as:

𝑑𝑖𝑛 = 𝑚𝑖𝑛 {1, ∑𝑚

𝑖=1 𝑤𝑖𝑛 𝑥𝑘 𝑣 } , 𝑛 = 1,2, . . . . . , 𝑓 (eqn. 5.11)
𝑖𝑛

The notation of 1 as the upper threshold for the normalized weightings is done using the symbol “Ꚛ”

and the normalization of the weighted functions causes the operator ‘Ꚛ’ to regress when real numbers

are added such that:

𝑑𝑖𝑛 = ∑𝑚
𝑖=1 𝑤𝑖𝑛 𝑥𝑘 𝑣 , 𝑛 = 1,2, . . . . . , 𝑓
𝑖𝑛

That is, the operation relapses to {M (●, Ꚛ)}, and this model is termed as the weighted mean score

(Hsiao 1998). The computed matrix, therefore, forms the foundational fuzzy matrix to calculate the

overall vulnerability index for the procurement of infrastructure projects. Therefore, using the formula

below:

𝐷1 𝑑11 𝑑12 𝑑13 𝑑14 𝑑15

𝐷 𝑑 𝑑22 𝑑23 𝑑24 𝑑25
𝑅̅ = | 2 | = | 21 | (eqn. 5.12)
𝐷3 𝑑31 𝑑32 𝑑33 𝑑34 𝑑35
𝐷4 𝑑41 𝑑42 𝑑43 𝑑44 𝑑45

Where 𝑅̅ represents the fuzzy matrix for estimating the overall vulnerability index, 𝐷𝑖 (𝑖 =

𝑣1 , 𝑣2 , 𝑣3 , 𝑣4 ) characterizes the obtained evaluated matrix. A typical illustration is presented below

using the final generated fuzzy evaluation matrix of the procurement constructs at level 2, which will

then be used to determine the overall vulnerability index of the procurement process. This is

demonstrated below:

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𝐷𝑝𝑠𝑐 0.13 0.14 0.18 0.37 0.19

𝐷𝑐𝑡𝑠 0.06 0.07 0.17 0.43 0.27
𝑅̅ = | =| |
𝐷𝑐𝑎𝑠 | 0.11 0.16 0.19 0.41 0.14
𝐷𝑝𝑐𝑝 0.07 0.12 0.20 0.43 0.18

Using equation 12 above, the fuzzy matrix, 𝑅̅ , is afterward normalized through the determined

weighting function set of the individual constructs of the procurement process (𝑤1 , 𝑤2 , 𝑤3 , 𝑤4 )to

estimate the fuzzy evaluation matrix of the final stage, as explicated in the previous section:

𝑑11 𝑑12 𝑑13 𝑑14 𝑑15

̅𝑖 ●𝑅̅𝑖 = (𝑤1 , 𝑤2 , 𝑤3 , 𝑤4 )𝑥 |𝑑21
̅𝑖 = 𝑊
𝐷
𝑑22 𝑑23 𝑑24 𝑑25
| = (𝐷′1 , 𝐷′ 2 , 𝐷′ 3 , 𝐷′ 4 , 𝐷′ 5 ) (eqn. 5.13)
𝑑31 𝑑32 𝑑33 𝑑34 𝑑35
𝑑41 𝑑42 𝑑43 𝑑44 𝑑45

̅𝑖 represents the fuzzy

Using the generated weighting function set estimated through Eqn. 10, where 𝐷

evaluation matrix or the membership functions for the procurement stages

(𝑖. 𝑒. , 𝐷′1 , 𝐷′ 2 , 𝐷′ 3 , 𝐷′ 4 , 𝐷′ 5 ), the fuzzy matrix can be quantified using the selected grade alternative

(L=1,2,3,4,5) using the formula below:

̅ × 𝐿𝑡 = (𝐷′ , 𝐷′ 2 , 𝐷′ 3 , 𝐷′ 4 , 𝐷′ 5 ) × (1,2,3,4,5)
∑5𝑘=1 𝐷 1 ≤ CVI ≤ 5 (eqn. 5.14)
1

0.271 0.13 0.14 0.18 0.37 0.19

0.257 0.06 0.07 0.17 0.43 0.27
𝑅̅ = | |=| | = (0.09, 0.12, 0.19, 0.41, 0.20)
0.181 0.11 0.16 0.19 0.41 0.14
0.290 0.07 0.12 0.20 0.43 0.18

𝑃𝑉𝐼𝑜𝑣𝑒𝑟𝑎𝑙𝑙 = [(0.09 × 1) + ( 0.12 × 2) + ( 0.19 × 3) + ( 0.41 × 4) + ( 0.20 × 5)] = 3.54

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5.3.7 Development of the Procurement Vulnerability Model

In developing the procurement vulnerability model, the vulnerability index for each of the constructs is

merged to develop a linear equation model. The technique is adopted due to its ability and flexibility to

allow for different ordinal grading scales (i.e., either 9, 7 or 5-point scale to be used in assessing the

vulnerability index of procurement processes in developing countries, which share similar

characteristics with Ghana. Moreover, another advantageous justification for adopting the linear model

approach is that it is clear, concise, logical, and easily understandable. It, therefore, allows practitioners,

policymakers, anti-corruption institutions, and researchers to adopt or use it without difficulty.

However, prior to the development of the linear model for the evaluation of the overall procurement

vulnerability index for infrastructure projects in Ghana or other developing regions, it was needful to

normalize the individual procurement vulnerability index of the procurement stages in order to equate

the summation of all the constructs to one (Osei-Kyei and Chan 2017). This can enable the evaluation

or the estimation of any of the overall procurement vulnerability index of either a proposed or existing

project irrespective of the grading scale of linguistic terms adopted. Table 5.4 presents the normalized

values of the procurement constructs.

Table 5.4: Stages of the Procurement Process

Code IP Stages Weighting Coefficients Coefficient Symbols

PSC Pre-Contract stage 3.34 0.240 𝐶𝑝𝑠𝑐

CTS Contract Stage 3.77 0.271 𝐶𝑐𝑡𝑠

CAS Contract administration stage 3.30 0.237 𝐶𝑐𝑎𝑠

PCP Post contract phase 3.51 0.252 𝐶𝑝𝑐𝑝

Total 13.92 1.000

Therefore, using the normalized values, the linear equation model of the estimation of the overall PVI

for IP’s in Ghana or other similar developing countries is presented below:

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𝑃𝑉𝐼𝑜𝑣𝑒𝑟𝑎𝑙𝑙 = 𝐶𝑝𝑠𝑐 [𝑃𝐶𝑆] + 𝐶𝑐𝑡𝑠 [𝐶𝑇𝑆] + 𝐶𝑐𝑎𝑠 [𝐶𝐴𝑆] + 𝐶𝑝𝑐𝑝 [𝑃𝐶𝑃] (eqn. 5.15)

= 0.240[PCS]+ 0.271[CTS]+0.237[CAS]+0.252[PCP]

In equation 5.15, the coefficients assigned to each procurement construct correspond with their

respective normalized values and according to the equation. CAS turned out to be the construct with

the highest coefficient value followed by PCP due to their respective high weightings obtained from

the FSE technique.

5.4 Discussion

The indexes obtained from the FSE technique for each of the procurement constructs or stages explicitly

revealed two out of the four constructs to be vulnerable to corrupt practices. They are the contract stage

and post-contract stage. However, some of the vulnerability indexes of the individual activities within

the specified constructs vary. Hence, whereas activities such as the preparation and signing of the

contract may regarded as less vulnerable even though its respective construct (i.e., the contract stage)

is determined to be vulnerable, activities such as the solicitation of tenders is regarded to be one of the

highly vulnerable activities to the incidence of corrupt practices even though its respective construct

(i.e., pre-construct stage) is identified to be relatively less vulnerable. A further discussion on each of

the constructs or stages is subsequently presented.

5.4.1 The Pre-Contract Stage

The pre-contract stage encompasses the definition of the project to be constructed through to the receipt

of tenders (Ruparathna and Hewage, 2013). However, other practices regarding a specific project may

conduct the pre-tender meeting to establish the evaluation criteria that would be employed to assess

tenders received (Lester, 2007). Therefore, CTS1 can be captured under PCS, depending on the project

plan. The susceptibility index recorded at this stage is identified to be relatively low, mainly due to the

limited number of parties involved at this stage as compared to the other constructs. However, despite

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the low-level index recorded by the construct, two activities out of the six under this construct were

identified to be vulnerable to corrupt practices. They are the solicitation of tenders, which also happened

to be the highest susceptible activity under the PCS construct and second highest in terms of the

vulnerability indices of all the 21 activities of the procurement process. At the pre-contract stage, most

of these risks are initiated by the client’s representatives or parties within the sourcing board. In the

public domain, it is often instigated by a government official who serves as representatives (Le et al.,

2014). Government officials are frequently reported to be major contributors to the proliferation of

corruption in the public sector and at this particular stage of the procurement process (Owusu et al.,

2017). The penultimate susceptible activity recorded at this stage is the obtaining of the required

approvals (PCS4) either needed to commence a project’s execution or during execution. A respondent

reported on the proliferation of collusion (regarded as a fraudulent act often characterized by the

undisclosed arrangement among a group of projects’ representatives who meet to conspire to commit a

deceitful act with the primary aim of obtaining illegitimate benefits such as financial gains (Chan and

Owusu, 2017) at this stage. However, this identified shortfall was not attributed to a specific activity

but as a general issue within the pre-contract stage.

5.4.2 The Contract Stage and the Contract Administration Stage

The contract stage was found to be the most susceptible stage of the procurement process to corruption,

as indicated by the respondents. This stage covers activities ranging from the pre-tender meeting to the

evaluation of retrieved bids as well as the selection and the award of the contract to the suitable

contractor. The activities within this construct obtained relatively higher vulnerability indexes, making

the CTS construct the most vulnerable procurement process in developing countries. Some identified

risk factors such as conflict of interest, bid suppression and rotation, cover bidding, cartels, ghosting,

and bid-rigging are manifested at this stage and during the execution of the individual activities (World

Bank, 2013). The causal factors underpinning the incidence of these variants of corrupt acts can be

attributed to project-specific causes such as the lack of proactive mechanisms to stop or limit the

proliferation of corrupt acts over competition in the tendering process, overclose relationship and weak

procurement structures among many others (Owusu et al., 2017; Zhang et al., 2017; Le et al., 2014).

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Due to the high level of susceptibility, both the fuzzy weighting and the model coefficient for the CTS

construct were calculated to be 3.77 and 0.271 (more than a quarter percentage out of four constructs).

These values were identified to be the highest estimated values at both levels. In effect, any development

of anti-corruption measures aimed at expurgating corrupt practices in the procurement process should

consider targeting and expending greater efforts at the contract and post-contract phases as compared

to the other two. This will either save time or create more time as well as allow the maximum output of

the expended efforts and resources.

As explained earlier, the contract administration stage consists of four distinct but interrelated activities.

This stage can also be termed as the post-tender or the contract management stage (Park and Kim 2018).

In descending order of highly susceptible activities, the topmost is the administration of progress

payments with a mean index of 3.39, monitoring of project’s progress, 3.39, issuing of contract

amendments, and the follow up of project delivery with mean indexes of 3.13 and 2.97 respectively.

The overall fuzzy index generated for the construct was 3.30, which indicates moderate or neutral

vulnerability. Given the overall index, it must be emphasized that this particular construct is as well

vulnerable to the incidence of corrupt practices, although moderately. Therefore, in advancing strategic

measures to curb the incidence of corrupt practices should not only consider the vulnerable stages (i.e.,

the contract and the post-contract stages) but also on reducing both the index and the real-life incidence

of the varying forms of corrupt practices at this stage of the procurement process with their respective

causal instigators.

5.4.3 The Post Contract Stage

The post-contract stage was identified to be the second-highest susceptible construct. The respective

overall index and associated model coefficient values were 3.51 and 0.252. This depicts more than 25%

of the overall susceptibility index of the procurement process. The activities within the PCP construct

that render the entire construct vulnerable to the incidence of corrupt practices include the checking of

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proof for delivery and the issuance of the final contractual amendment and the completion of final

audits, among other activities.

Even though there are wide reported cases and studies on the causal factors and the associated effects

of corrupt practices in the procurement process, only a few efforts have been made to research the

specificity of the procurement activities and their relationships with various constructs under the subject

of corruption (Owusu et al., 2017). Consequently, it is extremely challenging to make determinations

and estimations on the degree of corrupt practices (Shan et al., 2015; Ameyaw et al., 2017). This is

because, whereas the practices of corruption are constantly evolving, resulting in new forms and their

associated causal factors, there is an unparalleled development of calculative measures instigated and

enforced to curtail their incidence and effects (Chan and Owusu, 2019; Bowen et al., 2012). In other

words, the current anti-corruption measures or frameworks may not be comprehensive enough to

exterminate the specific forms or corruption at the specific stages of the procurement process.

Therefore, even though there are several policies and stipulations on the entire procurement process that

guide different jurisdictions, studies on measures developed to specifically target the expurgation of the

proliferation of corrupt practices as well as the susceptibility of the procurement process remain limited

(Owusu et al., 2018; Shan et al., 2017). Per the results, not only do the stages or constructs of the

procurement process vary in terms of their degree of susceptibility and the proliferation of corruption

but also terms of the corrupt activities prevalent within the stages (Stansbury and Stansbury, 2008; Chan

and Owusu, 2017). Therefore, this study maintains that the development of anti-corruption measures

and frameworks towards the annihilation of variants of corrupt practices in the procurement process

should be specific and directed towards the individual procurement activities rather than being generic.

Regarding the decision to contract stage, Ferewer et al. (2017) pointed out that while this stage is

intended to facilitate the decision to procure the needed goods, works, and services, there is a high

tendency to deviate from the policy rationale or the actual need to procure. The deviation is therefore

aimed at creating a possible outlet to illegally channel resources or benefits either to an organization or

the parties behind the act (OECD, 2007; Ferewer et al., 2017; Owusu et al., 2017). One key indicator

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that was identified at the requirement definition stage was the tendency for project consultants or public

officials to design the tender to suit a favorite bidder since the procurement process design is formulated

by these parties (Ferewer et al., 2017; Stansbury and Stansbury, 2008; Sohail and Cavil, 2007; Tabish

and Jha, 2008).

As a result, the entire tendering process is secretly distorted. According to Soreide (2002), it is not

uncommon for public officials to decide which person or firm gets invited to tender in a competitive

bidding procurement system. This, results in diverse forms of discriminatory, corrupt practices

including favoritism, cronyism, nepotism, and patronage among other forms of corruption (Chan and

Owusu, 2017; Brown and Loosemore, 2016; Bowen et al., 2012). These forms of corrupt practices often

manifest in the procurement process as a result of some critical causal factors including the complex

nature of projects (Owusu et al., 2017; Krishnan, 2009), fierce competition (Le et al., 2016; Zhang et

al., 2017), complex contractual structure (18;34), overclose relationship (Ling et al., 2014; Chan et al.,

2003), and the inadequate proactive measures to mitigate corruption especially in developing countries

like Ghana (Ameyaw and Chan, 2017). Regarding the remaining phases (i.e., from the contract

administration stage to the post-contract stage), diverse examples triggered by their unique causal

instigators have been identified by different studies in different contexts. For instance, at the pre-

qualification and tender phase, the noted examples which corroborate the views of experts were price-

fixing, bid-rigging, and unreasonably shorter bidding time. Others included inadequate tender

advertisement, ghosting, and influence peddling (Chan and Owusu, 2017; Ameyaw et al., 2017; Le et

al., 2014; Locatelli et al., 2018).

5.5 Chapter Summary

This chapter examined the susceptibility of the procurement process of infrastructure-related projects

in Ghana using the FSE technique. The study aimed to ascertain the extent to which the activities within

the procurement process get exposed to corruption. This is aimed at advocating for more specific and

comprehensive efforts can be taken to address the vulnerability level of each of the activity within the

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process. It also aimed at developing an assessment tool for determining the vulnerability indexes of

projects. The results obtained were not altogether unsurprising as Ghana is regarded by several

measurement indexes such as the corruption perception index (CPI) by the Transparency International

(TI) as one of the neutrally corrupt countries regarding the proliferation of corrupt practices in the public

sector. This study contributes to the body of knowledge on corruption, and particularly in the field of

construction management, by examining the vulnerabilities of projects’ procurement process to the

incidence of corrupt practices in the developing countries. The study further established the indexes for

the individual procurement stages, thereby informing researchers and practitioners about how prone the

stages are regarding corruption and their respective contributions towards the overall estimation of the

vulnerability index. The weightings of the stages were normalized to facilitate the development of the

linear model, which can be adopted to estimate the vulnerability index of existing or proposed projects.

This can enhance the facilitation process of predicting how susceptible projects are to corruption and

the necessary measures to take to limit or expunge corruption in Ghana and other developing countries.

Generally, the most common techniques for measuring corruption adopts the solicitation of the general

perception using the average or mean ratings to indicate the levels of criticalities. This study employed

the FSE technique to examine the vulnerability of corruption in project procurement as well as develop

a linear measurement model for estimating and predicting the vulnerability index of proposed or

existing projects - the first of its kind to be conducted and reported in the field of construction

management. The results also indicate that the activities undertaken at the contract stage should be given

attention to reducing the number of risk indicators that could potentially expose a proposed or an

ongoing project to corruption. This study contributes to the body of knowledge on the ways of

measuring the various indicators of corruption in infrastructure procurement and is, arguably, the first

to employ soft computing techniques (i.e., the FSE approach) to estimate the susceptibility patterns of

the various stages of the procurement process as well as develop an easy to adopt-and-use, yet

standardized approach to facilitate similar estimations in future works. Practically, the model

understandable and can be adopted by practitioners such as policymakers and auditors for detecting and

measuring the vulnerability indexes of various procurement activities and their respective stages of the

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procurement process to the incidence of corruption. The model can as well form the basis for researchers

to develop more comprehensive tools that extend beyond the boundaries of the procurement process for

predicting, measuring, and offering effective measures for corrupt practices right from the definition of

project’s requirements through to project execution to contract close-out. Lastly, this study contributes

to a more deepened understanding of the various means of measuring corruption in the domain of

project procurement and management.

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CHAPTER 6 – MEASURING THE CRITICALITIES OF THE

NEGATIVE CONSTRUCTS OF CORRUPTION AND THEIR
IMPACT ON THE PROCUREMENT PROCESS10

6.1 Introduction

This section examines the criticalities of all the negative indicators within the procurement process.

Thus, while the previous chapter examined how vulnerable the activities and the stages within the

procurement process are to corruption, this chapter examines how the negative indicators take

advantage of the susceptibility attributes of the procurement process and impact the procurement

process negatively. As mentioned earlier, the negative constructs explored in this study are the causal

indicators of corrupt practices, the procurement irregularities of risk indicators, and lastly, the barriers

that inhibit the efficacy of the procurement process. All these constructs are made up of their categories

and variables. However, to ascertain the significance of the contributory effects of these negative

constructs on the procurement process, the relational assessment conducted in this study makes use of

the variables rather than the categories. Thus, the empirical explorations of all the variables within their

respective constructs are examined first and later assessed in relation to the procurement process. The

next sections are therefore discussed in the following order: 1) the causal indicator of corruption, 2)

procurement irregularities or risk indicators of corruption, and 3) the barriers that hinder the efficacy of

the enforced anti-corruption measures.

6.2 Forms of Corruption

As described in the literature review section (chapter3), twenty-eight different forms of corrupt practices

were identified via a thorough literature review. However, twenty-seven were noted to be noticeable in

public projects executed the developing context. The only form of corruption that was excluded in the

case of the developing was 'Guanxi' which is typically affiliated to the Chinese construction public

10
Owusu E. K, Chan A. P. C (2019). Investigating the Criticalities of Corruption Forms in Infrastructure
Projects in the Developing Context. Construction in the 21st Century (CITC). 9-11 September 2019, United
Kingdom.

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sector (Le et al. 2014). Thus, while the experts involved in the pilot survey recommended the deletion

of any factor that does not relate to the context under study, it was also obvious that the term 'guanxi' is

a Chinese term and does not apply to any other context. The twenty-seven forms are presented in Table

6.1

The categories developed in the third chapter of the study were maintained to ensure consistency. As a

result, the five main constructs, in addition to the unclassified conduct, were empirically assessed. They

are; bribery acts, collusive ads, fraudulent acts, discriminatory acts, and extortion acts. All these

constructs are made up of at least three variables, and except the conduct of extortion any act, all the

remaining constructs were noted to have at least two critical variables. The criticalities of the individual

variables are therefore explicated with their respective constructs. The constructs are therefore

discussed in descending order of their criticalities. Lastly, their impacts or influence at the various

sections of the procurement processes of both contexts are presented in Chapter 8.

Table 6.1: Forms of corruption variables

No. Variables Mean N-Value Sig SD Overall Construct

Rank Rank
1. Bribery 4.02 1.00 0.000 1.118 1 1
2. Lobbying 3.81 0.76 0.000 1.069 2 2
3. Facilitation payments 3.79 0.74 0.000 1.175 4 3
4. Kickbacks 3.74 0.68 0.000 1.241 7 4
5. Solicitation 3.66 0.59 0.000 1.280 9 5
6. Influence peddling 3.65 0.57 0.000 1.216 10 6
7. Front/shell companies 3.63 0.55 0.000 1.244 11 1
8. Collusion 3.58 0.49 0.000 1.033 14 2
9. Fraud 3.53 0.44 0.003 1.376 15 3
10. Ghosting 3.52 0.43 0.001 1.198 17 4
11. Dishonesty 3.44 0.33 0.007 1.236 18 5
12. Deception 3.37 0.25 0.020 1.218 20 6
13. Money laundering 3.27 0.14 0.129 1.405 23 7
14. Price fixing 3.81 0.76 0.000 .989 3 1

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15. Bid rigging 3.76 0.70 0.000 1.141 5 2

16. Cartels 3.26 0.13 0.081 1.144 24 3
17. Coercion 3.34 0.22 0.047 1.318 21 1
18. Blackmail 3.29 0.16 0.086 1.311 22 2
19. Extortion 3.24 0.10 0.125 1.224 25 3
20. Client abuse/clientelism 3.19 0.05 0.223 1.239 26 4
21. Intimidations and threats 3.15 0.00 0.327 1.157 27 5
22. Favoritism 3.68 0.61 0.000 1.170 8 1
23. Nepotism 3.58 0.49 0.000 1.181 13 2
24. Patronage 3.44 0.33 0.007 1.223 19 3
25. Conflict of interest 3.74 0.68 0.000 1.130 6 1
26. Embezzlement 3.61 0.53 0.000 1.077 12 2
27. Professional negligence 3.52 0.43 0.004 1.352 16 3

6.2.1 Bribery Acts

Albeit, bribery acts' construct was not anticipated to emerge as the most critical construct especially

when the entire construction and procurement activities and stages are identified and reported to be

plagued with collusive and fraudulent acts (Shan et al. 2017). However, the bribery acts’ construct was

revealed to be the most critical construct among all the forms of corrupt practices. It also emerged as

one of the two constructs with their entire variables identified or noted to be critical. However, unlike

the results ascertained in Chapter 3 regarding the most discussed construct of corruption forms, the

bribery acts construct was identified to be the third most discreet construct. Thus, inasmuch as other

constructs are widely discussed as compared to the bribery construct, the bribery construct was

empirically identified to be the most critical in the context of the deve-loping countries such as Chana

(Owusu et al. 2019). Bribery identified to be the most critical with a criticality index of 4.02. This was

succeeded by lobbying, facilitation payments, kickbacks, solicitation, and influence peddling with their

criticality indexes at 3.81, 3.79, 3.74, 3.66, and 3.65, as indicated in Table 6.1.

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The realization of the bribery acts" construct was not all surprising as the construct and its attributes are

noted to be the most long-standing variants of all forms of corruption (Noonan 1984). Moreover, the

form 'bribery' was assessed by the experts to be the most critical form of corruption, not only under its

construct but also among the entire twenty-seven forms of corrupt practices. The promising and offering

of rewards (most typically, in monetary terms) to entice officials with delegated authority is a common

practice in the Ghanaian public project processes (Ameyaw et al. 2017). And as indicated, this is

expressed in the other forms, such as lobbying (distorting or negatively influencing, the policies of an

institution to one's favor), facilitation or grease payments and kickbacks (Chan and Owusu 2017).

However, inasmuch as these forms have been indicated or identified to be the most critical in the

developing context, their generic criticalities may be argued out to be a common knowledge which does

not contribute that much toward the extirpation of their influence and negative impacts in the modus

operandi of the processes involved in a project. Future studies can examine their criticalities at the

different stages of the project processes and the mechanisms needed to limit the irregularities and the

opportunities that create room for any of these forms of corrupt practices. However, this

recommendation does not only apply to this construct (i.e., the bribery acts’ construct) but all the other

forms of corrupt practices.

6.2.2 Collusive Acts

As indicated in Chapter 3, inasmuch as the construct of collusive acts tends to be a stand-alone construct,

it is viewed by different scholars and reports as the most mentioned form of fraudulent acts. Thus, these

two are correlated with each other as collusive practices fall under the construct of fraudulent practices

(Chan and Owusu 2017). With an overall criticality index of 3.61, three main forms are captured under

this construct, namely price-fixing, bid-rigging, and the influence of cartels. However, two out of the

three forms were revealed to be critical, as assessed by the experts involved in the survey. They are 1)

price-fixing, with a criticality index of 3.81 followed by bid-rigging with a criticality index of 3.76.

Inasmuch as these variables or forms have been indicated by the experts to be critical, one will hardly

find forms like price-fixing or cartels being reported in the news due to the subtle or clandestine nature

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as well as the ingrained endemic culture of corruption within the project-context of most developing

countries such as Ghana (Damoah et al. 2018; Ameyaw et al. 2017). Taking price-fixing as an example,

unless any of the members within the cartel is willing to betray the rest of the team responsible for

fixing prices, it is often difficult or challenging to discover such acts.

It is, however, obvious that these forms of corrupt acts are often prevalent at the pre-contract stage of a

project where tenders are advertised and solicited (Owusu et al. 2019). Thus, measures taken towards

the extirpation of collusive practices may consider not only the generic connotations and incidences but

also the specific stage and activities within which these forms occur. For instance, given that bid rigging

occurs when consenting parties (from both the consulting and contracting teams) meet to settle on the

bid results beforehand, how can this be stopped? Or what mechanism can be established to limit the

opportunities that create room for corrupt practices of this nature to happen? Adopting transparency

mechanisms have been suggested as one of the good approaches to limit such acts. However, the

adoption and modes of applications remain challenging, again due to the clandestine nature of corrupt

practices.

6.2.3 Discriminatory Acts

As the name implies, discriminatory acts refer to the acts of demonstrating prejudicial disparities in

favor of one party against the other (Chan and Owusu 2017). Predominantly in projects, discriminatory

acts take place when projects are awarded unfairly to other unqualified parties as a result of existing

ties or relations. (Chan and Owusu 2017). Again, three different forms were captured under this

construct, namely favoritism, nepotism, and patronage rain out of the three, the first two were identified

to be critical, and patronage revealed to be moderately critical. While other works record cronyism

(showing favoritism to friends and colleagues without following necessary principle or qualifications)

as one of the dominant forms of corruption, this research acknowledges cronyism as a synonym of

favoritism while nepotism deals with the unfair award of a privilege or a benefit to a relative or a friend.

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On a larger scale, cases on the unfair award of contracts due to favoritism or nepotism are not

uncommon in developing countries such as Ghana. In 2017, a case was recorded where a chief executive

officer of a public office awarded eleven contracts to a very close relative (Joy 2018). The question

regarding how the acts of favoritism can be limited also poses a challenge in helping solve the issue of

corruption in general. This is because, as a psychological issue, personal greed has been identified as

the leading cause of corruption despite the creation of systematic and organizational irregularities

(Owusu et al. 2017; Le et al. 2018). And since greed is often ingrained in humans who constitute the

decision-making teams at the government, project, and organizational levels. Moreover, since it is often

difficult to alter the behavioral makeup of a person, an effective proposition to limiting these kinds of

events will be to investigate into a more transparent mechanism that can ensure the effective and

unbiased award of contracts.

6.2.4 Fraudulent and Extortionary Acts

Fraud means deception or deceit. Fraudulent acts can, therefore, be termed as cheating or corrupt acts

where the corrupt party deceives another to obtain an illegitimate favor or other monetary rewards (Chan

and Owusu 2017). Seven different forms were captured under this construct, namely, front/shell

companies, collusion, fraud, ghosting, dishonesty, deception, and money laundering. However, out of

these seven, the first four were identified to be critical, and the last three determined to be moderately

critical. As mentioned, some of the fraudulent acts in their very nature have remained very ruinous and

difficult to extirpate. Typical examples are what have been discussed at the collusive act's section, such

as bid-rigging and price-fixing and others highlighted in this section, such as front companies (i.e., a

shell company without a physical presence but are formed to cover the parent company from liability)

and ghosting. These kinds of acts or practices are heavily predominant in a secrecy or tax haven

jurisdiction, and the primary aim is to shield the actual beneficial owner from taxes, disclosure, or both.

Moreover, the act of bid-rigging has also been noted as one of the causal factors of other forms of

corruption, such as the offering of bribes or facilitation payments (Chan and Owusu 2017). Thus, it can

be argued out that the development and enforcement of adequate measures to check bid-rigging can

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help to either reduce or eliminate the incidence and proliferation of some of the critical forms at both

the pre-contract and the contract stages of the procurement process where all the opportunities and

possibilities or rigging the bid process is possible.

6.2.5 Unclassified Acts (Professional Malfeasance Acts)

This construct contains stand-alone variables. Thus, as explicated at the literature review section, the

construct was labeled unclassified because a common name for this construct is yet to be developed.

Three variables were captured under this construct, and they were all revealed to be critical in the

developing context. According to the rating of the experts, the three variables captured under this

construct together with their criticality indexes are 1) conflict of interest being noted as the most critical

variable under this construct with a criticality index of 3.74 2) embezzlement with a criticality index of

3.61 and 3) professional negligence also with a criticality index of 3.52. Conflict of interest, which is

reported to be a common practice in the developing context, was identified to be the most critical CF

within this construct (Owusu and Chan 2019). According to ACD (2013), conflict of interest

encapsulates three core elements namely 1) the primary interest (what needs to be achieved for the

client), 2) the secondary or private interest (the interests of the individual or party offering services to a

client which often creates room for the conflict and 3) the conflict itself.

Thus, given these three elements, a conflict of interest can occur in a scenario where a contractor

responsible for executing a public project (a primary interest) compromises on either the allotted time

or budget for completion to satisfy his interest (secondary interest). There are situations where more

often than not, the conflict noes not necessarily compromise of the primary interest as indicated in the

given analogy by rather creates a situation where the need for getting the primary interest gets

abandoned or neglected (ACD 2013). Inasmuch CFs such as conflict of interest may not necessarily

engage all the three most active players of corruption (i.e., the demand side, the supply side, and the

condoning side), there is the need to determine possible areas of construction activities or processes that

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may be susceptible to the incidence of conflict of interests in order to draw proactive mitigation

strategies to limit their incidence (ACD 2013; Le et al. 2014b; Owusu et al. 2019).

The other forms captured under this construct, namely embezzlement and professional negligence, share

some common characteristics with conflict of interest in that all the three classes of corrupt parties are

not supposed to be present for these forms of corruption to occur. In essence, one party (the corrupt

party) is the key player in all three forms of corruption captured under this construct. For instance,

unlike bribery, collusive and discriminatory acts where there should be at least two consenting parties,

the forms under this construct epitomizes the misappropriation of power by just in an individual with

either absolute or delegated authority. In the instance of embezzlement, a single person holding an either

an authoritative or a delegated power (i.e., either project managers or employees) position illegally uses,

misappropriates, or traffics the resources entrusted in his care but intended for completing the project

for his personal interest (TI 2019). Again, similar to the conflict of interest, the acts of embezzlement

also distort or compromise on the actual intended purpose of the projects’ resources (TI 2019). The

same goes for professional negligence, where a careless act of a professional creates a vulnerable room

for the intended purpose of project resources to be misappropriated (Chan and Owusu 2017). However,

unlike the first two variables where the actors or professionals involved are mostly intentional about

engaging in such acts, professional negligence can either be intentional or unintentional. Thus, the

development of effective measures to curb the incidence and proliferation of these forms may consider

not only the intended negative acts from the professionals but also the proactive measures to extirpate

or mitigate the unexpected shortcomings of professionals that carry the potency of distorting any of the

processes involved in a project.

6.2.6 Extortionary Acts

Extortionary acts that can be defined as forceful practices of obtaining illegal favors, rewards, or gains

ranked last among the other constructs in this section. Since it was noted as one of the constructs with

at least five variables, none of the variables was identified to be critical. Simply put, while corruption

remains a critical problem and concern in the developing world, the results indicate that the nature of

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corrupt acts prevalent in the developing contexts is sometimes subtle rather than forceful. The variables

captured under this construct are coercion, blackmail, extortion, client abuse/clientelism, intimidations,

and threats with their criticality indexes revealed to be moderate within the range of 3.15 and 3.34.

Moreover, the power balance that exists among the various parties forming the project team

limits the opportunity for a project party to forcefully abuse his delegated authority even though he can

secretly abuse it. Thus, the results are seen to be unsurprising as extortionary cases are uncommon in

some parts of the developing context such as Ghana and are also hardly reported in the news. However,

despite the low rates of criticalities recorded by the individual variables, reported measures that can

increasing limit the incidence and proliferation of such acts are: 1) continual raising of awareness of

corruption and one’s rights in a contractual environment, 2) proactive administrative measures to

extirpate the creation of opportunities for such acts and 3) reactive measures to extend necessary charges

and due penalties for such acts (Owusu et al. 2018). The criticalities of the individual constructs have

been presented in Fig. 6.1.

Criticality Index (CI) for the Corruption Forms

3.9
3.8
3.7
3.6
3.5
3.4
3.3
3.2
3.1
3
2.9
Unclassified Descriminatory Extortionary
Bribery Acts Collusive acts Fraudulent Acts
Acts Acts acts
CI 3.78 3.62 3.61 3.57 3.48 3.24

Figure 6.1: Graphical presentation of the criticalities of Corruption Forms Constructs

6.3 Causal Factors of Corruption

As explained in chapter 3, the causal factors of corruption refer to the causal agents that instigate or

give rise to corruption. This section of the chapter, therefore, aims to examine the criticality of the

causal factors of corruption in infrastructure-related works and their respective impacts on the

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procurement process. Following an extensive review (Chapter 3), 38 causal factors were examined first

to highlight their levels of criticalities, and second, reveal their impact throughout the procurement

process made up of 21 activities captured under four stages. The experts involved in the survey were

asked to rate the criticality of the causal factors. The 38 individual variables are captured under five

main categories, namely Psychosocial-Specific Causes (PSSC), Organizational-Specific Causes,

Statutory-Specific Causes (SSC), Regulatory or Legal-Specific Causes (RSC) and Project-Specific

Causes (PSC). Table 6.1 is presented to give an overall summary of the variables and their respective

constructs. This section aims to make a theoretical contribution to the scholarship of construction and

project management-related scholarships by offering a deepened understanding of corruption-related

studies regarding the critical causal factors that distort the construction-related processes. Additionally,

the study reveals the critical activities and stages of the procurement process that are affected most by

the established causal factors. Practically, the findings of this study are highly relevant to the project

stakeholders, policymakers, anti-corruption institutions, and activists in developing countries as it

informs them about the critical causal factors within the procurement process to expurgate. It also

informs them about the vulnerable stages of the procurement process that requires necessary

reinforcement to make the entire process resilient to the pervasiveness and impacts of corruption.

Table 6.2: Criticalities Estimations of the corruption causal variables

Code Variables Mean N-V OR CR Criticality
PSSC Psychosocial-Specific Causes (PSSC) 3.61 High
CC 1 Personal greed 3.92 1.00 1 1 High
CC 6 Over close relationship 3.71 0.77 6 2 High
CC 9 Negative role models 3.66 0.71 9 3 High
CC 14 Poor professional ethical standard 3.60 0.64 14 4 High
CC 35 Feeble semblance of public interest 3.16 0.16 35 5 Moderate
OSC Organizational-Specific Causes 3.43 Moderate
CC 2 Inadequate sanctions 3.77 0.83 2 1 High
CC 11 Lack of a positive industrial climate 3.61 0.66 11 2 High
CC 12 Poor documentation of records 3.61 0.66 12 3 High
CC 15 Delaying the payment of workers" salaries 3.56 0.60 15 4 High
CC 20 Over competition in tendering process 3.50 0.53 20 5 High
CC 23 Low wage level 3.50 0.53 23 6 High

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CC 27 Economic survival 3.40 0.42 27 7 Moderate

CC 30 Complexities of institutional roles and functions 3.29 0.30 30 8 Moderate
CC 32 Absence of effective and responsible administrative 0.27 32 9 Moderate
3.26
systems
CC 33 Fierce competition 3.24 0.24 33 10 Moderate
CC 38 The nature of corruption being a secret activity 3.02 0.00 38 11 Moderate
SSC Statutory-Specific Causes (SSC) 3.58 High
CC 4 Lack of coordination among Government departments 3.71 0.77 4 1 High
CC 5 Inappropriate political interference 3.71 0.77 5 2 High
CC 18 Subjecting workers to Job insecurity, especially in 0.56 18 3 High
3.52
government and public enterprises
CC 19 Transition of government 3.52 0.56 19 4 High
CC 25 Appointment of a local representative who acts on 0.48 25 5 High
3.45
behalf of the firm to obtain contracts
RSC Regulatory or Legal-Specific Causes (RSC) 3.48 High
CC 3 Flawed regulation system 3.74 0.80 3 1 High
CC 7 Lack of legal awareness 3.69 0.74 7 2 High
CC 10 Insufficient legal punishment and penalties 3.66 0.71 10 3 High
CC 21 Multifarious license or permits 3.50 0.53 21 4 High
CC 24 Absence of project anti-corruption systems 3.48 0.51 24 5 High
CC 26 Absence of control mechanism 3.44 0.47 26 6 Moderate
CC 29 Deficiencies in rule and laws 3.29 0.30 29 7 Moderate
CC 31 Deregulation in the public construction 3.27 0.28 31 8 Moderate
CC 34 Weak procurement/contractual structures 3.23 0.23 34 9 Moderate
PSC Project-Specific Causes (PSC) 3.44 High
CC 8 Lack of rigorous supervision 3.69 0.74 8 1 High
CC 13 Lack of pro-active steps by funders to limit corruption 0.64 13 2 High
3.60
on projects
CC 16 Asymmetric information amongst project parties 3.55 0.59 16 3 High
CC 17 Great project complexity 3.55 0.59 17 4 High
CC 22 Insufficient transparency in the selection criteria for 0.53 22 5 High
3.50
tenders
CC 28 Lack of frequency of projects 3.30 0.31 28 6 Moderate
CC 36 Complex contractual structure 3.15 0.14 36 7 Moderate
CC 37 The nature of infrastructure 3.14 0.13 37 8 Moderate
Note: N-V represents Normalized Values; OR represents overall rank; CR represents construct rank.

The Psychosocial-Specific Causes (PSSC) in this context simply refers to the relational interactions of

social and psychological factors and the outcome or influence in a given setting (e.g., the workplace) or

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on the modus operandi of a work execution (Greitzer 2013; Heiser 2001). A recent review conducted

by Owusu et al. (2017) identified the variables within this construct to be the most discussed in the

extant scholarship of construction project management. The results obtained in this study do not deviate

from the position regarding the criticality of this construct as it was evaluated to be the most critical

construct with a mean index (MI) of 3.61. In agreement with the construct criticality, the respondents

evaluated the variables under this construct to be the most pressing causal factors of corruption in

construction projects. Thus, reechoing the need to pay more critical attention in examining the entire

construct and the variables within it to develop more stringent anti-corruption tools and measures potent

and resilient enough to extirpate their criticalities, particularly in the developing context. From the

estimation of the experts, four out of the five causal factors captured under this construct were noted to

be critical. Personal greed (CC1) was evaluated as the most critical variable among all the 38 causal

factors, with a mean index (MI) of 3.92. The remaining critical factors were over-close relationship

(CC6), Negative role models (CC9), and poor professional, ethical standard (CC14) with their

respective MI as 3.71, 3.66, and 3.60.

Statutory-Specific Causes (SSC) came second to PSSC as the second most critical construct in the

developing context, with an overall MI of 3.58. According to Owusu et al. (2017), SSC is government-

driven forces that instigate the incidence and proliferation of corruption. Given that the definition of

corruption is often attributed to the misappropriation of a State’s resources, the government is seen as

the most vulnerable areas to high-level corruption (Johnston 2017). Albeit this construct was identified

to second most critical, unlike PSSC, all the five variables captured under this construct were identified

to be critical. With the first two variables obtaining the same MI of 3.71, the respondents revealed that

the inappropriate interferences political influences in public projects (CC5) and the lack of coordination

among government departments responsible for a given public project (CC4) were noted as the most

critical factors under this construct. The remaining variables which were subjecting public workers to

Job insecurity, especially in government and public enterprises (CC18), change of government (CC19)

and the appointment of unqualified local representative who acts on behalf of the firm to obtain

contracts (CC25) obtained MI of 3.52, 3.52 and 3.45 respectively.

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Anytime there is an ethical dilemma regarding a person and his or her environment or the state, the

usual link that commonly found between these two subjects is the compliance to law or regulations

binding them. It was, therefore, unsurprising to identify regulatory or legal-Specific Causes (RSC) as

the third critical construct among the five with a construct MI of 3.48. Regulations simply refer to acts,

directives, norms or principles for guiding a process or an object to conform to the acceptable standards

required. Thus, regulatory-specific causes can be defined as loopholes in guiding principles or the

partial inclination to the demands of a regulation that result in corruption in the long run. The RSC

construct is made up of nine unique variables, and out of these nine variables, five were evaluated to be

critical, and the remaining four to be moderately critical. With flawed regulation system (CC3)

emerging as the most critical variable with an MI of 3.74, the other four critical RSC variables were 1)

the lack of legal awareness either in a project setting or a contractual environment (CC 7) with an MI

of 3.69, 2) insufficient legal punishment and penalties (CC10) with an MI of 3.66, 3) multifarious

license or permits (CC21) obtaining an MI of 3.50 and 4) the absence of project anti-corruption systems

(CC24) with an MI of 3.48.

Even though most projects in the developing world are often susceptible to corruption due to the causal

factors captured under the construct of Project-Specific Causes (PSC) as well as the other causes

identified under the other constructs, the PSC construct was evaluated or revealed by the respondents

to be moderately critical with an MI of 3.44. PSC can be defined as the project-oriented loopholes that

instigate corruption during the planning, procurement, and management of construction projects (Le et

al. 2014; Owusu et al. 2017). With an overall number of 8 causal factors captured under the PSC

construct, five were revealed to be critical. They are the 1) the lack of meticulous project supervision

(CC8) with an MI of 3.69, 2) lack of pro-active steps by funders to limit corruption on projects (CC13)

scoring 3.60, 3) the distortion in information flow or symmetric information amongst project parties

(CC 16) with a criticality index of 3.55, 4) the complexities involved in project and contractual

structures (CC17), with an MI of 3.55 and 5) the lack of transparency in the selection criteria for tenders

(CC22) with an MI of 3.50. The type and location of a project often influence the degree of its

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vulnerability the corruption. Thus, complex projects and contractual systems in the developing context

tend to be highly vulnerable to corruption as compared to small and simple projects and projects

undertaken in a developed region with a more formidable structure to limit corruption (Wai 2006; Chan

and Owusu 2017). The last and least evaluated construct among the five was Organizational-Specific

Causes’ (OSC) construct with an MI of 3.43. OSC refers to the causal factors of corrupt practices that

stem from both the internal and external structures of either a public or private organization or

institution. Simply put, they are negative organizational influences that instigate and breed corruption

in an organizational setting (Owusu et al. 2017). Comparatively, this construct had the highest number

of variables (i.e., 11 unique variables) and the highest number of critical variables (i.e., six variables).

However, it was evaluated to be the least because of the lower scores obtained by the other five

variables. From the topmost critical variable under this construct, the practice of inadequate sanctions

(CC2) with an MI of 3.77 was evaluated by the respondents as the most critical followed by the lack of

a positive industrial climate (CC 11) with an MI of 3.61 and the poor documentation of records (CC 12)

scoring 3.61. The remaining three critical variables were suspending or delaying the payment of

workers’ salaries (CC15) scoring 3.56, over the competition in tendering process (CC20) scoring 3.50

and low wage level (CC23) also scoring 3.50.

Causal Constructs' Criticalities

3.65

3.60

3.55
Criticality Index

3.50

3.45

3.40

3.35

3.30
Psychosocial- Organizational- Statutory-Specific Legal-Specific Project-Specific
Specific Causes Specific Causes Causes Causes Causes
Index 3.61 3.43 3.58 3.48 3.44

Figure 6.2: Graphical presentation of the criticalities of Corruption Causal Constructs

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6.4 Procurement Irregularities11

This chapter aims to bridge the gap identified in the identification and examination of the risk indicators’

construct, especially in the context of developing countries. Moreover, while the identified irregularities

are identified to be critical in the developing context, their contribution to the incidence of corruption

remains hypothetical. Therefore, aside bridging the identified gap by exploring the procurement

irregularities in the context of the developing region, a further step is taken to test the hypothesis of

their contribution to the incidence and proliferation of corruption within the procurement process. Thus,

this chapter intends to explore the construct of corruption risk indicators also identified as irregularities

by Tabish and Jha (2011) and corruption vulnerabilities by Le et al. (2014) in the context of developing

countries using Ghana as the geographical point of focus. To realize the aim, three objectives are

established. They are: 1) identify the corruption risk indicators or irregularities that are conjectured to

render the infrastructure procurement process to corrupt practices; 2) examine the criticalities of the

identified irregularities with their associated constructs and 3) test the hypothesis regarding the

attribution of corruption incidence to the identified risk factors.

The identification of the criticality indexes of both individual variables is aimed at contributing to both

theory and practice. Theoretically, as it has been highlighted earlier, this chapter does extend not only

the theoretical base of corruption-related research regarding the subject matter but also bridges the

research gap in this area in the developing region. That is, this section of the study is arguably the first

empirical research to be conducted in this area. Moreover, it contributes to a deepened understanding

of the subject matter of corruption in general and on the subtopic of corruption irregularities in

particular.

Thus, it facilitates and adds to a deepened and more holistic understanding of the subject matter of

corruption and the various constructs that contribute to the prevalence of corruption. Practically, this

11
Owusu, E. K., Chan, A. P., Hosseini M. R., Nikmehr B., (2020). Assessing Procurement Irregularities in the
Supply-Chain of Ghanaian Construction Projects: A Soft-Computing Approach. Journal of Civil Engineering
and Management. Manuscript ID. SCEM-2019-0215.R1 (In Press).

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 Chapter 6 – Impact of Corruption on the Procurement Process

chapter contained vital information relevant to industry practitioners, anti-corruption activists or

advocates, researchers, and procurement board executives in the developing context (particularly in the

context of Ghana). The information provided is not only aimed at drawing the attention of the mentioned

parties to the procurement irregularities prevalent in the supply chain of procurement process but also

to notify them about their degree of criticality regarding their probability and severity of the incidence

and impact. Moreover, it aims at contributing to the development of a more holistic and stringent ACMs

aimed at estimating not only the forms of corruption and the respective causal factors but also the

potential irregularities possible of distorting the order of the procurement process. Lastly, this chapter

is also intended to benefit researchers as it demonstrates that the application of soft computing

techniques (i.e., fuzzy evaluation method) to examine the irregularities prevalent within the

procurement process. It serves as a source of reference to continue this trend of corruption-related

research in different fields.

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Table 6.3: Factor Analysis of the variables (Irregularities)

No Variables for Procurement Irregularities Probability Severity* Overall
Mean SD Sig N-V Rank Mean SD Sig N-V Rank SI Impact N-V
1 Institution not following correctly the public 3.58 1.049 .000 0.58 8 3.66 1.007 .000 0.68 5 13.10 3.62* 0.61
procurement Acts in terms of obtaining minimum
quotations, exceeding authorization threshold limits
and unauthorized sole sourcing of suppliers
2 Lack of adequate supervisory control over 3.39 1.014 .004 0.30 16 3.44 1.182 .005 0.30 12 11.66 3.41 0.25
procurement transactions and management
3 Payments for uncompleted works 3.85 .973 .000 0.97 2 3.84 1.027 .000 1.00 1 14.78 3.84* 1.00
4 Non-application of sanctions 3.61 1.030 .000 0.62 7 3.48 1.184 .002 0.37 6 12.56 3.54* 0.47
5 Poor supervision of subordinate officers 3.56 1.182 .000 0.55 10 3.48 1.184 .002 0.37 6 12.39 3.52* 0.44
6 Disregard for public procurement Acts regulations 3.65 1.202 .000 0.68 5 3.48 1.225 .003 0.37 6 12.70 3.56* 0.51
7 Procurement not taken on ledger charge 3.63 1.134 .000 0.65 6 3.31 1.049 .025 0.07 16 12.02 3.47* 0.35
8 The procurement of goods and services by 3.47 1.170 .003 0.42 14 3.69 1.088 .000 0.74 3 12.80 3.58* 0.54
management without adequate resources to
procurements committee of the various public
institutions, which diverges from the provided
regulations
9 Variations to contract 3.45 .986 .001 0.39 15 3.39 1.136 .009 0.21 13 11.70 3.42 0.26
10 Outstanding Mobilization advances owing to non- 3.18 1.248 .267 0.00 18 3.37 1.059 .008 0.18 14 10.72 3.27 0.00
observance of stipulated regulations
11 Fragmentary procurement 3.32 1.184 .036 0.20 17 3.48 1.004 .000 0.37 6 11.55 3.40 0.23
12 Little evidence of value for moneys spent 3.56 1.168 .000 0.55 10 3.27 1.162 .068 0.00 18 11.64 3.41 0.25
13 Sourcing of proforma invoices from the same 3.87 1.079 .000 1.00 1 3.77 1.165 .000 0.88 2 14.59 3.82* 0.96
supplier
14 Overpayment of purchases 3.58 1.124 .000 0.58 8 3.35 1.202 .023 0.14 15 11.99 3.46* 0.33
15 Lack of proper co-ordination among key 3.73 1.104 .000 0.80 3 3.68 1.037 .000 0.72 4 13.73 3.70* 0.75
departments of the company and apparent internal
control weaknesses reconciliation on Association
16 Lack of consistent monitoring and review of 3.66 1.055 .000 0.70 4 3.45 1.097 .002 0.32 11 12.63 3.55* 0.49
procurement activities
17 Lack of whole-of-government and corporate 3.50 1.170 .001 0.46 13 3.48 1.141 .001 0.37 6 12.18 3.49* 0.39
procurement planning for significant purchases
18 Lack of audit trails or verification data 3.52 1.264 .002 0.49 12 3.31 1.139 .038 0.07 16 11.65 3.41 0.25
Note: SD = Standard Deviation; Sig = Significance; N-V = normalized value; SI = Significance Index

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6.4.1 Developing the Constructs for the Risk Variables

Following the construct developed by the FA technique, the eighteen variables were captured under four

constructs. They are administrative-specific irregularities, procedural irregularities, compliance

irregularities,, and lastly, contract monitoring irregularities, which can also be regarded as probing-specific.

The only studies that have been conducted to capture this construct either partially or fully were conducted

in India and China by Tabish and Jha (2011) and Le et al. (2014), respectively. Interestingly, this construct

stands to be unique, unlike the others in the sense that it is context-specific (Owusu et al. 2019). For

instance, in the case of the forms, the definition of bribery act in a given context is somewhat similar if not

the same in other contexts even though their criticalities may differ from one context to another. Similarly,

personal greed as a cause of corruption is a generic causal factor that is bound to or can happen in any part

of the world. However, corruption risk indicators are bound to happen in a more specific context as a result

of the irregularities posed to the context. Therefore, during the exploration of this construct in the Indian

procurement sector, the authors made use of the chief technical examiner's reports of India to extract the

identified irregularities. The factors represented the contextual condition of India (Tabish and Jha 2011).

Therefore, the development and enforcement of the needed strategic efforts to extirpate these irregularities

would be context-specific since they are influenced by the identified context-specific irregularities.

In the second study (i.e., Le et al. 2014) conducted in China, the authors emphatically stated that the

variables used in the study were adapted from the study of Tabish and Jha (2011). Justifications for adaption

were attributed to shared socio-economic and demographic commonalities such as population and

economic growth among others. Therefore, even though out of the 61 procurement irregularities identified

by Tabish and Jha (2011), only 24 factors were considered in the study of Le et al. (2014) because they

were the only variables that were common to both contexts. However, there were some commonalities in

their respective constructs developed even though the two studies had uneven sets of variables (i.e., 61 in

the case of India and 24 in the case of China), the identified variables were captured under five similar

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constructs in both studies. The constructs were: transparency irregularities, professional standards, fairness,

contract monitoring, and procedural irregularities.

This section of the study, therefore, followed a similar suit in naming the constructs since it is intended to

contribute to previous studies as well as address the gaps identified in the earlier studies. Even though

eighteen variables were captured under the study, they were categorized into four constructs by the FA

technique as listed in the previous paragraphs. Therefore, while the procedural and contract monitoring

constructs were identified in the previous studies, the other two constructs that evolved in this study were

administrative and compliance irregularities. Therefore, even though the theoretical constructs in previous

research influenced the labeling of the developed constructs, the second justification to the labeling of the

constructs was that they were named by extracting the identical or common themes that existed among the

variables (Owusu et al. 2019). The constructs developed in this chapter are discussed in the subsequent

sections in their order of criticalities after the FSE results.

Table 6.4: Factor Analysis of the variables (Irregularities)

Code Variable C1 C2 C3 C4 Initial Extra
ction
Administrative-specific
ASI1 Lack of whole-of-government and corporate .771 1.000 .646
procurement planning for significant
purchases
ASI2 Sourcing of proforma invoices from the same .760 1.000 .655
supplier
ASI3 Little evidence of value for money spent .648 1.000 .637
ASI4 Lack of proper coordination among key .617 1.000 .473
departments of the company and apparent
internal control weaknesses reconciliation on
Association
ASI5 Non-application of sanctions .548 1.000 .539

Procedural-Irregularities
PII1 Fragmentary procurement .797 1.000 .754
PII2 Procurement of goods and services by .766 1.000 .625
management without adequate resources to

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procurements committee of the various public

institutions, which diverges from the provided
regulations
PII3 Procurement not taken on ledger charge .624 1.000 .639
PII4 Variations to contract .592 1.000 .482

Compliance Irregularities
CII1 Institution not following correctly the public .728 1.000 .582
procurement Acts in terms of obtaining
minimum quotations, exceeding authorization
threshold limits and unauthorized sole
sourcing of suppliers
CII2 Disregard for public procurement Acts .689 1.000 .563
regulations
CII3 Poor supervision of subordinate officers .680 1.000 .597
CII4 Payments for uncompleted works .482 1.000 .467

Contract monitoring Irregularities

CMI1 Outstanding Mobilization advances owing to .758 1.000 .780
non-observance of stipulated regulations
CMI2 Lack of adequate supervisory control over .689 1.000 .687
procurement transactions and management
CMI3 Overpayment of purchases .645 1.000 .509
CMI4 Lack of audit trails or verification data .567 1.000 .608
CMI5 Lack of consistent monitoring and review of .515 1.000 .660
procurement activities
Eigenvalues (EV) 5.603 2.145 1.729 1.425
Variance (VA) 31.131 11.919 9.605 7.917
Cumulative Variance (%) (CV%) 31.131 43.049 52.654 60.572
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.714
Bartlett's Test of Sphericity Approx. Chi-Square 464.8
df 153
Sig. .000

6.4.1.1 Compliance irregularities

To comply means to adhere or conform or act in accordance with orders rules or other regulatory

stipulations (Cambridge Dictionary 2018). The mention of compliance has evolved in several corruption-

related studies, especially in the context of anti-corruption research. As the name implies, compliance in

the context of anti-corruption studies connotes a responsive and proactive conformity to anti-corruption

stipulations aimed at creating a corrupt-free environment (Owusu et al. 2018). Worthy et al. (2017)

presented the forms of compliance by which public bodies, among others may comply with regulatory

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stipulations. From the highest form to the least, they are concordance, full-compliance, partial-compliance,

lesser-compliance, and non-compliance. The importance of this construct is attributed to the fact that the

development and enforcement of anti-corruption measures need compliance mechanisms in place to ensure

the effectiveness of the ACMs or ensure that the stipulated measures are being adhered to (Owusu et al.

2018).

However, this study identified one of the contextual irregularities in public procurement to be compliance

risks. In effect, the construct reveals the criticality index of the potential loopholes that manifest in the form

of compliance irregularities. At the construct level, the compliance irregularities construct was identified to

be the most critical construct with an overall impact index of 3.64 with both of its probability of incidence

and severity indicators respectively estimated to be 3.66 and 3.62, respectively. Four variables were

captured under this construct. It was unsurprising to note that the non-compliance to the public procurement

act coupled with limited or non-compliance with contractual stipulations regarding payment of non-

executed works were noted as the top two critical irregularities as compared to the other two. While there

are standardized procedures to facilitate the procurement process which is embedded in the public

procurement act, not only did the A-G indicated this to be one of the most critical concerns in the public

domain, the experts also highlighted this to be one of the most critical irregularities that have the potential

to create room for corruption to flourish and also cause other financial, performance and standardization

irregularities in a given public domain. The other critical concerns are the disregard for public procurement

act and regulations and the payment for uncompleted works. Similar to the first to irregularities, the issue

of this disregarding stipulated act is antonymous to compliance. Thus, in the first scenario, whereas public

procurement officials may choose to follow some parts of the procurement policies (similar to partial

compliance as defined by Worthy et al. 2017), the cause of disregard is directly synonymous to non-

compliance. As such, the harm that this specific irregularity may lead to is likely to be greater than in the

former case. Similar compliance-related irregularities were identified under the regulatory irregularities in

the studies of Tabish and Jha (2011), indicating the criticality of this factor and the need to extirpate its

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incidence, influence, and proliferation in the procurement process as well as other activities involved in

public procurement.

6.4.1.2 Administrative Irregularities

Administrative irregularities can be defined in this context as the potential organizational risks that transpire

due to weakened internal and external structures, depreciated organizational morality, professional and

ethical standards within an organizational setting. This endangers the workflow, productivity, and overall

institutional structures to two known and unknown corruption incidences (Owusu et al. 2017; Le et al.

2014). Analogous to the compliance irregularities construct, the administrative irregularities construct was

identified to be one of the critical constructs made of 5 individual irregularities. Even though past studies

have not captured the administrative irregularities as a construct, both the studies of Tabish and Jha (2011)

as well as Le et al. (2014) identified professional standards irregularities as one of the five pressing

constructs identified in the context of India and China respectively. However, some of the variables

captured under the construct of professional standards irregularities are somewhat similar to those captured

under administrative irregularities in this chapter. For instance, limited disclosure of money spent,

unrealistic preparation of sound cost estimates, and unrealistic high rated or highly valued items that are

not adequately verified or monitored existed under a common construct of all the three mentioned studies.

However, the remaining variables captured under this construct included sourcing or procuring of proforma

invoices from the same supplier with a criticality impact of 3.82, and the lack of proper coordination among

key departments and personnel within an organization with a criticality impact index of 3.70. The non-

application of sanctions to unprincipled and undisciplined work ethics and the lack of whole governing

body or management and corporate procurement planning for significant purchases also with a critical

impact index of 3.49 were also captured. According to the A-G, these are critical administrative

irregularities that have ensued within the administrative structures of the public procurement board for an

appreciable period.

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Moreover, the experts could not agree more to this concern. This justifies the criticality of the loopholes

identified within the administrative structures of the public procurement system within the developing

context and the need to extirpate these irregularities to limit the incidence of other unlikely events such as

corruption among others. Lastly, on this construct, a recent study conducted by Owusu et al. (2018) on the

measures established to extirpate corrupt practices in construction project management captured one of the

constructs as administrative measures out of 6 constructs. This chapter, therefore, recommends that

practical deduction can be made from the findings of Owusu et al. (2018) as it remains the most up-to-date

review study of anti-corruption measures in this context. It would as well be needful for researchers and

other anti-corruption advocates to draw strategic measures specifically skewed to limit or extirpate the

incidence and impact of administrative irregularities in the public procurement system of developing

countries.

6.4.1.3 Procedural Irregularities

Procedural irregularities represent one of the two constructs in this study captured by both studies of Tabish

and Jha (2011) and Le et al. (2014). The word procedural simply means an established, usual, or an official

way by which a task is executed (Cambridge Dictionary 2018). It is the adjectival form of the noun

'procedure' which can also mean method, plan, program, policy, or transaction. Any of these words aim at

commencing and completing a specific task through an acceptable sequence. Thus, any form of risk posed

to any task encapsulated in the process of the sequence of getting the specified work done can be termed as

procedural irregularities. In the context of public procurement, the term lends itself to the distortion, risk,

or threat posed against the established modus operandi of transacting an official or established procurement

process. The explication of this term is needful to establish a common ground to discuss the variables

captured under this construct. Tabish and Jha (2011), however, defined this term from the perspective of

non-compliance, which has already been captured in our previous construct. While the concept of

compliance can be captured under this construct, it must be emphasized that procedural irregularities can

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manifest in different forms other than non-compliance. For instance, per the four variables captured under

this construct in this study, the act of fragmentary procurement or variation to a contract may not necessarily

be non-compliance to established procurement processes but can, however, pose a threat to the supply chain

of the procurement process. Variations to contract take place as a result of different causal factors, including

force majeure (Bing et al. 2004). This does not necessarily mean non-compliance to procedural stipulations.

However, if variations to a contract are not effectively handled, they may serve as a threat or susceptible

grounds for corruption to flourish, such as inflation of the amount to cover the varied part of the given

contract (Stansbury and Stansbury 2008). This is one of the rationales for emphasizing the definition of

procedural irregularities. The mentioned procedural irregularities (i.e., fragmentary procurement and

variations to contract) scored 3.40 and 3.42 respectively, which connote moderate criticalities. However,

the severity impact of the fragmentary procurement and the probable impact of the variations to contract

were identified to be critical by the experts. This implies the need for practical rectification measures to

extirpate their respective concerns. However, apart from the two irregularities, the other two instead had

appreciable levels of critical impact indexes. They include procurement not taking on ledger charge and the

procurement of goods and services by management without adequate resources to the procurement

committee of various public institutions, which diverges from the provided regulations. These two

irregularities had their respective impact indexes to be 3.47 and 3.58, respectively, indicating the respective

criticalities. The variables regarding the procurement of goods and services by management without

adequate resources, which as well diverges from provided regulation, can as well be regarded as an

administrative or non-compliance irregularity. This shows that even though some variables are specifically

skewed towards a construct, they can as well be considered under other constructs indicating the

relationship between the variables. There is, therefore, the need to pay critical attention to how the

respective stages within the procurement process can be effectively structured to limit the incidence of these

irregularities or the unlikely outcomes that are bound to happen should the irregularities happen.

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6.4.1.4 Contract monitoring irregularities

The construct of contract monitoring irregularities was as well identified as the second out of the two

constructs that have been captured in the previous studies mentioned (Tabish and Jha 2011; Le et al. 2014).

Again, previous studies defined this construct to be the contractual laxities that ensue as a result of non-

compliance to contractual stipulations or agreement. Therefore, it can be established that this one of the

main limitations of the previous works on this subject matter. That is, attributing almost all the constructs

to non-compliance. However, as established, this study postulates that not all the irregularities emerge or

take place as a result of non-compliance. While non-compliance may be regarded as a direct causal factor

contractual irregularities, it must be emphasized that other forms of irregularities other than non-compliance

can instigate the emergence of new forms.

For instance, the topmost critical variable under this construct, which is the lack of continual stringent

monitoring and the review and evaluation of procurement activities, may not be an issue of non-compliance

as reported in the previous instance. However, as identified by the experts, this variable was revealed to

have high criticality indexes for both the probability and severity indicators. This highlights the need to

raise awareness on the development of stricter contract monitoring mechanisms to extirpate the identified

irregularities. As mentioned, five irregularities were captured under this construct. However, regarding the

remaining four, only one variable was identified to be critical, and that was the overpayment of purchases

with an index of 3.46. The remaining three are I) the lack of inadequate trails or verification data, 2) lack

of adequate supervisory control over procurement transactions and management, and 3) the outstanding

mobilization advances incurred as a result of either limited or non-observance of stipulated regulations.

These variables again can be attributed to administrative flaws, especially regarding the need to verify any

given data on the specifications and any other information of purchases made and the need to ensure

adequate supervisory control on procurement transactions.

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This will enable early detection of both unidentified and unknown irregularities to facilitate the strategy

formulation of effective measures to extirpate them. Again, per the stipulations presented by Worthy et al.

(2017), the use of the term non-compliance as frequently used in past studies is highly debatable. The term

non-compliance refers to zero adherence, according to Worthy et al. (2017). However, there are instances

where the recorded irregularities may instigate or propagate as a result of partial compliance, lack of

awareness, or absolute ignorance of certain demands or stipulations required of them. In such instances, the

primary problem may not be attributed to non-compliance or adherence. Therefore, this section is intended

to inform its audience about the correct use of the term non-adherence due to the relevance of the various

forms of compliance (i.e., from noncompliance to concordance) and the measures required to check the

specificity of the various levels of compliance.

Table 6.5: Overall Descriptors and Hypothesis Validation

No Risk Probability Risk Severity Overall
CT Index LI CE Index LI CE Impact RK LI N-V
ASI 3.66 High 0.26 3.55 High 0.25 √3.66 × 3.55 2 Critical 0.864*
= 𝟑. 𝟔𝟏
PII 3.47 High 0.24 3.48 High 0.25 √3.47 × 3.48 3 Critical 0.273
= 𝟑. 𝟒𝟖
CII 3.66 High 0.26 3.62 High 0.26 √3.66 × 3.62 1 Critical 1.000*
= 𝟑. 𝟔𝟒
CMI 3.47 High 0.24 3.38 Neutral 0.24 √3.37 × 3.38 4 Neutral 0.000
= 𝟑. 𝟒𝟐
Total 14.26 1.00 14.03 1.00
OI 3.57 3.51 √𝟑. 𝟓𝟕 × 𝟑. 𝟓𝟏 Critical
= 𝟑. 𝟓𝟒
LI = Linguistic; CE= Coefficient; RK = Rank; N-V = Normalized Value; OI = Overall Index

With the critical means set at 3.45 to 4.44 and the highly critical index set at 4.45 to 5.0, there were 12 out

of 18 variables that were noted to be critical, and the remaining 6 noted as moderately critical. The most

critical variable was identified to be payment for uncompleted works followed by the sourcing of proforma

invoices from the same supplier. Four constructs emerged after running them under factor analysis. They

included administrative irregularities, procedural irregularities, compliance irregularities, and lastly,

contract monitoring irregularities. However, using the FSE technique to evaluate the criticalities of their

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respective constructs, three were identified to be critical and 1 moderately critical. The most critical

construct was identified to compliance irregularities construct, and the least was contract monitoring. With

the overall criticality index at 3.54, the procurement irregularities were identified to be critical in the

Ghanaian context.

Lastly, regarding the suppositions raised on variables’ contribution to the incidence of corrupt practices,

this study confirmed two constructs to be significantly critical towards rendering the entire procurement

process to the incidence and proliferation of corrupt practices. Thus, despite the criticalities of the

constructs, the normalized values upon which the validity of the four hypothesized statements were based

revealed that the hypothesis regarding ASI and CII were accepted.

6.5 Assessment of the Impact of the Variables on the Procurement Process

This section examines the significant impacts of the individual variables on the procurement process. It

must be emphasized that this section is primarily conducted to show the variables that affect the

procurement process. Thus, aside from the information obtained regarding the susceptibility of the

procurement activities, this section steps the previous results up by showing the real impact of the driving

forces of corruption on the procurement process. It can, however, be postulated that any efforts taken

towards the abatement of the susceptibility levels only addresses the issue of corruption at the vulnerability

assessment level and not at the corruption extirpation level.

Moreover, inasmuch as the analysis conducted in this section represents a two-mode relational analysis, a

higher emphasis is placed on the procurement process since the activities within the process are much more

standardized as compared to the negative drivers of corruption, which are always evolving with new ways

of corrupting the procurement process. Fig. 6.2, therefore, shows a conceptual framework of the relational

impacts of the constructs on the procurement process. The expanded network analysis model is present next

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right after the conceptual model (Fig. 6.3), showing the actual results of the significant relational model of

the impacts of the variables on the activities on the activities of the procurement process.

Figure 6.3: Conceptual illustration of the negative constructs of corruption on the procurement process

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 Chapter 6 – Impact of Corruption on the Procurement Process

Figure 6.4: Network analysis of the negative constructs of corruption on the procurement process.

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 Chapter 6 – Impact of Corruption on the Procurement Process

20.00
DoI NV Linear (DoI) Linear (NV)
19.00
18.00
17.00
16.00
Criticality Impacts on the Procurement Process

15.00
14.00
13.00
12.00
11.00
10.00
9.00
8.00
7.00
6.00
5.00
4.00
3.00
2.00
1.00
0.00
PCS1 PCS2 PCS3 PCS4 PCS5 PCS6 CTS1 CTS2 CTS3 CTS4 CTS5 CAS1 CAS2 CAS3 CAS4 PCP1 PCP2 PCP3 PCP4 PCP5 PCP6

Procurement Process

PP PCS1 PCS2 PCS3 PCS4 PCS5 PCS6 CTS1 CTS2 CTS3 CTS4 CTS5 CAS1 CAS2 CAS3 CAS4 PCP1 PCP2 PCP3 PCP4 PCP5 PCP6
DoI 8.84 9.17 6.45 8.54 7.64 12.21 9.12 6.82 12.46 11.75 13.04 16.58 7.96 9.26 13.10 11.08 12.58 16.14 13.31 14.51 6.18
NV 0.26 0.29 0.03 0.23 0.14 0.58* 0.28 0.06 0.60* 0.54* 0.66* 1.00* 0.17 0.30 0.67* 0.47* 0.62* 0.96* 0.69* 0.80* 0.00

Figure 6.5: Criticality impact of the corruption constructs on the procurement process

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 Chapter 6 – Impact of Corruption on the Procurement Process

Figure 6.3 presents an overarching overview of all the negative constructs explored in this study and their

collective impact on the procurement process. In essence, the figure shows a two-mode relational analysis

between the variables of all the negative constructs and the activities within the procurement process. However,

the emphasis in this section is placed on the procurement process and the activities within the procurement

process since that is the main area under investigation. Detailed explication regarding the individual constructs

has been presented in other sections of the study. This section is therefore devoted to the dynamics or relational

effects of the constructs of corruption on the procurement activities and stages. In general, eleven out of twenty-

one stages were noted to be highly impacted by the constructs. Among the eleven impacted one activity was

identified under the pre-contract stage, three out of five activities of the construct stage, two out of four at the

contract administration stage, and five out of six activities at the post-contract stage.

Thus, none of the stages was exempted from the criticalities of the constructs of corruption. At the pre-contract

stage where most of the preliminary works (building and contract works) such as defining the outlines and

requirements of the proposed projects and obtaining necessary approvals among others were identified to be the

stage with the least critical impact. Per the analysis, the only activity that was deified to be significantly impacted

by the corruption constructs was PCS6 (that is, the receipt of leaders). While PCS4 (obtaining necessary

approvals) and PCS5 (soliciting tenders) were noted as the most susceptible activities to corrupt practices, the

network analysis revealed PCS6 (even though not as vulnerable as PCS4 and PCS5) as the most significant in

terms of the constructs' criticalities at the pre-contract stage. It must be emphasized that the elimination or

inclusion of any of the variables or associated construct of corruption may alter the overall results regarding the

impact. However, the individual examinations were not conducted since the criticalities of all the variables had

been previously examined.

Moving on to the next stage (i.e., the contact-stage), the three most impacted activities based on the normalized

values were CTS3 (the selection of a contractor), CTS4 (awarding of contact) and CTS5 (the preparation and

signing of contract). Moreover, similar to the findings on the vulnerability patterns of the activities, the

evaluation of tenders as an activity was identified as one of the most vulnerable. Even though it may appear to

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be somewhat surprising to note that the tender evaluation activity was not identified as one of the most impacted

activity given its high susceptibility index, it must be emphasized that other constructs other than the causal

factors of corruption may contribute to the low significance level of the CTS2 activity. Moreover, other than

the vulnerable activities, the network analysis was performed to reveal other relevant activities that need to be

checked to limit the incidence and proliferation of corrupt practices at the different stages of the procurement

process. The contract stage (CTS) in most instances, is regarded as the most susceptible stage to corruption. The

study findings confirmed this supposition even though the results "can be argued to be the views of the experts

involved. Similar to the pre-contract stage, the development of anti-corruption measures and tools aimed at

extirpating corrupt practices must consider how the vulnerability patterns of the vulnerable activities such as

the tender evaluation stage and the contractor selection stage can be resolved. Another consideration can be

attributed to how the overall impact can be checked at the contractor selection stage through to the award of the

contract (Owusu et al. 2019).

Stage three (also known as the contract administration stage) also recorded similar results as compared to the

previous stage. Two out of four activities were identified to be impacted by the collective force of all the

variables captured under the negative constructs of corruption. The two activities are CAS1 (issuing of contract

amendments) and CAS4 (administering progress payment). CAS4 was the only activity noted to be highly

vulnerable to the incidence of corrupt practices (Owusu et al., 2019). The administration of progress payments

is often identified to be clouded with the negative impacts of corruption due to the prevalence of some of the

procurement irregularities such as the lack of adequate managerial or supervisory control over procurement

transactions.

Moreover, other procurement irregularities such as unjustified variations in contracts and the lack of proper

coordination among key departments responsible for procurement transactions are identified to contribute to the

significant impacts of corruption on the procurement process and especially during contract amendment at

progress payments’ issuance stages. Other influences stemming from the corruption causal construct include

weak contractual structures that often obscure the transparency of contractual payments, poor documentation of

records, and often, the absence of control mechanisms. As a result, inasmuch as all the four activities captured

under the CAS construct needs critical resolute measures in extirpating the influence and effects of corruption

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on this stage, there is the need for greater attention on the conditions surrounding the process of contract

amendments and the administration of progress payments as these variables were noted as the most impacted

activities and the CAS4 noted as the most vulnerable activity to corruption in this stage.

Finally, a turn to the last stage of the procurement process reveals that not only are the activities ident) captured

under this stage vulnerable to the criticality of corruption, but also the activities are recorded to be highly

impacted by the negative constructs of corruption at this stage. Among the six activities captured and examined

at this stage, five of the activities were identified to be crucial regarding their criticalities to the impacts of the

construct of corruption. Thus, the activities noted were: 1) completing final audits, checking proofs of delivery

(project deliveries), and returning of performance bond as closing out the contract. The only activity identified

to be less critical regarding the impacts of the negative constructs is the confirmation of the accuracy and

completeness of file documentations. Similar findings were noted under the vulnerability assessment stage. That

is, aside from the first five activities identified to be vulnerable to corruption, the final activity within this stage

(that is, PCP6) was the only activity noted to be less vulnerable to corrupt practices. Again, considering the

criticalicality of this stage, there is the need to develop resolute measures aimed at neutralizing or reinforcing

the activities against the likely occurrence of irregularities that renders the stage to the incidence of corruption.

Thus, as examined, any framework developed to extirpate corruption at this stage should examine the

correlational impacts of the causal factors of corruption, the barriers that hamper the effectiveness of anti-

corruption measures at this stage, as well as the noted irregularities that obscure transparency in the procurement

process. As such, future studies can examine how the variables captured under each of the constructs mentioned

can impact the individual activities of the procurement process. This can be studied into great detail to establish

to the individual activities’ interactions with the various variables under each specific construct.

6.6 Chapter Summary

This chapter serves as an extension to the previous chapter by examining the criticalities of the negative

constructs of corruption as it relates to the procurement process. Simply put, the constructs were empirically

examined to identify how critical they are towards the various activities and stages of the procurement process.

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Thus, they included the empirical assessment of the constructs of corruption, including the forms and the

associated causal factors and risk indicators. With the most critical form identified to be bribery, collusive, and

professional malfeasance acts, the notable cause factors were identified to be psychosocial and statutory-specific

causal factors. Lastly, the payments made for uncompleted works, lack of proper coordination among key

departments of an institution responsible for procurement works, and sourcing from the same supplies overtime

via the medium of favoritism formed the leading indicators for the risk construct. In all cases, more than fifty

percent of the variables captured under all the examined negative constructs were identified to be critical,

signaling the widespread of corruption within the context under study.

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 Chapter 7 – Anti-Corruption Measures and Associated Barriers Assessments

CHAPTER 7 – EXAMINING THE EFFECTIVENESS OF ANTI-

CORRUPTION MEASURES AND ASSOCIATED BARRIERS12’13

7.1 Introduction

Given that the endemic nature of corruption is often attributed to the causal factors as well as the

contextual vulnerabilities, not much emphasis has been given to examining the proliferation of

corruption in a given context in the light of the ineffectiveness of anti-corruption measures. As a result,

inasmuch as continual efforts are expended by different scholars to ascertain the causal instigators of

corruption, as well as the risk indicators, not many attempts, have been given to the influence of anti-

corruption measures, especially in the case of developing countries. For instance, in the case of Ghana,

there have been over 25 legal stipulations, including the enactments of laws against corruption, acts,

decrees, legislation, and the constitution established enforced to check corruption since the country

gained independence from its British in 1957 to date. However, corruption persists in the country,

especially in most parts of the public sector (Osei-Tutu et al. 2010; TI, 2017). This reflects the situation

of other developing countries that have countless anti-corruption stipulations but yet corrupt. Moreover,

this stands to confirm, at least in the case of Ghana, that the enforcement of many anti-corruption

measures does not necessarily correlate with or indicate low records of corruption.

As a result, there is a need to periodically conduct a critical assessment of the effectiveness and the

performances of the enforced measures. This will help ascertain how effective or weak the existing anti-

corruption measures are and determine whether there is a need for some level of reinforcement.

Moreover, corruption-related studies in the context of developing countries and their exploration of the

indicators of corruption in the public procurement sector, as well as the public construction-sector, have

12
This chapter is fully or partially published in the following journal article: Owusu, E. K., & Chan, A. P.
(2018). Barriers Affecting Effective Application of Anticorruption Measures in Infrastructure Projects:
Disparities between Developed and Developing Countries. ASCE Journal of Management in Engineering, 35(1),
04018056.
13
Owusu, E. K., Chan, A., & Hosseini, M. R. (2020). Impacts of anti-corruption barriers on the efficacy of anti-
corruption measures in infrastructure projects: Implications for sustainable development. Journal of Cleaner
Production, 119078.

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not been that encouraging. Particularly in Ghana, apart from the periodic (annual) release of the

Attorney General’s report on public boards and departments, it is difficult to find and extract data from

the public domain on the indicators related to corruption.

Against this backdrop, this chapter intends to investigate the potency of the measures developed and

enforced to guide, check, and extirpate the incidence and proliferation of corrupt practices in

infrastructure project procurement and management. Given the peculiarity of the context (i.e., project

procurement and management), analogous and relevant literature published on the subject matter to

date were consulted to understand the case of corruption in this context and the anti-corruption measures

established to check corruption in the developing region. With other studies exploring some of the

mentioned indicators, this chapter aims to investigate the existing anti-corruption measures in the

context of public procurement and their potency or efficacy in limiting and expurgating the proliferation

of corrupt practices during the procurement process of construction and engineering works. To realize

this aim, three vital objectives are stipulated which are: 1) identify the existing anti-corruption measures

established to mitigate corruption in infrastructure works; 2) examine the effectiveness of this measures

in the context of public procurement process of construction and engineering works; 3) stipulate

recommendations based on the findings. Evaluating the effectiveness of anti-corruption stipulations

guiding a project can produce very vital information on the measures and the constructs that need further

reinforcing mechanisms to make them recover the efficacy to become more resilient.

This chapter is highly relevant not only because of its theoretical contribution to the body of knowledge

but also to practice. Theoretically, this study is arguably the first empirical assessment of ACMS

established to guide, check, and extirpate corrupt practices in construction project management,

especially in the developing context. Thus, it contributes originally to the body of corruption-related

knowledge in infrastructure project procurement and management. Moreover, it adds to a deepened

understanding of the subject matter of anti-corruption research, the development, enforcement,

application, and the establishment of the mechanisms for their compliance. Regarding contribution to

practice, the findings of this chapter are intended to inform project participants, policymakers, anti-

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corruption institutions and researchers on the performance of the measures with their associated

constructs and the need to reinforce the measures that are revealed to be weak or ineffective. Thus,

rendering great support to these bodies to strategize the formulation of ACMs in a more focused

direction skewed to a specific area in infrastructure procurement as management. Lastly, information

on the apropos integration of the different constructs of the measures to yield high-end results can also

be determined by examining the effectiveness and the relations of the ACMs and with other institutions

/contexts and the processes which apply. As a foundational study, the information provided in this

chapter can guide both scholars and institutional practitioners to develop more rigorous frameworks

and assessment tools not only for evaluating the effectiveness of anti-corruption measures but also to

determine the criticality of other constructs or indicators on the topics of corruption as highlighted

previously. Analogous to other traditional manuscript outlines, the succeeding sections presents the

systematic review of relevant literature, the extraction of the needed constructs and variables for an

apropos questionnaire development (questionnaire development), the needed methods for the study

(such as questionnaire formation, sampling techniques, presentation of data analysis and discussions

and lastly, the limitations encountered and directions for future studies.

7.2 Anti-Corruption Estimation and Prediction Model Development

7.2.1 Index System Development

To commence, the six constructs identified in this section of the study are used to establish the

foundation for the development of the evaluation index system (EIS) (Ameyaw and Chan 2015). Thus,

the EIS is established by setting the constructs as the first-level index system (i.e., 𝑢𝑎𝑐𝑚 = 𝑢1 , 𝑢2 , 𝑢3 ..,

𝑢𝑚 ) Where 𝑢1 , 𝑢2 , 𝑢3 .., 𝑢𝑚 represents the individual constructs (i.e., sets that contain the individual

ACM variables). Thus, they are probing, regulatory, reactive, compliance promotional and managerial

measures and the variables within the constructs as the second level systems. Therefore, the set 𝑢𝑎𝑐𝑚

can be expressed as 𝑢𝑎𝑐𝑚 = (𝑢𝑝𝑟𝑚 , 𝑢𝑟𝑔𝑚 , 𝑢𝑚𝑎𝑚 , 𝑢𝑐𝑜𝑚 , 𝑢𝑝𝑏𝑚 , 𝑢𝑟𝑒𝑚 ), and promotional construct is

presented as 𝑢𝑝𝑟𝑚 = (𝑢𝑝𝑟𝑚1 , 𝑢𝑝𝑟𝑚2 , 𝑢𝑝𝑟𝑚3 , 𝑢𝑝𝑟𝑚4 , 𝑢𝑝𝑟𝑚5 ), since the construct is made up of five

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measures. The other variables within other constructs are defined analogously. The index systems

defined above forms the input variables for the fuzzy analysis. This is presented in Table 7.1.

Table 7.1: Anti-Corruption Variables

Code Variables MV NV SD Sig OR CR TM WVC
Regulatory Measures 𝒖𝒓𝒈𝒎 8.82 0.111
1 Comprehensive rules and 2.98 0.25 1.094 𝑢𝑟𝑔𝑚1 16 1
regulations
2 Ethical code 2.97 0.23 1.201 𝑢𝑟𝑔𝑚2 18 2
3 Development of strong 2.87 0.00 1.194 𝑢𝑟𝑔𝑚3 26 3
political and ethical will to
enforce existing anti-
corruption policies and laws.
Managerial/Administrative 𝒖𝒎𝒂𝒎 15.36 0.194
Measures
4 Good leadership 3.31 1.00 1.168 𝑢𝑚𝑎𝑚1 1 1
5 Professional associations 3.24 0.84 1.197 𝑢𝑚𝑎𝑚2 2 2
6 Transparency mechanism 2.97 0.23 1.101 𝑢𝑚𝑎𝑚3 18 3
7 Increase in accountability 2.94 0.16 1.279 𝑢𝑚𝑎𝑚4 21 4
8 Financial 2.90 0.07 1.251 𝑢𝑚𝑎𝑚5 24 5
disclosure/Disclosure
Compliance Measures 𝒖𝒄𝒐𝒎 9.17 0.116
9 Procedural compliance 3.19 0.73 1.171 𝑢𝑐𝑜𝑚1 5 1
10 Contractual compliance 3.00 0.30 1.187 𝑢𝑐𝑜𝑚2 15 2
11 Compliance to fairness and 2.98 0.25 1.248 𝑢𝑐𝑜𝑚3 16 3
transparent procedures
Promotional Measures 𝒖𝒑𝒓𝒎 18.12 0.229
12 Information technology 3.11 0.55 1.368 𝑢𝑝𝑟𝑚1 6 1
13 Raising awareness 3.08 0.48 1.205 𝑢𝑝𝑟𝑚2 9 2
14 Enhance communication 3.03 0.36 1.241 𝑢𝑝𝑟𝑚3 11 3
15 Education 3.03 0.36 1.187 𝑢𝑝𝑟𝑚4 11 3
16 Training and development 2.97 0.23 1.305 𝑢𝑝𝑟𝑚5 18 5
initiatives
17 Access to information 2.90 0.07 1.197 𝑢𝑝𝑟𝑚6 24 6

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 Chapter 7 – Anti-Corruption Measures and Associated Barriers Assessments

Probing Measures 𝒖𝒑𝒃𝒎 15.76 0.199

18 Contract monitoring 3.24 0.84 1.250 𝑢𝑝𝑏𝑚1 2 1
19 Whistle-blowing mechanism 3.24 0.84 1.250 𝑢𝑝𝑏𝑚2 2 1
20 Efficient reporting system 3.11 0.55 1.203 𝑢𝑝𝑏𝑚3 6 3
(independent hotline)
21 Rigorous supervision among 3.10 0.52 1.183 𝑢𝑝𝑏𝑚4 8 4
others
22 Rigorous technical auditing 3.07 0.45 1.209 𝑢𝑝𝑏𝑚5 10 5
system
Reactive Measures 𝒖𝒓𝒆𝒎 11.91 0.150
23 Dismissal from employment 3.03 0.36 1.379 𝑢𝑟𝑒𝑚1 11 1
or other disciplinary action
24 Harsh punishment or penalty 3.02 0.34 1.361 𝑢𝑟𝑒𝑚2 14 2
25 Debarment/promoting fair 2.94 0.16 1.279 𝑢𝑟𝑒𝑚3 21 3
debarment procedures
26 Effective investigation, court 2.92 0.11 1.334 𝑢𝑟𝑒𝑚4 23 4
proceedings, departmental
disciplinary action
79.14 1.000

7.2.2 Determining the MF for variables and constructs of the ACM

The determination of both the variables and constructs membership functions are conducted by fuzzy

mathematics (Ameyaw and Chan 2015). However, the MF of the variables are derived first by

employing the grading alternatives used to evaluate the level of effectiveness during the questionnaire

survey (i.e., k=1,2,3,4,5; where k1=very low, k2=low, k3=neutral, k4= high, k5= very high). Therefore,

the formula for computing the MF for a given variable is presented below;

𝑧1 𝑢 𝑧2 𝑢 𝑧3 𝑢 𝑧4 𝑢 𝑧5 𝑢 𝑧1 𝑢 𝑧𝑓 𝑧5 𝑢
𝑖𝑛 𝑖𝑛 𝑖𝑛 𝑖𝑛 𝑖𝑛 𝑖𝑛 𝑢𝑖𝑛 𝑖𝑛
𝑀𝐹𝑢𝑖𝑛 = + + + + = + +. . . . + equation (1)
𝑘2 𝑘3 𝑘4 𝑘5 𝑣𝑒𝑟𝑦 𝑙𝑜𝑤 𝑙𝑜𝑤 𝑣𝑒𝑟𝑦 ℎ𝑖𝑔ℎ

Where 𝑢𝑖𝑛 indicates the nth risk factor of a given construct i (i=𝑢𝑎𝑐𝑚 = (𝑢𝑝𝑟𝑚 , 𝑢𝑟𝑔𝑚 , 𝑢𝑚𝑎𝑚 , 𝑢𝑐𝑜𝑚 ,

𝑢𝑝𝑏𝑚 , 𝑢𝑟𝑒𝑚 ). MF represents the membership function of a particular variable 𝑢𝑖𝑛 ; 𝑍𝑔 𝑢 (𝑔=1,2,3,4,5)
𝑖𝑛

indicates the percentage of the respondents involved in the expert survey who assigned a score 𝑔 to

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indicate the level of effectiveness to a given variable. Moreover, the terms 𝑧1 𝑢𝑖𝑛 ⁄𝑘𝑖 connotes a

relationship between 𝑧1 𝑢𝑖𝑛 and its respective grade scale 𝑘𝑖 but not a fraction as it appears and the

symbol ‘+’ also represents a notation rather than an addition. Therefore, the MF of a given variable is

presented as 𝑀𝐹𝑢𝑖𝑛 = (𝑧1 𝑢𝑖𝑛 + 𝑧2 𝑢𝑖𝑛 + 𝑧3 𝑢𝑖𝑛 + 𝑧4 𝑢𝑖𝑛 + 𝑧5 𝑢𝑖𝑛 ) – equation (2). Using ‘transparency

mechanism as an example,

0.10 0.27 0.24 0.34 0.05

the 𝑀𝐹𝑓𝑖𝑛 = + + + + and presented as (0.10, 0.27, 0.24, 0.34,
𝑣𝑒𝑟𝑦 𝑙𝑜𝑤 𝑙𝑜𝑤 𝑚𝑜𝑑𝑒𝑟𝑎𝑡𝑒 ℎ𝑖𝑔ℎ 𝑣𝑒𝑟𝑦 ℎ𝑖𝑔ℎ

0.05). The set of values in a defined MF range between (0 and 1) and the summation of all the values

must equate 1. That is, ∑5𝑔=1 𝑍𝑔 𝑢 = (0.10 + 0.27 + 0.24 + 0.34 + 0.05) = 1. The MFs and the
𝑖𝑛

respective weightings for a particular ACM construct are processed to arrive at the MF for the

particular construct. The MFs for the individual variables are presented in Table 7.2, and that of the

constructs are computed in the next sections.

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Table 7.2: Membership Functions (MFs) at ACM Variables and Constructs Levels
Code Variables Mean Weightings MF for Level 3 MF for Level 2
Regulatory Measures 0.14, 0.21, 0.27, 0.31, 0.06
1 Comprehensive rules and regulations 2.98 0.338 0.13, 0.18, 0.31, 0.35, 0.03
2 Ethical code 2.97 0.337 0.16, 0.18, 0.26, 0.34, 0.06
3 Development of strong political and ethical will to enforce 2.87 0.325 0.13, 0.29, 0.26, 0.23, 0.10
existing anti-corruption policies and laws.
Managerial/Administrative Measures 0.11, 0.22, 0.25, 0.29, 0.12
4 Good leadership 3.31 0.215 0.06, 0.21, 0.24, 0.32, 0.16
5 Professional associations 3.24 0.211 0.08, 0.23, 0.21, 0.34, 0.15
6 Transparency mechanism 2.97 0.193 0.10, 0.27, 0.24, 0.34, 0.05
7 Increase in accountability 2.94 0.191 0.18, 0.19, 0.26, 0.26, 0.11
8 Financial disclosure/Disclosure 2.90 0.189 0.16, 0.21, 0.32, 0.18, 0.13
Compliance Measures 0.11, 0.24, 0.24, 0.30, 0.11
9 Procedural compliance 3.19 0.348 0.06, 0.29, 0.15, 0.39, 0.11
10 Contractual compliance 3.00 0.327 0.11, 0.26, 0.24, 0.29, 0.10
11 Compliance to fairness and transparent procedures 2.98 0.325 0.16, 0.16, 0.34, 0.21, 0.13
Promotional Measures 0.13, 0.26, 0.21, 0.28, 0.13
12 Information technology 3.11 0.172 0.16, 0.21, 0.16, 0.29, 0.18
13 Raising awareness 3.08 0.170 0.08, 0.29, 0.24, 0.24, 0.15
14 Enhance communication 3 .03 0.167 0.13, 0.24, 0.21, 0.31, 0.11
15 Education 3.03 0.167 0.11, 0.26, 0.19, 0.35, 0.08
16 Training and development initiatives 2.97 0.164 0.16, 0.24, 0.19, 0.27, 0.13
17 Access to information 2.90 0.160 0.11, 0.31, 0.26, 0.21, 0.11
Probing Measures 0.10, 0.23, 0.22, 0.32, 0.13
18 Contract monitoring 3.24 0.206 0.11, 0.18, 0.23, 0.32, 0.16
19 Whistle-blowing mechanism 3.24 0.206 0.10, 0.23, 0.18, 0.34, 0.16
20 Efficient reporting system (independent hotline) 3.11 0.197 0.10, 0.26, 0.19, 0.34, 0.11
21 Rigorous supervision among others 3.10 0.197 0.10, 0.26, 0.19, 0.35, 0.10
22 Rigorous technical auditing system 3.07 0.195 0.11, 0.21, 0.30, 0.25, 0.13
Reactive Measures 0.18, 0.21, 0.21, 0.25, 0.15
23 Dismissal from employment or other disciplinary action 3.03 0.254 0.19, 0.16, 0.24, 0.23, 0.18
24 Harsh punishment or penalty 3.02 0.254 0.19, 0.18, 0.19, 0.29, 0.15
25 Debarment/promoting fair debarment procedures 2.94 0.247 0.16, 0.24, 0.21, 0.27, 0.11
26 Effective investigation, court proceedings, departmental 2.92 0.245 0.16, 0.27, 0.21, 0.19, 0.16
disciplinary action

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7.2.3 Estimation of the weightings

The weighting of a particular ACM connotes the relative importance as expressed by the respondents

involved in the expert survey. While it can be calculated from several methods such as normalized mean

and the analytic hierarchy process, the normalized mean method was adopted to estimate the weightings

for both the variables and the constructs (Lo 1999; Ameyaw and Chan 2015). The mean values obtained

from the survey results are normalized to obtain the weighting function of both the individual variables and

the construct. The formula used to estimate the weighting of function is given as

𝑀𝑖
𝑀𝐹𝑢𝑖𝑛 = ∑5 , 0 < 𝑤𝑖 < 1, 𝑎𝑛𝑑 ∑5𝑖=1 𝑤𝑖 = 1 equation (4)
𝑖=1 𝑀𝑖

where 𝑤𝑖 , represents the weighting function of a specific ACM variable or construct i and 𝑀𝑖 indicates the

mean value of a specific variable or construct. The estimated weighting functions of a given set (i.e., either

variable or construct) is presented as 𝑤𝑖 = (𝑤1 , 𝑤2 , 𝑤3 , 𝑤4 , 𝑤5 ) - equation (5). Therefore, using good

leadership as an example, the weighting is estimated as follows;

3.31 3.31
𝑤mam1 = = = 0.215
3.31 + 3.24 + 2.97 + 2.94 + 2.90 15.36

Moreover, the weightings of the remaining constructs are computed as;

8.82 8.82
𝑓𝑟𝑔𝑚 = = = 0.111
8.82 + 15.36 + 9.17 + 18.12 + 15.76 + 11.91 79.14

15.36 15.36
𝑓𝑚𝑎𝑚 = = = 0.194
8.82 + 15.36 + 9.17 + 18.12 + 15.76 + 11.91 79.14

9.17 9.17
𝑓𝑐𝑜𝑚 = = = 0.116
8.82 + 15.36 + 9.17 + 18.12 + 15.76 + 11.91 79.14

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18.12 18.12
𝑓𝑝𝑟𝑚 = = = 0.229
8.82 + 15.36 + 9.17 + 18.12 + 15.76 + 11.91 79.14

15.76 15.76
𝑓𝑝𝑏𝑚 = = = 0.199
8.82 + 15.36 + 9.17 + 18.12 + 15.76 + 11.91 79.14

11.91 11.91
𝑓𝑟𝑒𝑚 = = = 0.150
8.82 + 15.36 + 9.17 + 18.12 + 15.76 + 11.91 79.14

𝑤𝑖 is therefore presented as = (0.111, 0.194, 0.116, 0.229, 0.199, 0.150). Moreover, the summation of𝑤𝑖 ,

(i.e. 0.111, 0.194, 0.116, 0.229, 0.199, 0.150) =1. The weighting of all the variables and their respective

constructs have been presented in Table 7.2.

7.2.4 Development of the Multi-Criteria and Multi-Level Fuzzy Model

Prior to the evaluation of the overall effectiveness index (EI) which is normally a single indicator to denote

the level of effectiveness of the context under study, the effectiveness of the individual constructs is

evaluated to determine the indexes for each construct. Therefore, to determine the effectiveness of a given

construct, Ki is first established for every construct after the estimation of the membership functions for the

variables within their respective constructs. Therefore, following equation (2), the membership functions

of all the individual constructs are presented in a fuzzy matrix:

𝑀𝐹u𝑖1 𝑧1 u𝑖1 𝑧2 u𝑖1 𝑧3 u𝑖1 𝑧4 u𝑖1 𝑧5 u𝑖1

𝑀𝐹 𝑧2 𝑧1 u 𝑧1 u 𝑧1 u 𝑧1 u
| u𝑖2 | | u𝑖2 𝑖2 𝑖2 𝑖2 𝑖2
Ri= 𝑀𝐹u𝑖3 = 𝑧3 u𝑖3 𝑧1 u𝑖3 𝑧1 u𝑖3 𝑧1 u𝑖𝑛3 𝑧1 u𝑖2 | – equation (6), elements are presented by 𝑍𝑘 .
| | ⋯ u𝑖𝑛
|
⋯ ⋯ ⋯ ⋯ ⋯ |
𝑀𝐹u 𝑧1 u𝑖𝑛 𝑧2 u𝑖𝑛 𝑧3 u𝑖𝑛 𝑧4 u𝑖𝑛 𝑧5 u𝑖𝑛
𝑖𝑛

Therefore, Di, which represents the fuzzy evaluation matrix, is computed using the weighted function set

of both the ACM variables and constructs, respectively. This formula is presented as follow;

𝐷𝑖 = 𝑊𝑖 ●𝑅𝑖 = (𝑑𝑖𝑛 , 𝑑, 𝑑𝑖𝑛 , … 𝑑𝑖𝑛 )

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𝑧1 𝑢𝑖1 𝑧2 𝑢𝑖1 𝑧3 𝑢𝑖1 𝑧4 𝑢𝑖1 𝑧5 𝑢𝑖1

𝑧2 𝑧1 𝑢𝑖2 𝑧1 𝑢𝑖2 𝑧1 𝑢𝑖2 𝑧1 𝑢𝑖2
|𝑧 𝑢𝑖2 𝑧1 𝑢𝑖3 𝑧1 𝑢𝑖3 𝑧1 𝑢𝑖𝑛3 𝑧1 𝑢𝑖2 | = (𝑑𝑖𝑛 , 𝑑, 𝑑𝑖𝑛 , … 𝑑𝑖𝑛 ).
𝐷𝑖 = (𝑤1 , 𝑤2 , 𝑤3 , . . . 𝑤𝑛 )● 3 𝑢𝑖3
| ⋯ ⋯ ⋯ ⋯ ⋯ |
𝑧1 𝑢 𝑧2 𝑢 𝑧3 𝑢 𝑧4 𝑢 𝑧5 𝑢
𝑖𝑛 𝑖𝑛 𝑖𝑛 𝑖𝑛 𝑖𝑛

Where 𝑑𝑖𝑛 represents the grading scale degree of membership, 𝑘𝑖 of a specific ACM construct i; the

designation ‘●’ connotes a composite operation in the fuzzy environment (Hsaio 1998; Ameyaw and Chan

2015). Therefore, using equation above, the compliance measures construct is computed as follows:

0.06 0.29 0.15 0.39 0.11

𝐷𝑖 = (0.348, 0.327, 0.325) × |0.11 0.26 0.24 0.29 0.10|= (0.11, 0.24, 0.24, 0.30, 0.11)
0.16 0.16 0.34 0.21 0.13

This is repeated for all the other constructs, and the results are presented in Tables 7.2 and 7.3. However,

after the derivation of fuzzy evaluation matrix for each of the construct, the effectiveness index for each

construct is computed using the formula ∑5𝑖=1 𝐷 × 𝐾 𝑡 , 1 ≤ 𝑂𝐸𝐼 ≤ 5. – equation (7). Therefore, the

effectiveness indexes of the constructs are computed as follows:

𝐸𝐼𝑟𝑔𝑚 = [(0.14 × 1) + (0.21 × 2) + (0.27 × 3) + (0.31 × 4) + (0.06 × 5)] =2.92

𝐸𝐼𝑚𝑎𝑚 = [(0.11 × 1) + (0.22 × 2) + (0.25 × 3) + (0.29 × 4) + (0.12 × 5)] =3.08

𝐸𝐼𝑐𝑜𝑚 = [(0.11 × 1) + (0.24 × 2) + (0.24 × 3) + (0.30 × 4) + (0.11 × 5)] = 3.06

𝐸𝐼𝑝𝑟𝑚 = [(0.13 × 1) + (0.26 × 2) + (0.21 × 3) + (0.28 × 4) + (0.13 × 5)] = 3.02

𝐸𝐼𝑝𝑏𝑚 = [(0.10 × 1) + (0.23 × 2) + (0.22 × 3) + (0.32 × 4) + (0.13 × 5)] = 3.15

𝐸𝐼𝑟𝑒𝑚 = [(0.18 × 1) + (0.21 × 2) + (0.21 × 3) + (0.25 × 4) + (0.15 × 5)] = 2.98

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The computed evaluation fuzzy matrixes, 𝐷𝑖 (𝑖=1,2,3,4,5,6) will then form the fuzzy matrix 𝑅̅ , for

computing the overall effectiveness index of the measures.

𝑀𝐹1 𝑑11 𝑑12 𝑑13 𝑑14 𝑑15

𝑀𝐹2 𝑑21 𝑑22 𝑑23 𝑑24 𝑑25
|𝑀𝐹 | |𝑑 𝑑32 𝑑33 𝑑34 𝑑35
|
3
Therefore 𝑅̅(𝑜𝑒𝑖) = = 31 ,
| 𝑀𝐹4 | |𝑑41 𝑑42 𝑑43 𝑑44 𝑑45
|
𝑀𝐹5 𝑑51 𝑑52 𝑑53 𝑑54 𝑑55
𝑀𝐹6 𝑑61 𝑑62 𝑑63 𝑑65 𝑑65

Where 𝑖 = (1,2,3,4,5,6) represents the individual constructs of the measures. Therefore, using equation 10,

𝑅̅ is again normalized through the weighted function 𝑊

̅(𝑜𝑒𝑖) = (𝑤′1 , 𝑤′2 , 𝑤′3 , . . . 𝑤′𝑛 ), using the individual

constructs to compute for the fuzzy evaluation matrix of the final stage as described in the previous section.

This is therefore presented as;

𝑑11 𝑑12 𝑑13 𝑑14 𝑑15

𝑑21 𝑑22 𝑑23 𝑑24 𝑑25
| |
̅(𝑜𝑒𝑖) ●𝑅̅(𝑜𝑒𝑖) = (𝑤′1 , 𝑤′2 , 𝑤′3 , . . . 𝑤′𝑛 ) ● 𝑑31
̅(𝑜𝑒𝑖) =𝑊
𝐷
𝑑32 𝑑33 𝑑34 𝑑35
= (𝐷′1 , 𝐷′2 , 𝐷′3 , . . . 𝐷′𝑛 )
𝑑 𝑑42 𝑑43 𝑑44 𝑑45
| 41 |
𝑑51 𝑑52 𝑑53 𝑑54 𝑑55
𝑑61 𝑑62 𝑑63 𝑑65 𝑑65

̅(𝑜𝑒𝑖) =(𝐷′1 , 𝐷′2 , 𝐷′3 , . . . 𝐷′𝑛 )

Where ′𝑜𝑒𝑖′ represents the overall effectiveness index of the measures and 𝐷

connotes the fuzzy evaluation matrix for the overall effectiveness index (OEI) of the measures which can

be quantified using the grading scores (k=1,2,3,4,5) using the formula below: 𝑂𝐸𝐼𝑎𝑐𝑚 =

̅ × 𝐾 𝑡 = (𝐷′ , 𝐷′2 , 𝐷′ 3 , 𝐷′4 , 𝐷′ 5 ) × (1,2,3,4,5), 1 ≤ 𝑂𝐸𝐼 ≤ 5,

∑5𝑖=1 𝐷 1

Where 𝑂𝐸𝐼𝑎𝑐𝑚 represents the index generated for the overall effectiveness index of anti-corruption

measures in the developing countries. This stage is known as defuzzification (i.e., the fuzzy members are

converted into crisp values/outputs), which facilitates decision making.

Table 7.3: Stages of the Procurement Process

No Anticorruption Constructs Weighting MF for Level 2 MF for Level 1
1 Regulatory Measures 0.111 0.14, 0.21, 0.27, 0.31, 0.06 0.13, 0.23, 0.23, 0.29, 0.12
2 Administrative Measures 0.194 0.11, 0.22, 0.25, 0.29, 0.12

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3 Compliance Measures 0.116 0.11, 0.24, 0.24, 0.30, 0.11

4 Promotional Measures 0.229 0.13, 0.26, 0.21, 0.28, 0.13
5 Probing Measures 0.199 0.10, 0.23, 0.22, 0.32, 0.13
6 Reactive Measures 0.150 0.18, 0.21, 0.21, 0.25, 0.15

The fuzzy membership functions are thus defuzzified through the grading alternatives adopted (Sadiq and

Rodriguez 2004; Ameyaw and Chan 2015). The actual calculations are presented below:

0.111 0.14 0.21 0.27 0.31 0.06

0.194 0.11 0.22 0.25 0.29 0.12
|0.116| |0.11 0.24 0.24 0.30 0.11|
̅(𝑜𝑒𝑖) =𝑊
𝐷 ̅(𝑜𝑒𝑖) ●𝑅̅(𝑜𝑒𝑖) = × = (0.13, 0.23, 0.23, 0.29, 0.12)
|0.229| |0.13 0.26 0.21 0.28 0.13|
0.199 0.10 0.23 0.22 0.32 0.13
0.150 0.18 0.21 0.21 0.25 0.15

Therefore, using equation 10 above, the Overall Effectiveness Index of the ACM is given as:

ACMoei = [(0.13 × 1) + (0.23 × 2) + (0.23 × 3) + (0.29 × 4) + (0.12 × 5)] = 3.05

7.2.5 Discussions

Generally, the overall effectiveness index of ACM in developing context is 3.05, which indicates that ACM

in this context (especially in the case of Ghana) stands at the neutral level (i.e., moderately effective; not

too bad nor too good). Moreover, the results may indicate why the diverse forms of corrupt acts are still

prevalent in the developing context. However, it must be emphasized that the results indicate steady and

gradual progress from ineffectiveness to neutral effectiveness of anti-corruption measures in the

procurement and management of infrastructure projects. This is owed to the supposition that the strength

of an institution or a country against the prevalence of corruption is directly correlated to the potency of

stipulated anti-corruption measures in operation. In effect, the more potent the measures are, the less corrupt

the context in question.

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This section explored 26 anti-corruption measures derived from an extensive literature review. The

measures were identified under six constructs, namely investigative measures, administrative measures,

compliance measures, promotional measures, punitive or reactive measures, and lastly, regulatory measures

(Owusu et al. 2019). The review explored the existing anti-corruption measures developed and enforced

overtime to thwart and extirpate the proliferation of corrupt acts both in the short term and long term,

respectively. The experts involved were asked to assess the effectiveness of the anti-corruption measures

regarding their adoption in project procurement and management. Inasmuch as the Likert grading system

ranging from 1-5, was adopted to indicate the level of effectiveness, none of the variables was

approximately rated nor had a score of greater than 3.50 (which indicates effectiveness). Among all the 26

constructs, the highest-ranked variable obtained a mean index (MI) of 3.31 (which indicates moderately

effective) and the lowest-ranked variable MI of 2.87 (also, moderately effective). The measures with their

respective constructs are thus discussed in the succeeding section.

7.2.6 The development of the EI model for other Developing Regions

In developing the effectiveness index model (EIM), the index for all of the anti-corruption constructs were

merged to establish a linear equation model. The technique is mostly adopted due to its ability or flexibility

to allow for different ordinal grading scales (i.e., either 9, 7 or 5-point scale to be used in assessing the

vulnerability index of procurement processes). Moreover, another advantageous justification for adopting

the linear model approach is that it is clear, concise, logical, and easily understandable. It, therefore, allows

practitioners and policymakers, anti-corruption institutions, and researchers to adopt or use it without

difficulty.

However, prior to the development of the linear model for the evaluation of the overall EI for the anti-

corruption measures stipulated to extirpate corrupt practices encountered in the procurement and

management of projects in other developing regions, there was the need to normalize the individual EI of

the ACM constructs in order to equate the summation of all the constructs to one (Osei-Kyei and Chan

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2017). This can enable the evaluation or the estimation of any of the overall EI of either a proposed or

existing project irrespective of the grading scale of linguistic terms adopted. Table 7.4 presents the

normalized values of the procurement constructs.

Table 7.4: Stages of the Procurement Process

Code IP Stages Weighting Coefficients Coefficient Symbols
RGM Regulatory Measures 2.92 0.160 𝐸𝐼𝑟𝑔𝑚
MAM Administrative Measures 3.08 0.169 𝐸𝐼𝑚𝑎𝑚
COM Compliance Measures 3.06 0.168 𝐸𝐼𝑐𝑜𝑚
PRM Promotional Measures 3.02 0.166 𝐸𝐼𝑝𝑟𝑚
PBM Probing Measures 3.15 0.173 𝐸𝐼𝑝𝑏𝑚
REM Reactive Measures 2.98 0.164 𝐸𝐼𝑟𝑒𝑚
Total 18.21 1.000

Therefore, using the normalized values, the linear equation model of the estimation of the overall PVI for

IP’s in Ghana or other similar developing countries is presented below:

𝑂𝐸𝐼 = EIrgm [𝑅𝐺𝑀] + EImam [𝑀𝐴𝑀] + EIcom [𝐶𝑂𝑀] + EIprm [𝑃RM] + EIpbm [𝑃𝐵𝑀] + EIrem [𝑅𝐸𝑀]

𝑂𝐸𝐼 = 0.160[𝑅𝐺𝑀] + 0.169[𝑀𝐴𝑀] + 0.168[𝐶𝑂𝑀] + 0.166[𝑃RM] + 0.173[𝑃𝐵𝑀] + 0.164[𝑅𝐸𝑀]

- Equation 11

In equation 5, the coefficients assigned to each anti-corruption construct connotes their respective

normalized values. According to the equation, probing measures turned out to be the construct with the

highest coefficient value succeeded by administrative measures due to their respective high weightings

obtained from the FSE technique, as presented in Table 7.1.

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7.2.7 Performance of the Measures

Regulatory or statutory measures can be defined as legal stipulations (ranging from acts, decrees,

regulations, etc.) enforced to avert the incidence and the proliferation of corrupt acts at the systemic or

national level with its effects penetrating to public institutions and boards (Owusu et al. 2018; Tabish and

Jha 2012). These measures are stipulated to create a clean environment towards a corrupt-free zone,

conducive enough to limit indulgence (by self-driven, system motivated, or peer pressure) in corrupt acts.

With an overall effectiveness index of 2.94, the variables captured under this construct (namely the

establishment of comprehensive rules and regulations, ethical code, and the development of strong political

and ethical will to enforce existing anti-corruption policies and laws obtained similar scores of 2.98, 2.97

and 2.87 respectively. Even though the regulatory measure's construct was the least ranked among the six

constructs, the variable captured under this construct received relatively equal mean values obtained by the

other variables.

It must be emphasized that the high number of statutory measures does not necessarily reflect or indicate

less incidence of corruption. For instance, with more than over 25 statutory stipulations enforced to check

the prevalence of corrupt acts in the case of Ghana, the effectiveness of regulatory measures in this context

remain questionable. On the other hand, Hong Kong, which is known to have one comprehensive anti-

corruption manual (i.e., the Prevention of Bribery Ordinance), and yet has been able to help check

corruption to an appreciable level as compared to the previous decades. It is now regarded as one of the

clean regions in the world regarding the incidence of corruption (Quah, 2016). This analogy supplements

the notion that the number of statutory stipulations in a given context does not necessarily reflect how clean

or corrupt that particular context is. A context may have very few stipulations and yet very clean. On the

other hand, another state may have several laws stipulated to limit the proliferation of corrupt practices and

yet corrupt, as presented in the case of Ghana. However, this supposition may need further empirical

research to justify its validity.

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This, therefore, prompts the need for compliance or adherence measures. Compliance measures are

enforced to drive (either willingly or cogently) project parties to comply to laid down regulatory measures

(Owusu et al. 2018). From Table 7.1, three variables captured under this construct are procedural

compliance with an MI of 3.19, contractual compliance with an MI of 3.00, and lastly, the compliance to

fairness and transparent procedures, also with an MI of 2.98. Thus, all three variables were also revealed to

be moderately effective. Could there be a possible supposition that the level of attention given to compliance

measures had a direct correlation with the performance or effectiveness of other constructs?

Owusu et al. (2018) attributed to the need for compliance measures as well as the deterrence from the notion

that people often follow stipulated regulatory measures once enforced. The authors pointed out that until

deliberate efforts are taken to inform and equip the parties to whom the stipulated measures affect, there is

the tendency for corruption to prevail. Regarding the five facets of compliance measures, Worthy et al.

(2017) instigated that whereas full compliance and concordance from the needed expectations from those

whom the measures affect (project parties), the remaining three types of compliance (i.e., noncompliance,

less compliance, and partial compliance) may have a negative implication or repercussions on the adoption

of the measures. Therefore, after the development and enforcement of proactive or preventive ACMs, the

next most important phase would be to establish compliance measures through which the stipulated

measures can be fully applied to its best. Another resolute measure could be to integrate not only compliance

measures in the tender documents or contractual stipulations binding a project but also indicate in the

mentioned documents, the necessary reactive measures should they default or falter in any of the measures.

Administrative measures, unlike statutory measures, encompass the internal structures that regulate the

behavior and actions of parties towards the prevention and extirpation of corrupt practices. Therefore,

whereas statutory measures are considered to be of more external structures that affect a greater population,

administrative measures are considered to be from within an organization, which vary from organization to

organization and as a common trait, they derive their source or influence from statutory regulations. Per the

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results, the administrative measures’ construct obtained an index of 3.08, making it the second-highest

ranked construct even though the measures captured under this construct were identified to be moderately

effective. The variables encapsulated in this construct included good relationships, professional

associations with an MI of 3.24, transparency mechanism with an MI of 2.97, and lastly, an increase in

accountability as well as financial disclosure placing fourth and fifth with their respective mean values of

2.94 and 2.90. It is identified that the variables captured under this construct are all geared towards the

creation of a transparent and accountable environment that fosters a corrupt-free environment.

Moving on to the promotional measures construct, the variables encapsulated in this construct are aimed at

publishing and educating the informants (i.e., project parties) on the incidence, outcome, and resolute

measures on corruption. With an overall construct MI of 3.02, the variables under this construct shared

similar scores with the case of education, raising awareness, conducting training and development

initiatives, access to information, information technology, and enhanced communication with their means

ranging from 3.11 to 2.90. In other contexts, such as Hong Kong, this construct is identified to be a solid

contributor to the extermination of corrupt actions. As such, there is a lone department responsible for

dutifully executing the tasks related to promotional measures not only to keep the general public informed

but also to develop context-driven training and initiative measures towards thwarting and extirpating

corrupt practices in selected public departments (ICAC 2018). Thus, analogous to the compliance measures,

the development of anti-corruption frameworks for a particular purpose without necessitating effective

promotional measures to propagate the core elements or demands of the framework with the suitable means

of adaptation and consequence, may propel the practices of corruption to persist.

Among all the constructs, probing measures received the highest construct EI of 3.15, indicating its

importance and yet revealed to be moderately effective, just as in the cases of the other constructs. Probing

measures refers to the proactive indicators established to facilitate and ensure effective auditing

investigation processes (Owusu et al. 2018; Sichombo et al. 2009). Moreover, they can be considered as

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corruption-preventive mechanisms established to monitor the periodic performance of projects to ensure

that projects do not get susceptible to corrupt practices and thus create auxiliary surveillance to prohibit

project parties from engaging in corrupt acts. They are therefore made up of variables including contract

monitoring (with an MI of 3.24, being the highest-ranked variable under the investigative construct),

whistleblowing mechanism, efficient reporting system both with MI’s of 3.24 and 3.11 respectively.

The remaining variables captured under this construct include rigorous technical and auditing of project

documents regarding finance, performance bonds, and standards, among others, as well as conducting

rigorous supervision of project execution (with MI’s of 3.07 and 3.10 respectively). Similar findings

realized in the variables of the previous constructs are analogous to the case of this construct. The

effectiveness of one has direction on another. Even though this construct is identified to be neutrally

effective in the domain of the developing context, it is, however, known to be one of the strong anti-

corruption mechanisms in the developed contexts like the HK. Moreover, even though every construct of

the ACM plays a huge integral role in extinguishing the flames of corruption, ICAC (2018) opined that a

greater share of the strength is derived from the effectiveness of the stipulated investigative measures. It is

supported by the justification by Wai (2006) that it is only an effective investigative process that can lead

to the discovery of an anticipated corrupt act. The offer further pointed out that the ICAC of HK expends

over 70% of the institution's resources in the operations department (i.e., the department responsible for

conducting investigations). However, in the case of developing countries, there would be a need for further

studies to examine the impact of probing measures on the effectiveness of the other anti-corruption

measures.

Similar to the case of probing or investigative measure, some scholars attribute the strength of most

anti-corruption frameworks to the strength of its reactive measures (Bowen et al. 2007; Zou 2006). This is

owed to the proposition that other proactive measures such as regulatory, administrative, and compliance

measures may not be very stern as compared to reactive measures. Reactive measures can be described as

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the threshold of every anti-corruption framework where culprits cannot cross but rather face the

consequences of their actions. They are therefore regarded as control mechanisms stipulated to render

justice, equity, or fairness as payback for the indulgence in a corrupt act. They consist of measures such as

dismissing employers (project parties) from employment coupled with other disciplinary actions such as

confiscating properties obtained by means of corruption, offering harsh punishment such as long-term or

life imprisonment to offenders, barring identified culprits from taking part in future projects among others

(Stansbury 2009; Sohail and Cavill 2008; de Jong 2009).

Again, all these measures obtained an MI ranging between 3.03 and 2.92 (also indicating a level of neutrally

effective). Therefore, similar to other constructs, the reactive measures construct also obtained a construct

EI of 2.98 obtaining the fifth position in terms of constructs ranking. As a common observation, there is the

need to examine all the variables captured under all the constructs critically, and how they can be reinforced

to obtain their full potency.

7.3 Barriers Inhibiting the Efficacy of Anti-corruption Measures

7.3.1 Introduction

Whereas extant literature attributes the proliferation of corrupt practices, especially within the domain of

public project procurement and management, to the causal factors of corruption, succeeding works (e.g.,

Tabish and Jha 2011; Le et al. 2014) reported on the risk indicators associated with corruption in public

projects. In effect, it was identified that corruption in public projects manifests as a result of causal factors

as well as risk indicators. Typical examples include the complexity of projects and contractual structure,

selecting unqualified contractors for megaprojects, and the distorted flow of information among project

parties (Locatelli et al. 2014; Le et al. 2014; Owusu et al. 2014).

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Thus, corruption research in this regard often highlights these two mainstreams as the problematic areas of

concern, in tackling corruption (i.e., the causal factors of corrupt practices and the risk indicators of

corruption). However, given that most anti-corruption measures were developed to tackle these two

instigators of corruption, limited attention was and is still given to the exploration of the factors (barriers)

that hamper the effectiveness of the enforced anti-corruption measures. Recent studies have emphasized

the need to explore and overcome these barriers in specific contexts, as they do not only contribute to the

ineffectiveness of anti-corruption measures but also the proliferation of corrupt practices at governmental,

organizational, and project levels (Owusu and Chan, 2019). This research problem has not been adequately

addressed in the extant project management-related scholarship. Particularly regarding public projects in

developing countries such as Ghana. Additionally, there is very little knowledge of the quantitative impacts

of various barriers types on the effectiveness of anti-corruption measures, owing to the lack of quantitative

models that elucidate these impacts. In the ACMs application context, researchers, practitioners, and

policymakers are interested not only in the barriers that are more critical but also which barriers are

“significantly” correlated to the ACMs effectiveness. Such knowledge is useful to successful and effective

development and application of ACMs in project management.

Against these backdrops, the specific this section aims to examine the question of why most anti-corruption

measures, stipulated to guide the execution of corrupt-free projects in the developing countries, often fail.

With projects exceeding their capped or budgeted limit excessively coupled with time overruns and

substandard works due to corruption. How critical are the barriers against the anti-corruption measures?

In line with the established research problem, this study attempts to address the identified gaps in the

existing project-management-related scholarship, contributing to the BoK by analyzing: (1) the impacts of

the barriers (i.e., the probability and severity indexes); and (2) the degrees of influences of the barriers on

the effectiveness of the ACMs. It must, however, be emphasized that the stated objectives are skewed

towards project management in developing countries using Ghana as the representative scope, making it

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arguably the first to examine the quantitative impacts of barriers on the effectiveness of ACMs in public

project management. Thus, justifying its originality. This section in its entirety (that is, the constructs

assessed, the hypothesis tested, and the model developed) is an original contribution to the scholarship of

project management. It makes a significant contribution to the body of knowledge on corruption-related

studies in project management by deepening understanding of the subject. Theoretically, since previous

studies have not empirically addressed these issues from the perspective of project experts, the study’s

findings represent the first to reveal the correlational impact of the barriers on the effectiveness of anti-

corruption measures.

Consequently, such findings also contribute to the existing body of knowledge (BoK) on corruption-related

studies in project management. Cumulatively, the research provides anti-corruption institutions,

policymakers, and industry practitioners that may assist in the development and implementation of more

stringent anti-corruption tools and measures for extirpating the barriers that impede the effectiveness of

ACMs in project management. The work also serves to provide a foundation for further empirical studies

on the subject matter.

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Figure 7.1: Individual variables and constructs of barriers and ACMs

(Adapted from Owusu and Chan 2018 and Owusu et al. 2018).

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7.3.2 Hypotheses Formulation

Before developing the hypotheses for this section of the study, it was expedient to relay the research

framework. According to Darko et al. (2017), a research framework is needful for developing new

knowledge. It can be based on either logic or theory or both (Simon and Goes 2011). Therefore, the research

framework developed in this section is based on both theory and logic. Theoretically, the barriers that affect

the effective application of ACMs are noted to contribute to the prevalence of corrupt practices (Owusu

and Chan 2019). As there is no existing framework regarding the barriers construct in the literature, the

empirical exploration of these constructs is identified to be in its infancy. However, inferences are taken

from Le et al.’s (2014) study, which measured two negative constructs of corruption in the Chinese

infrastructure sector. The constructs involved were the causes of corruption and the vulnerability to corrupt

practices (Le et al. 2014). Therefore, it is theoretically identified in the literature that the correlation among

the negative indicators and other constructs of corruption-related studies can be examined to ascertain its

significant relationships and how these relationships can be extirpated. Thus, making both theoretical and

practical contributions to the expurgation of corrupt practices in project procurement and management.

Regarding developing the hypotheses, this section focuses on two main corruption-related issues, namely,

the barriers affecting the effectiveness of ACMs and the constructs of ACMs. The ineffectiveness of most

ACMs has been the concern of many governments and private institutions (Owusu et al. 2017). Thus, this

section partly addresses the concern by examining the identified ineffectiveness of the ACMs in light of the

identified barriers. The term ‘partly addresses’ is emphasized because other corruption-related constructs

other than the barriers may contribute to the incidence, influence, and proliferation of corrupt practices

(Shan et al. 2017; Zhang et al. 2017). However, the measurement of corruption prevalence from the

perspective of the ACMs’ ineffectiveness, which is partly attributed to the identified barriers, has not been

conducted yet. Therefore, as mentioned earlier, most of these attributions are directed to the causal

instigators of corruption and risk indicators (Le et al. 2014). This section of the study is the first attempt to

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measure the significance of the influences of the constructs captured under the barriers and ACMs.

Comprehensive reviews have already been conducted on both constructs in previous studies (Owusu and

Chan, 2019; Owusu et al., 2019). However, as explicated earlier, this section is specifically skewed towards

the context of developing regions, and as a result, the indicators for both constructs were pilot tested to suit

the context under study. Further explications on this point are presented in the methodology section. There

are ten constructs to be tested (four barriers construct and six ACMs constructs). The four barriers are socio-

political barriers, administrative barriers, psychosocial barriers, fear, and insecurity. The six ACMs are

administrative, compliance, probing, promotional, reactive, and regulatory measures (Owusu et al. 2019).

Therefore, a total of 24 hypotheses are established from the four barriers and six ACMs (each barrier is

mapped to the six ACMs). However, they are captured under four main themes:

1) Socio-political barriers have a significant negative influence on all the six ACMs’ constructs;

2) Psychosocial barriers have a significant negative influence on all the six ACMs’ constructs;

3) Fear and insecurity have a significant negative influence on all the six ACMs’ constructs; and

4) Administrative barriers have a significant negative influence on all the six ACMs’ constructs.

In order not to skew the hypothesis, there is a supposition that all the constructs captured under the barriers

have significant negative influences on all the ACMs. The hypothetical framework is presented in Fig. 7.2.

The results from the hypotheses testing do not only contribute to the theoretical exposition and contribution

on the subject matter but also enlighten project parties, anti-corruption institutions and advocates, contract

administrators, and policymakers about the barriers that significantly influence the effectiveness of ACMs

in project procurement and management. Thus, they can contribute to the development and enforcement of

ACMs that are effective to extirpate corrupt practices in project procurement and management.

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Figure 7.2: Hypothetical model of the study (expanded model).

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Table 7.5: Descriptive and Impact Evaluation of Barriers to effective application of ACMs
Code Variables Probability Severity Overall
Mean SD Sig N-V Rank Mean SD Sig N-V Rank Sig Impact N-V
BAC1 Political and structural barriers 3.65* 1.073 .000 0.72 9 3.95* 1.015 .000 1.00 1 14.42 3.80* 0.88
BAC2 Fear of insecurity. Example, fear of losing 3.77* 1.108 .000 0.92 3 3.82* .950 .000 0.81 3 14.40 3.79* 0.86
Job
BAC3 Fear of losing life 3.44 1.196 .006 0.38 14 3.27 1.190 .074 0.00 17 11.25 3.35 0.00
BAC4 Social misrepresentation 3.39 1.150 .010 0.30 15 3.42 1.167 .006 0.22 14 11.59 3.40 0.10
BAC5 Fear of being marginalized 3.61* 1.150 .000 0.66 10 3.37 1.258 .024 0.15 15 12.17 3.49* 0.27
BAC6 Fear of being caught reporting 3.39 1.164 .011 0.30 15 3.37 1.218 .020 0.15 15 11.42 3.38 0.06
BAC7 Social or occupational stigma and 3.48 .987 .000 0.44 13 3.61* 1.030 .000 0.50 9 12.56 3.54* 0.37
rejection
BAC8 Bureaucratic process of reporting corrupt 3.69* 1.080 .000 0.79 7 3.82* 1.109 .000 0.81 3 14.10 3.75* 0.78
cases
BAC9 Lack of independence 3.52* 1.098 .000 0.51 12 3.56* 1.196 .000 0.43 10 12.53 3.54* 0.37
BAC10 Fear of victimization 3.81* 1.114 .000 0.98 2 3.56* 1.288 .001 0.43 10 13.56 3.68* 0.65
BAC11 Inappropriate internal institution 3.21 1.073 .129 0.00 17 3.52* 1.036 .000 0.37 13 11.30 3.36 0.02
coordination/inter agency relations
BAC12 Perception of no better end result, distrust 3.74* 1.039 .000 0.87 4 3.63* 1.028 .000 0.53 5 13.58 3.68* 0.65
in system
BAC13 Lack of political will, A lack of political 3.73* 1.190 .000 0.85 5 3.63* 1.028 .000 0.53 5 13.54 3.68* 0.65
will by government officials and statutory
professional councils to fight corruption is
seen as an exacerbating factor
BAC14 Lack of knowledge and understand of their 3.82* .967 .000 1.00 1 3.90* .953 .000 0.93 2 14.90 3.86* 1.00
rights within a contractual environment,
difficulty in providing concrete evidence
BAC15 Inappropriate staffing 3.60* 1.108 .000 0.64 11 3.63* 1.120 .000 0.53 5 13.07 3.61* 0.51
BAC16 Lack of knowledge or non-familiarity with 3.69* 1.065 .000 0.79 7 3.56* 1.096 .000 0.43 10 13.14 3.62* 0.53
ethical codes organizational codes of
ethics
BAC17 Personal attitude, for example, lack of will 3.73* 1.043 .000 0.85 5 3.63* 1.075 .000 0.53 5 13.54 3.68* 0.65
to become involved in fighting corruption
Note: SD represents standard deviation; Sig represents significance; N-V represents normalized value; ‘*’ represents critical variables

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Table 7.6: Factor Analysis of Barriers

Code Variable C1 C2 C3 C4 Initial Extraction

Component1 Socio-Political Barriers (SPB)

BAC1 Political and structural barriers such as 0.875 1.00 0.854
instability
BAC12 Perception of no better result, distrust in the 0.717 1.00 0.669
system
BAC7 Social or occupational stigma and rejection 0.568 1.00 0.649
BAC8 The bureaucratic process of reporting corrupt 0.503 1.00 0.506
cases

Component2: Administrative Barriers (ADB)

BAC13 Lack of political will by government officials 0.753 1.00 0.689
and statutory professional councils to fight
corruption
BAC11 Inappropriate internal institution 0.703 1.00 0.622
coordination/inter agency relations
BAC15 Inappropriate staffing 0.655 1.00 0.474
BAC14 Lack of knowledge and understanding of their 0.544 1.00 0.513
rights within a contractual environment,
difficulty in providing concrete evidence

Component3: Psychosocial Barriers (PSB)

BAC17 Personal attitude, for example, lack of will to 0.785 1.00 0.676
become involved in fighting corruption
BAC4 Social misrepresentation 0.684 1.00 0.695
BAC3 Fear of losing life 0.562 1.00 0.601
BAC5 Fear of being marginalized 0.553 1.00 0.658
BAC16 Lack of knowledge or non-familiarity with 0.465 1.00 0.542
ethical codes organizational codes of ethics

Component4: Fear and insecurity (FIB)

BAC9 Lack of independence 0.843 1.00 0.791
BAC2 Fear of insecurity which includes fear of losing 0.665 1.00 0.695
Job
BAC6 Fear of being caught reporting 0.588 1.00 0.629
BAC10 Fear of victimization 0.413 1.00 0.366
Eigenvalues (EV) 6.168 1.684 1.480 1.297
Variance (VA) 36.282 9.907 8.705 7.627
Cumulative Variance (%) (CV%) 36.282 46.188 54.893 62.520
Construct Mean 3.69 3.62 3.50 3.60
N-values 1.00 0.65 0.00 0.49
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .778
Bartlett's Test of Sphericity Approx. Chi-Square 478.022
df 136
Sig. .000

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Constructs' Criticality Index

3.75

3.7

3.65

3.6

3.55

3.5

3.45

3.4
SPB ADB PSB FIB

Figure 7.3: Criticality Impact Indexes of the Barriers’ Constructs

7.3.3 Discussions

First, it must be emphasized that due to the copious amount of information gathered from the results,

the discussion will be limited to the explications of the barriers constructs in conjunction with the PLS-

SEM results. Thus, since the primary emphasis is on the barriers and all the constructs encapsulated

under the barriers were found critical, the discussion will consider all the constructs from the topmost

ranked barriers to the least. The analyses were conducted to identify not only the critical barriers and

their associated constructs but also test the research hypotheses. While the individual barriers will be

thoroughly explicated under their respective constructs, a summary of the results indicated high

criticality indexes among all the barriers. Of the 17 barriers examined, 13 had high impact indexes,

indicating that almost 80% of the identified barriers were critical in the context of project procurement

and management processes. Moreover, the four constructs developed by FA were also found critical.

To present thorough explications on the developed constructs and their respective variables, the adopted

approaches with their respective results are presented in the next section.

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7.3.4 The criticality of constructs and the variables

As stated earlier, FA was employed to establish the four respective constructs. The developed constructs

were labeled based on the central thematic construction of the variables captured under them (Zhang et

al. 2016; Owusu and Chan 2017). The four constructs are psychosocial barriers, social-political barriers,

fear and insecurity, and administrative barriers. Moreover, even though the categorization of the ACMs

was not conducted in this study, PLS-SEM was used to confirm the ACM constructs used in this study.

The ACM constructs, therefore, included regulatory measures, administrative measures, promotional

measures, compliance measures, probing measures, and reactive measures (Owusu et al. 2018). Since

the detailed discussions on the ACMs have already been conducted in the study of Owusu et al. (2018),

the present study rather discusses the significant influences of the barriers on the ACMs. However, the

established hypothesis paths (i.e., the impacts of the barriers on the ACMs) are tested later in this study.

7.3.5 Measurement Models Evaluation

Table 7.7: Measurement Validity of the constructs

Latent Variables (Constructs) Code CA rho_A CR AVE
Anti-Corruption Measures (ACMs)
Administrative Measures ADM 0.76 0.81 0.84 0.51
Compliance Measures CPM 0.67 0.70 0.82 0.60
Probing Measures PBM 0.79 0.79 0.85 0.54
Promotional Measures PRM 0.83 0.85 0.87 0.54
Reactive Measures REM 0.74 0.82 0.83 0.55
Regulatory Measures RGM 0.64 0.75 0.84 0.73
Barriers to Against ACM Effectiveness
Socio-Political Barriers SPB 0.79 1.23 0.84 0.58
Administrative Barriers ADB 0.74 0.79 0.85 0.65
Psychosocial Barriers PSB 0.76 0.82 0.83 0.57
Fear and Insecurity FIB 0.65 1.03 0.76 0.53
CA represents Cronbach's; AVE represents Alpha Average Variance Extracted; CR
represents Composite Reliability

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Table 7.8: Discriminant Validity of the constructs

Codes ADB ADM CPM FIB PBM PRM PSB REM RGM SPB
ADM 0.803
ADM 0.104 0.716
CPM 0.068 0.683 0.774
FIB 0.277 0.157 0.205 0.727
PBM 0.191 0.71 0.598 -0.015 0.735
PRM 0.217 0.778 0.743 0.209 0.661 0.731
PSB 0.525 0.17 0.173 0.542 0.097 0.259 0.752
REM 0.205 0.663 0.592 0.109 0.791 0.732 0.326 0.744
RGM 0.048 0.679 0.496 0.383 0.546 0.675 0.12 0.532 0.853
SPB 0.461 -0.304 -0.206 0.463 -0.25 -0.152 0.525 -0.058 0.001 0.763

7.3.4.1 Socio-Political Construct (SPC)

This construct comprises of both social and political factors as defined by Merriam Webster dictionary

(2018). It was developed using FA and encapsulated four critical variables. From the most critical to

the least, the variables captured under this construct are political instability with an impact index of

3.80, the complex bureaucratic and social structures for reporting corrupt cases, with a high impact

index of 3.75. Bowen et al. (2007) revealed the influence of politics on the problematic barriers in the

South African construction industry. Similar identifications were found in the studies of Tabish and Jha

(2011) that was conducted in India, as we as Shan et al. (2017) conducted in China. With the contexts

noted above, it can be pointed that even though this barrier can hinder the effectiveness of ACMs in

different countries from around the world, the study indicates that this political influence as a primary

indicator is more critical in the developing context. It was, therefore, unsurprising to identify the

obstructions posed by politics within the context of public-project procurement and management in the

developing region to be the most critical variable under this construct. Politics affects corruption in

many ways and has been identified as one of the powerful instigators of corruption in many parts of the

world and also in public procurement and management of megaprojects (Soroide 2002; Owusu et al.

2018; Ameyaw et al. 2017). A direct implication is its influence on the effectiveness of the state’s laws

in general. This case may exemplify the macro effects of the negative implications of political

structures. The result of such practices (political corruption) is that public institutions’ departments and

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boards suffer a fair share of the acts. At the micro-level, it advocates against any unhealthy decisions

or practices from a political standpoint. This construct is better explained in the context of political

corruption, where government officials and associates around them take advantage of their political

position to exploit public office for illegal personal gains. Gale (2006) referred to this as government

corruption. Thus, in effect, it may simply be regarded as government impediments and cuts across the

entire public sector. Being one of the most complicated barriers because of the context involved, past

studies have emphasized on some mitigation mechanisms, such as efficient checks and balances on the

various arms of government. Moreover, given the complications attached to this barrier, political issues

regarding corruption cannot be solved at the project level (Owusu et al. 2018). However, advocates

may call for reinforcement actions on other arms of government to help check the faulty arm (Zou

2006; Owusu et al. 20019). For instance, as the barrier is instigated at the executive level, the judicial

or legislative arm of government can be called upon to help check the case at hand.

Reporting a corrupt case can be complex, especially if the context within which the corrupt act to be

reported consists of the extreme hierarchical order of power (Osei-Tut et al. 2010). It must, however,

be emphasized that the phobia attached to reporting a corrupt case in the first instance put people off

(Bowen et al. 2012). If one must also go through bureaucracy to get a case reported coupled with the

immense fear of reporting, it is somewhat logical and safe not to get involved in such trauma at all. As

a result, advocates claimed the need to provide accessible and safer procedures of reporting a suspected

or identified corrupt case. Among these include the need to provide an efficient hotline for reporting

corrupt cases (Powell 2006). This practical process has enabled different regions and institutions to get

notified of any corrupt act. The remaining two are i) the lackadaisical attitude towards the adherence

of anti-corruption stipulations emanating from the perception of no better results and ii) the lack of trust

in the system (Ameyaw et al. 2017; Owusu and Chan 2019; Bowen et al. 2012). Lastly, the final variable

under this contract is the occupational or social rejection and stigma by peers resulting from adherence

to anti-corruption policies or not indulgence in a corporate, corrupt act (Krishnan 2009; Bowen 2007).

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Surprisingly, among four significant relations identified as confirmatory justification to the

ineffectiveness of ACMs, the socio-political construct was identified to have three significant negative

influence on the ACM constructs. Specifically, of the six anti-corruption constructs that were observed,

the socio-political construct was revealed to have strong negative influences on i) administrative

measures [with the highest path coefficient of 0.656 indicating a strong impact and a t-value of 2.810

at significant level of 0.005], ii) compliance measures [also with the high path coefficient of 0.505

indicating a strong impact and a t-value of 2.308 at significant level of 0.021]; iii) probing measures

[obtaining a path coefficient of 0.506 indicating a strong impact and a t-value of 1.832 at significant

level of 0.067] and lastly on promotional measures [with the highest path coefficient of 0.517 indicating

a strong impact and a t-value of 2.416 at significant level of 0.016]. Therefore, out of the six

hypothetical relationships established to either confirm or disprove the negative socio-political

influence on the six anti-corruption constructs, the socio-political construct confirmed its criticality as

not only by having the highest impact index but also been identified as the main inhibiting force against

four significant anti-corruption constructs. A part of the justification can be deduced from previous

studies where some unethical or illegal political actions pose negative influences not only on anti-

corruption policies but also the entire economic strength of the State.

7.3.4.2 Administrative barriers

Administrative barriers’ construct was another concern after socio-political construct. It was, however,

interesting to note that the criticality of the barriers’ construct followed the hierarchical order of power.

That is from the government level (where the parties are often government officials) to the institutional

or administrative level. A total number of four variables were also captured under this construct, with

an average criticality impact of 3.63. This, too, indicates that, analogous to the government barriers, the

administrative barriers were also identified to be critical. The four variables under this construct are:

inadequate possession of the needed knowledge and understanding of a contractual party in a

contractual environment (Bowen et al. 2012; Stansbury 2009; Shan et al. 2015) and the difficulty in

providing necessary solid evidence in the event of a corrupt incident (Owusu and Chan 2019; Bowen

et al. 2012). Administratively, contracting parties are expected to know and understand every critical

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stipulation presented in a contract document and any other document indicating the responsibilities of

each party. Lacking knowledge on some of these critical contract requirements will not only leave the

uninformed party ignorant about what is expected of him or her but also ignorant about the

consequences of the actions of him/herself and other team members.

Consequently, in the event of any corrupt act (whether knowingly or unknowingly) the ignorant party

may not be able to render any justification for his or her innocence. Thus, re-emphasizing on the

common phrase "ignorantia juris neminem excuseat", meaning "ignorance of the law excuses no one"

(Marriam-Webster 2018). It is, therefore, appropriate for all project team members to fully know and

understand their rights and limitations in a contractual environment. Other critical variables under this

construct are the lack of political will by officials to limit or fight corruption, and inappropriate staffing

(Ameyaw et al. 2017; Bowen et al. 2012; Osei-Tutu et al. 2010). Similar to the first case, inappropriate

staffing is noted as a primary contributor to knowledge gap creation (Owusu and Chan 2019). This

happens when an employee is assigned a responsibility that he or she knows little or nothing about.

Therefore, in the event of poor or non-performance, the employee is likely to be tempted to pay himself

out just to maintain a clean name. Because of this, they become willing to contribute to corruption.

Again, this may serve as one of the main contributory factors to the ineffectiveness of ACMs resulting

from inappropriate staffing.

However, regarding the PLS-SEM model, the administrative barriers construct was identified to have

a neutral, negative correlation with one of the most significant ACMs constructs: probing measures'

construct obtaining a t-value of 1.778 at a significant level of 1.96 and a path co-efficient of 0.324

(signifying a neutral level of influence). Although most of the negative impacts were attributed to the

criticality of socio-political constructs, administrative barriers' construct was identified to have a

significant negative impact on one of the most promising anti-corruption constructs, probing measures.

Probing measures have played a key role in dealing with corruption in Hong Kong (Wai, 2006). Wai

(2006) indicated that the Department of Hong Kong’s Independence Commission against Corruption

(ICAC) unit that most funds are expended is the operations department, which is responsible for

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conducting strategic and effective investigations. In short, the results indicate that the administrative

barriers have a very strong and significant negative influence on the effectiveness of probing measures

in Ghana. Thus, there is the need to strategically develop administrative measures aimed at extirpating

their negative influence on probing measures as well as enhance the effectiveness of ACMs in general.

Table 7.9: Structural model Evaluation

No Paths (O) (M) (STDEV) (|O/STDEV|) P Values Inference
ADB → ADM 0.191 0.169 0.174 1.099 0.272 NS
ADB → CPM 0.101 0.048 0.177 0.57 0.569 NS
ADB → PBM 0.324 0.282 0.182 1.778 0.075* Supported
ADB → PRM 0.247 0.221 0.182 1.354 0.176 NS
ADB → REM 0.136 0.132 0.168 0.807 0.42 NS
ADB → RGM 0.041 0.018 0.213 0.194 0.846 NS
FIB → ADM 0.259 0.215 0.235 1.102 0.271 NS
FIB → CPM 0.286 0.265 0.255 1.122 0.262 NS
FIB → PBM 0.035 0.107 0.286 0.124 0.902 NS
FIB → PRM 0.230 0.137 0.249 0.922 0.356 NS
FIB → REM 0.008 0.082 0.22 0.034 0.973 NS
FIB → RGM 0.506 0.359 0.298 1.698 0.09* Supported
PSB → ADM 0.274 0.243 0.269 1.016 0.31 NS
PSB → CPM 0.23 0.234 0.19 1.212 0.225 NS
PSB → PBM 0.174 0.231 0.313 0.555 0.579 NS
PSB → PRM 0.275 0.3 0.216 1.278 0.201 NS
PSB → REM 0.443 0.426 0.219 2.026 0.043** Supported
PSB → RGM 0.06 0.02 0.203 0.294 0.769 NS
SPB → ADM 0.656 0.547 0.233 2.810 0.005*** Supported
SPB → CPM 0.505 0.413 0.219 2.308 0.021** Supported
SPB → PBM 0.506 0.357 0.276 1.832 0.067* Supported
SPB → PRM 0.517 0.440 0.214 2.416 0.016** Supported
SPB → REM 0.349 0.261 0.221 1.582 0.114 NS
SPB → RGM 0.221 0.178 0.213 1.04 0.298 NS
Note: (O) = Original Sample; (M) = Sample Mean; (STDEV) = Standard Deviation; (|O/STDEV|) = T
Statistics; No = Number of hypothetical relationships tested; NS represents not supported
***2.58 (at a significant level of 0.01); **1.96 (at a significant level of 0.05) and *1.65 (at a significant
level of 0.1); NS means not supported

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Table 7.9 presents the results of the bootstrapping. It demonstrates the various significant paths linking

the barriers to the ACMs. Per the bootstrapping results, seven of the 24 paths were supported as their

paths had t-values above 1.65, 1.96, or 2.58. This implies that the seven supported paths were

statistically significant at 0.1, 0.05, and 0.01, respectively. These seven paths were: administrative

barriers to probing measures, fear and insecurity to regulatory measures, psychosocial barriers to

reactive measures, and lastly socio-political barriers to four different ACM constructs – administrative

measures, compliance measures, probing measures, and promotional measures. Therefore, all the

barriers were identified to have a significant impact on at least each of the ACM constructs.

However, the results revealed the criticality of the impact on probing measures, which were identified

as the only ACM construct that had two significant constructs of barriers affecting its effectiveness.

Path coefficients are identical to the weights of regression (Ozorhon and Oral 2017). The greater the

path coefficient, the more influential an independent variable on a dependent variable (Aibinu and Al-

Lawati 2010). Therefore, a path coefficient value within the range of 0.1 to 0.3 connotes a poor level

of influence, 0.3 to 0.5 represents a neutral level of influence, and 0.5 to 1.0 illustrates a strong impact

(Murari 2015). In this study, five of the seven significant paths had their coefficients to be above 0.50.

These are SPB → ADM, SPB → CPM, SPB → PBM, SPB → PRM, FIB → RGM, indicating strong

influence. The remaining two had their coefficients at the moderate levels (i.e., between 0.3 and 0.5).

These are ADB → PBM, PSB → REM. Lastly, all the critical paths that the socio-political barriers had

on the respective ACM constructs were identified to be within the range of 0.50 to 1.0, indicating that

the construct was not only critical as a standalone construct but also has a strong negative influence on

more than 70% of the ACMs. The final model indicating the influence of each construct and the

significance of each path is presented in Fig. 7.4.

7.3.4.3 Fear and insecurity (FIB)

Fear is commonly defined as a feeling impelled by a perceived threat, whereas insecurity refers to the

lack of confidence or uncertainty about oneself (Cambridge Dictionary 2018). The FIB construct was

also developed by FA and ranked third with a criticality impact index of 3.60, which is critical. Four

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variables were captured under this construct. From the most critical to the least, the variables include

fear of insecurity, the fear of victimization, the lack of independence, and the fear of being caught

reporting. It is unsurprising that the respondents revealed the fear of losing their job to be the topmost

barrier under this construct. As highlighted in the PSB section, whereas some people prefer to keep

mute to ensure that their lives are not threatened, others or the same people would as well be unwilling

to reveal a corrupt case (whether as a witness or a suspected case) to secure their jobs (Owusu and Chan

2019). Moreover, in developing countries, securing a job is highly competitive, the willingness to go

the extra mile to keep one’s job free from threat is always worth taking even at the expense of reporting

corrupt practices. This is where other barriers (such as the bureaucratic complexities that one must go

through before reporting a corrupt case) also play a key role.

Thus, the impetus of relaying a corrupt case is lost in the end to allow corruption to go unreported. A

similar phobia is attached to the other critical barriers under this construct, such as the fear of being

victimized coupled with the lack of independent pose a significant threat of putting an end to corruption.

Thus, the intended effectiveness of the stipulated ACMs is aborted due to these unresolved hindering

variables. Moreover, among the hypothetical relationships drawn, the construct of fear and insecurity

was also identified to have a strong influence on one of the ACMs’ constructs, regulatory measures.

Analogous to other critical and significant paths, the impact of FIB on RGM was identified to be one

of the five most significant paths with a t-value of 1.698 at a significant level of 0.09 and a path co-

efficient of 0.506 (signifying a strong level of influence).

Simply put, the measurement items under the construct of fear and insecurity are the contributory

factors that hamper the effectiveness of ACMs from the perspective of limiting the effectiveness of

stipulated regulatory measures. In the Owusu et al.’s (2017) study, regulatory measures are identified

to be statutory measures enforced to enhance corrupt-free societies. It is an undeniable fact that most

Ghanaians perceive the police service to be very corrupt (Pyman et al. 2012). Therefore, in most

developing regions such as Ghana, the fear or the sense of insecurity attached to complying with

regulatory measures such as reporting a corrupt case to the state’s law enforcement agency is very high.

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This is further justified by the corrupt behaviors of some of the law enforcement institutions, such as

the police force. Thus, in effect, reporting a corrupt case to a law enforcement agent who is, in turn,

corrupt can go to the extent of putting one’s security or life at risk. Most especially if the suspected or

the witnessed case concerns a powerful public official who often buys the trust and services of some of

these law-enforcing agents. This is one of the relationships that transpire between the fear and security

of a person against the effectiveness of stipulated ACMs from the perspective of regulatory measures.

This, however, calls for the critical need of attention towards [regulatory] measures that are aimed at

extirpating the negative forces of fear and insecurity attached to the effectiveness of enforced ACMs.

7.3.4.4 Psychosocial Barriers (PSB)

Finally, the PSB construct was identified to be the fourth-ranked construct among the others. As the

name implies, the term lends itself to the interrelation of social attributes and the psychological make-

up of a person and their impact on the ACMs stipulated to guide the procurement and management of

public projects (Owusu and Chan 2019). Even though this term is mentioned in psychology and

behavioral studies such as Greitzer (2013) and Heiser (2001), one of its first explication of this term in

corruption-related research in this domain was offered by Owusu et al. (2017). The authors captured

this construct as one of the causal constructs of corruption in public project management. Even though

it can be regarded as the least ranked among the others, it was also revealed to be a critical construct

just as the others with its criticality impact index as 3.50.

The most critical variable within this construct was identified to be the lack of knowledge or non-

familiarity with ethical codes organizational codes of ethics. This variable had an overall impact index

of 3.62, with its probability index to be 3.69 and its severity index as 3.56. Often, this barrier exists not

only because parties within a specific context are ignorant about the code of ethics and professional

standards that ensures the right thing to be done and behavior to be expected but also attributed to the

perception of one’s belief to be an ethical person. Persons within this category often have a firm belief

in their ethical values rather than what has been stipulated by his/her organization (Owusu and Chan

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2019). As such, the person may be susceptible to breach any of the obligations within the stipulated

codes due to ignorance.

Moreover, if the person’s actions object to regulations that are meant to extirpate corrupt practices, the

person becomes either a liable party or contributor to corrupt practices rather than to prevent their

incidence. A recent study by Owusu and Chan (2018) revealed this to be one of the critical barriers in

the developing region. The remaining critical variables under this construct were personal attitude

which includes the lack of will to become involved in fighting corruption with a criticality index impact

of 3.68 and the fear of being marginalized with an index of 3.49 (Shan et al. 2015; Bowen et al. 2012;

Bowen et al. 2007; Porter 1999). Lastly, even though the fear attached to losing one’s life as well as

being misrepresented were captured under this construct, the experts were of the view that they were

not that critical as compared to the barriers captured under this construct. Their respective indexes were,

therefore, 3.35 and 3.40, respectively. A recent report by TI (2018) reported on a witness of a corruption

case who lost his life after expressing fears regarding his safety. It was as well reported that the son of

the witness also lost his life three days after the death of his father. Cases like this often scare or puts

people off in reporting a corrupt case to protect their lives.

Despite the fact of many pieces of evidence of people who have lost their lives as a result of reporting

a corruption case or being a witness to corruption, this is one of the recent among the many cases

reported during the period of conducting this study. The question is, how can someone ensure his/her

safety after being a witness to corruption case or reporting a corrupt incident? There is, therefore, the

need for this kind of study, especially in the context of developing regions. Regarding the PLS-SEM

results, the PSB construct was identified to have one strong significant impact on reactive measures.

That is, the measurement items within the psychosocial barriers were somewhat noted to have a driving

influence on the ineffectiveness of the reactive measures construct. However, the impact of this

construct on reactive measures was identified to be moderately significant, with a t-value of 2.026 at a

significant level of 0.04 and a path coefficient of 0.443. Thus, there is the need to pay critical attention

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to the measures that will not only help mitigate corruption but always address some of the criticalities

and concerns associated with the PSB construct.

Figure 7.4: Structural Equation Model of the study (Expanded Model)

7.4 Chapter Summary

As one of the huge leaps in project management scholarship on the issue of corruption, this section of

the study sought to explore the dynamic and significant impacts of the barriers that hinder the

effectiveness of ACMs of the established ACMs constructs in public project procurement and

management. With the noted ACMs identified as probing, regulatory, promotional, administrative,

compliance, and reactive measures, this study first explored the criticality of the barriers identified to

be psychosocial, socio-political, fear and insecurity, and administrative barriers and later, examined

their influences on the established ACMs' constructs. The motivation behind this study section stems

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from four primary concerns. They are: 1) the lack of attention given to the exploration of corruption

concerns in project management scholarship; 2) the ineffectiveness of anti-corruption stipulations to

check the prevalence of corrupt practices in public projects in developing countries; 3) limited

explorative studies on the criticality of the ACM barriers in both project management-related literature

and the developing context and 4) the significant relationship of the barriers on the ACM construct to

facilitate decision making and future research.

However, to realize the aim, two key objectives were formulated together with twenty-four hypotheses.

An expert survey was conducted with 62 professionals involved in the modus operandi of project

procurement and management in the developing context. Different relevant techniques and tools

ranging from descriptive statistics to FA and PLS-SEM were employed to conduct the pre-test and the

main analysis of the data gathered. The results revealed the criticality of all the five constructs of

barriers in the context of Ghana with the most critical construct identified to be socio-political barriers,

and the most vital variable identified to be the lack of knowledge of a party within a contractual

environment followed by political instabilities. With over 24 hypothetical relationships drawn to be

tested, seven relationships were revealed to be significant. Thus, seven significant relationships

revealed the impact and negative influence of the barriers on the ACM constructs. The socio-political

construct, which was identified to be the most critical construct, was identified to have the highest

negative influence on four different constructs, namely administrative, compliance, probing, and

promotional measures. This indicates that in as much as all the barriers were identified to be critical,

the most significant relationships that must be considered with a greater degree of attention as compared

to the others are the significant negative relationships identified by the PLS results. Other significant

paths include the administrative barriers on probing measures, fear and insecurity on regulatory

measures, and lastly, psychosocial barriers on reactive measures.

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CHAPTER 8 – GLOBAL PERSPECTIVES – COMPARATIVE

ANALYSIS AND EXEMPLARY LESSONS

8.1 Introduction

Previous studies and reports emphasize the contextual disparities on corruption pervasiveness and

control in the procurement process between countries in the developed and developing world (Ateljevic

and Budak 2010; Osei Tutu et al. 2010; Agaba and Shipman 2007). However, empirical assessments

of these presuppositions are lacking. Moreover, while there are varied suppositions on the procurement

stages’ susceptibilities to corruption, a holistic empirical evaluation of the stages regarding how

susceptible they are to corruption is not available. Several suppositions revolve around the degrees of

criticalities among the stages of the procurement process (Chartered Institute of Building (CIOB) 2013;

Søreide 2002; Arewa and Farrell 2015). However, it is possible that different geographical contexts

may indicate different levels of corruption criticality and the mitigation measures to expunge corrupt

practices in the procurement process.

Given the polarization of presuppositions regarding the susceptibility and proliferation of corrupt

practices in the procurement process and the lack of empirical justification, this section of the study

attempts to answer the following question: how susceptible are the stages involved in the project

procurement process to corruption and what are the critical forms prevalent at each stage in both

developed and the developing countries? Furthermore, do all activities within the procurement process

require an analogous amount of time and effort in extirpating their proliferation of corruption? In

response to these questions, this section of the study presents empirical evidence of industry experts

from both developed and developing countries concerning the susceptibility of the procurement stages

to corruption and the prevalence of corruption forms in the procurement process. Concomitant

objectives are to (1) explore the comparative disparities of corruption prevalence and anti-corruption

effectiveness in developing and developed countries; (2) examine the degree of vulnerability of the IP

stages and activities to corruption; and (3) determine the most prevalent corruption forms (CFs) at each

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stage and within each activity of the procurement chain in both developed and developing countries.

To answer the questions above, a three-stage iterative approach was adopted. First, a systematic

literature review is conducted to identify the individual activities and stages of the procurement process.

Second, a survey of international experts was later conducted using purposive sampling. Third, a

number of descriptive tools were employed to analyze the data gathered. Findings reveal that the

evaluation of tenders received, and the selection of a suitable contractor were identified as the most

susceptible activities within the procurement process. However, the results of the two contexts were

significantly dissimilar. Theoretically, since previous studies have not empirically addressed these

issues from the perspective of international experts, the findings represent the first to address

susceptibility levels of the different activities and stages of the procurement process and the criticality

of the primary constructs of corrupt practices. Consequently, such work contributes to the existing body

of knowledge (BoK) on corruption-related studies in project management. Moreover, this section of

the study provides a richer understanding of the dynamism and behavior of corrupt practices in the

supply chain of the procurement process. Cumulatively, the research offers anti-corruption institutions,

policymakers, and industry practitioners with the knowledge that may assist in the development and

implementation of more stringent anti-corruption tools and measures for reducing or expunging the

identified CFs practices at specific stages of the procurement process. The work also serves to provide

a foundation for further empirical studies on the subject matter.

8.2 Findings from experts survey

The results are presented in the order of the study’s objectives, and the first section of the results

presents the outcome for the first two objectives. To begin, the measurement items which encapsulates

twenty-one distinct activities were captured under the four main constructs of the procurement process.

The relative rank of each activity was obtained from the opinions of the participating experts involved

(e.g., mean scores from the questionnaire survey). Even though an overview of the results is presented

in Tables 8.1 and 8.2, the discussions primarily focus on the two contextual backgrounds of the experts

(i.e., developed and developing countries). Tables 8.1 and 8.2, therefore, present a summary of the

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susceptibility levels (presented by the mean indexes) of the stages together with significant disparities

between stages or activities when comparing the two economies (shown by the Mann-Whitney U test

results). Indeed, the results affirm the distinct and prevailing levels of corruption vulnerabilities

between the two economies as substantiated by previous studies and world reports on corruption

indexes.

Table 8.1: Descriptive Statistics and normality test of procurement activities

No Procurement Process Code Mean SD p-value CR OR
1 Pre- Define requirements PCS1 2.48 1.11 0.000 4 17
2 Contract Procurement process planning and
2.45 1.06 0.000
stage strategy development PCS2 5 18
3 (PCS) Pre-tender survey PCS3 2.66 1.25 0.000 3 12
4 Getting required approvals PCS4 2.74 1.34 0.000 2 7
5 Tenders’ solicitation PCS5 2.94 1.50 0.004 1 3
6 Receipt of tenders PCS6 2.30 1.39 0.000 6 21

7 Contract Pre-tender meeting (to establish

Stage assessment criteria and plan as well 2.66 1.27 0.000
(CTS) as points to be allocated) CTS1 4 12
8 Tender evaluation (evaluation to
3.03 1.45 0.011
accept or decline tenders) CTS2 2 2
9 Contractor selection CTS3 3.14 1.47 0.051 1 1
10 Contract award/procure order CTS4 2.91 1.43 0.001 3 4
11 Contract preparation and signing CTS5 2.43 1.27 0.000 5 19

12 Contract Issuing contract revisions CAS1 2.80 1.25 0.000 1 6

13 administ Progress monitoring CAS2 2.72 1.34 0.000 3 8
14 ration Follow up delivery CAS3 2.60 1.26 0.000 4 15
15 stage Administer interim or progress CAS4 2 8
2.72 1.42 0.000
(CAS) payments

16 Post Filing of final action PCP1 2.65 1.36 0.000 4 14

17 contract Issue final contract amendment PCP2 2.68 1.34 0.000 3 11
18 phase Finalize financial audits PCP3 2.69 1.44 0.000 2 10
19 (PCP) Verify delivery/completed reports PCP4 2.91 1.36 0.001 1 4
20 Returning performance bonds and PCP5 6 20
2.34 1.31 0.000
contract close-out
21 Confirm completeness and accuracy
2.59 1.33 0.000
of file documentation PCP6 5 16
*
Note: indicates data with significant results of one-sample t-test (p < 0.05); Cronbach's Alpha =
0.962; Actual Chi-Square value = 65.440; Critical Chi-Square value = 31.410; df = 20; Asymp. Sig. of
Kendall’s W = 0.000; N=64; Construct Mean scores (MS): PSC=2.59; CTS= 2.83; CAS=2.71; PCP=
2.64.CR represents construct ranking: OR represents overall ranking.

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Table 8.2: Stages of the Procurement Process

No Procurement Process Developing Region Respondents Developed Region Respondents Mann-Whitney U test
a
(TS ) Mean Std. Dev Sig CR OR Mean SD Sig. CR OR U Sta W* Z P value
1 Pre-contract PCS1 2.6129 1.202 0.083 6 21 2.35 1.01 0.001 1 1 468.000 1063.000 -.803 0.422
2 stage PCS2 2.7742 1.06 0.243 5 20 2.15 .99 0.000 3 5 352.000 947.000 -2.401 0.016b
3 PCS3 3.1935 1.14 0.351 3 15 2.18 1.17 0.000 2 4 284.000 879.000 -3.292 0.001b
4 PCS4 3.5806 1.15 0.009 2 6 1.97 1.14 0.000 5 8 184.500 779.500 -4.626 0.000b
5 PCS5 3.8710 1.09 0.000 1 4 2.09 1.31 0.000 4 6 180.000 775.000 -4.714 0.000b
6 PCS6 3.0333 1.38 0.895 4 18 1.65 1.04 0.000 6 13 219.000 814.000 -4.108 0.000b
7 Contract stage CTS1 3.3226 1.17 0.134 4 11 2.09 1.04 0.000 2 6 230.000 825.000 -4.010 0.000b
8 CTS2 4.1290 0.81 0.000 2 2 2.03 1.14 0.000 3 7 96.000 691.000 -5.856 0.000b
9 CTS3 4.1935 0.87 0.000 1 1 2.18 1.22 0.000 1 4 114.000 709.000 -5.584 0.000b
10 CTS4 3.9677 0.91 0.000 3 3 1.94 1.10 0.000 4 9 106.500 701.500 -5.663 0.000b
11 CTS5 3.1613 1.16 0.444 5 16 1.77 0.99 0.000 5 11 192.000 787.000 -4.536 0.000b
12 Contract CAS1 3.2903 1.10 0.153 2 12 2.35 1.23 0.004 1 1 305.000 900.000 -3.003 0.003b
13 administration CAS2 3.2903 1.19 0.184 2 12 2.21 1.27 0.001 2 3 281.500 876.500 -3.321 0.001b
14 stage CAS3 3.0968 1.22 0.662 4 17 2.15 1.13 0.000 3 5 305.000 900.000 -3.001 0.003b
15 CAS4 3.5484 1.18 0.015 1 8 1.97 1.19 0.000 4 8 195.500 790.500 -4.467 0.000b
16 Post contract PCP1 3.3871 1.09 0.056 3 9 1.97 1.24 0.000 4 8 213.500 808.500 -4.243 0.000b
17 phase PCP2 3.3871 1.09 0.056 3 9 2.03 1.22 0.000 2 7 224.000 819.000 -4.109 0.000b
18 PCP3 3.5806 1.18 0.010 2 7 1.88 1.15 0.000 5 10 177.000 772.000 -4.742 0.000b
19 PCP4 3.8065 1.01 0.000 1 5 2.09 1.08 0.000 1 6 147.500 742.500 -5.131 0.000b
20 PCP5 3.0323 1.35 0.895 6 19 1.71 0.91 0.000 6 12 234.000 829.000 -3.990 0.000b
21 PCP6 3.2581 1.26 0.265 5 14 1.97 1.09 0.000 3 8 239.500 834.500 -3.876 0.000b
Note: TS. Grouping variable: contextual groups (i.e., developed and developing countries)
b. Results indicating significant differences (data with significant results)
* represents data with significant results; Sta* represents U statistics; W* represents Wilcoxon W; SD represents standard deviation.
Constructs’ MS for developing economies: PCS = 3.18; CTS = 3.76; CAS = 3.30; PCP =3.41
Constructs’ MS for developed economies: PCS = 2.07; CTS = 2.00; CAS = 2.17; PCP = 1.94.

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Given an almost uniform dispersion of both developed and developing countries, Tables 8.1 and 8.2

demonstrate an overall susceptibility level of the procurement activities with their respective stages.

Almost all the mean values fall within the range of neutral and are attributed to the balancing effects of

both economies. The discussions are presented on a comparative basis of the representative contexts to

highlight significant disparities between them (i.e., the developed and the developing countries).

Although the respondents’ overall opinion revealed relatively neutral levels of susceptibility in all the

activities, stages that had the highest scores were the contract stage and the contract administration

stage, which had MS of 2.83 and 2.71, respectively. However, cases between developed and developing

countries were different, with several being regarded as more susceptible to corruption within

developing countries (discussed later in the study).

The procurement activities in developing world countries are empirically identified to be more

vulnerable than countries within the developed world. While this may be an undebatable argument, the

MWU statistics also revealed high statistically significant differences between analogous stages of the

two contexts. Out of the overall 21 activities, the MWU test results indicated that 20 stages (with the

exceptions of PCS1) are statistically different regarding the levels of the activities’ vulnerabilities to

corrupt practices in the contexts of both economies. In all, the CTS construct of the developing countries

was identified to be the most vulnerable stage of the procurement process, with a mean score of 3.76.

This construct encapsulates activities such as the selection of a contractor (CTS3), which had the

highest mean score and was regarded as the most vulnerable activity in the procurement process. Tender

evaluation (review to approve or reject bids) (CTS2) and the award of contract or purchase order

(CTS4) came second and third places in both CTS construct and the overall rank. Pre-tender meeting

(CTS1) and the preparation came third in the CTS category, and 12th in the overall and signing of

contract (CTS5) fifth the CTS construct and 16th in the overall scores. The significance of susceptibility

magnitude of individual stage-by-stage comparisons of all the 21 activities, which demonstrate how

momentous an individual procurement activity is over other activities within the same construct, is

presented in the next section.

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Moreover, per the actual mean results, there was at least one vulnerable activity in each stage. For

instance, PCS4 under the pre-contract stage or CAS4 under the contract administration stage. However,

the situation was dissimilar in the context of the developed countries as the mean indexes for all the

various activities were identified to be moderately critical.

8.2.1 Stages-Comparative Results

To ascertain the order of distinctiveness between the two separate economies, the comparisons of the

stages were made based on their constructs and economies. Tables 8.3 and 8.4 present the stage-by-

stage comparisons of the constructs in the developed and developing countries, respectively.

Table 8.3: Developing Countries

Stage 1 – Pre -Contract stage Stage 2 – Contract Stage
Code PCS5 PCS4 PCS3 PCS2 PCS1 PCS6 CTS3 CTS2 CTS4 CTS1 CTS5
PCS5 - 0.501 0.792 0.834 0.267 0.009a CTS3 - 0.642 0.205 0.003 a 0.001 a
PCS4 - 0.312 0.266 0.079 0.042 a CTS2 - 0.426 0.005 a 0.002 a
PCS3 - 0.802 0.491 0.005 a CTS4 - 0.015 0.001 a
PCS2 - 0.229 0.017 a CTS1 - 0.514
a CTS5
PCS1 - 0.006 -
PCS6 - -

Stage 3 – Contract administration stage Stage 4 – Post contract phase

Code CAS4 CAS2 CAS1 CAS3 Code PCP4 PCP3 PCP2 PCP1 PCP6 PCP5
a
CAS4 - 0.417 0.313 0.077 PCP4 - 0.253 0.086 0.099 0.029 0.003 a
CAS2 - 1.000 0.162 PCP3 - 0.288 0.248 0.161 0.062
CAS1 - 0.396 PCP2 - 1.000 0.593 0.266
CAS3 - PCP1 - 0.551 0.220
PCP6 - 0.453
PCP5 -
Note: indicates Wilcoxon’s signed rank test result is significant at p-value < .05, indicating that the stage-by-stage
a

comparisons were statistically different

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Table 8.4: Developed Countries

Stage 1 – Pre -Contract stage Stage 2 – Contract Stage
Code PCS1 PCS3 PCS2 PCS5 PCS4 PCS6 Code CTS3 CTS1 CTS2 CTS4 CTS5
a
PCS1 - 0.491 0.229 0.267 0.079 0.006 CTS3 - 0.520 0.319 0.102 0.034 a
a
PCS3 - 0.802 0.792 0.312 0.005 CTS1 - 0.805 0.386 0.102
a
PCS2 - 0.834 0.266 0.017 CTS2 - 0.509 0.138
PCS5 - 0.501 0.009 a CTS4 - 0.211
a
PCS4 - 0.042 CTS5 -
PCS6 - -
Stage 3 – Contract administration stage Stage 4 – Post contract phase
Code CAS1 CAS2 CAS3 CAS4 Code PCP4 PCP2 PCP6 PCP1 PCP3 PCP5
CAS1 - 0.371 0.197 0.011 a PCP4 - 0.527 0.380 0.458 0.131 0.006 a
CAS2 - 0.720 0.142 PCP2 - 0.763 1.000 0.388 0.039 a
CAS3 - 0.347 PCP6 - 1.000 0.477 0.021 a
CAS4 - PCP1 - 0.405 0.084
PCP3 - 0.096
PCP5 -
Note: indicates Wilcoxon’s signed rank test result is significant at p-value < .05, indicating that the stage-by-
a

stage comparisons were statistically different

Tables 8.3 and 8.4 present the Wilcoxon’s signed-rank (WSR) test result at p-value < .05. This which

in turn specify the significance of the degree or extent of the stage-by-stage susceptibility to corrupt

practices. This test is performed to shed light on the significance of how a stage is more vulnerable to

the acts of corruption than another stage. The mean results reveal either an activity or a stage to be

critical than the other, and the Wilcoxon is only introduced to inform how significant the magnitude or

the degree of criticalities between two variables or activities being compared.

Therefore, even though an activity within any of the stages of the procurement process can be regarded

as highly vulnerable than another per their respective mean indexes, the outcome does not necessarily

show that the variation between the activities being compared is significant. This is because an activity

with a higher MS when compared to another, may not necessarily have a significant degree of

difference when compared with another variable with a relatively lower mean index. Therefore, the

higher the rate or value of significance that a variable possesses when compared with others, the more

relevant (or in this case ‘critical’) the magnitude of the variable in its mean rank against the others.

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In both contexts, the highly critical activities in their respective stages have been indicated based upon

their corresponding alpha values. Only three activities were statistically rated as being significant

(critical) than at least two other activities within their respective constructs (stages) for developing

countries, namely: CTS3 (contractor selection); CTS2 (tender evaluation); and PCP4 (checking for

proof of delivery). For instance, at the post-contract stage, PCP4 was the only activity that had a higher

significance level than at least two other activities (i.e., PCP6 and PCP5). Other significant activities’

ratings included all the activities at the pre-contract stage except for ‘receipt of tenders’ (PCS6).

Moreover, there were no statistically significant activities at the contract administration stage (CAS).

Lastly, CTS2, CTS3, and CTS 4 were identified to be significant activities at the contract stage.

Overall, 9 activities were significantly critical or more vulnerable when compared with the related

activities within their respective constructs. Analogous to the case of the developing context, all the

activities in stage one (except for the receipt of tenders) were identified to be significant in the

developed context. Also, at the post-contract phase, PCP4, PCP2, and PCP6 were noted as significant

activities. Lastly, the selection of a contractor (CTS3) and issuance of contractual amendments (CAS1)

were the only critical activities in their respective constructs. In all, ten activities were identified to be

significantly vulnerable when compared with the related activities within their respective constructs in

the developed context. This analysis is very important because it singles out the significant (or the more

vulnerable activities) when compared in a stage-by-stage or activity-by-activity manner. These results

may inform necessary industry stakeholders (such as contractors and clients) about the areas to expend

more efforts and resources when attempting to eradicate corrupt practices within the procurement

process.

8.2.2 Corruption Prevalence and Control in Project Procurement

Given prevailing disparities regards corruption control and the effectiveness of anti-corruption

measures within extant literature, Fig. 8.1 presents empirical evidence of respondents’ responses to the

differences that exist between developed and developing countries. Respondents from both

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dichotomous groups were asked to indicate on a scale from 1 to 5, the pervasiveness of corruption in

the modus operandi of infrastructure procurement works, and the effectiveness of the measures

stipulated to combat it. Distinctively, experts from both groups demonstrate or concur with the

propositions concerning the disparities. That is, whereas countries from the developed world have a

relatively low prevalence of corruption and employ effective measures to mitigate corrupt practices

occurring, countries from the developing world experience a high prevalence of corruption and have

fewer systems to expunge or mitigate corruption. It is apparent, therefore, that the high effectiveness of

the measures employed in the developed countries has contributed immensely to the low prevalence of

corrupt practices and vice versa in the case of the developing countries.

Although Fig. 8.1 concerns the subject of corruption in the procurement process; global indexes on the

perception of corruption in countries for these two regions demonstrate similar ratings. For instance,

the corruption perception index (CPI) statistics of Transparency International (2016), reveal that the

leading 20 clean countries internationally are all from the developed economies. This affirms the notion

that developing countries struggle with the development and enforcement of measures to reduce or curb

the high level of corruption experienced. However, even though the results are analogous to the trending

reports on corruption that exhibit disparities between developed and developing countries, this section

of the study is context-specific and entrenched within the domain of construction procurement and

management, unlike the general reports that encapsulate varieties of determinants of driving forces of

public enterprises. More detailed comparative statistics between the two economies and the individual

activities within the respective constructs are discussed in the succeeding sections.

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4
Mean Scores

0
Prevalency Effectiveness
Developed 1.9 4
Developing 3.7 2.4

Figure 8.1: Disparities of corruption prevalence ACMs effectiveness in the procurement process

8.2.3 Prevalent Forms of Corruption throughout the Procurement Process

This section presents the outcome for the third and final objective. Corruption has been inextricably

linked to and embedded within business activities for over several millennia (Chan and Owusu 2017).

The temporal evolution of corruption has led to the developments and manifestations of numerous CFs

in diverse contexts. In the area of procurement and construction management, the most recent study

was conducted by Chan and Owusu (2017). The authors identified 28 different CFs prevalent in

construction management and categorized these CFs into five main constructs viz: bribery acts,

fraudulent acts, collusive acts, extortionary acts, and discriminatory acts. Each of these five constructs

encapsulates different variables. For instance, the CFs classified under extortionary acts were

clientelism or client abuse, coercion, and blackmail (c.f. Chan and Owusu, ibid). These five main

constructs were employed to determine their prevalence in the supply chain of the procurement process.

Fig. 8.2 and 8.3, therefore, represent the prevalence of the CFs throughout the procurement process

in the developed and developing countries, respectively.

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Bribery Acts Collusive Acts Fraudulent Acts Discriminatory Acts Extortionary Acts
Linear (Bribery Acts) Linear (Collusive Acts) Linear (Fraudulent Acts) Linear (Discriminatory Acts) Linear (Extortionary Acts)
5

3
Criticality Index

0
PCS1 PCS2 PCS3 PCS4 PCS5 PCS6 CTS1 CTS2 CTS3 CTS4 CTS5 CAS1 CAS2 CAS3 CAS4 PCP1 PCP2 PCP3 PCP4 PCP5 PCP6

Procurement Process

Figure 8.2: Mean indexes for CFs prevalence within the PP (Developed Countries)

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Bribery Acts Collusive Acts Fraudulent Acts Discriminatory Acts Extortionary Acts
Linear (Bribery Acts) Linear (Collusive Acts) Linear (Fraudulent Acts) Linear (Discriminatory Acts) Linear (Extortionary Acts)
5.00

4.00

3.00
Criticality Index

2.00

1.00

0.00
PCS1 PCS2 PCS3 PCS4 PCS5 PCS6 CTS1 CTS2 CTS3 CTS4 CTS5 CAS1 CAS2 CAS3 CAS4 PCP1 PCP2 PCP3 PCP4 PCP5 PCP6

Procurement Process
Figure 8.3: Mean indexes for CFs prevalence within the PP (Developing Countries).

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Fig. 8.2 and 8.3 present the criticality, or how pervasive the five main categories of corruption forms

are, throughout the procurement process and during the execution of the procurement activities, for

developed and developing countries, respectively. Interestingly, the only activity (PSC1 - definition of

a project’s requirements) that was not statistically different (in terms of the Man-Whitney U test

comparisons between the two economies) demonstrated identical levels of collusive and fraudulent

practices in both contexts. The remaining 20 procurement activities were observed to demonstrate

dissimilar levels of corruption form pervasiveness regarding the contextual comparisons of the two

regions throughout their procurement processes.

The behavior of the corruption forms across the two contexts revealed very distinct results. With

reference to the statistically significant activities identified by the Wilcoxon’s signed-rank test results

(presented in tables 5 and 6), the nine critical activities identified within the context of developing

countries revealed that bribery acts, collusive practices and discriminatory acts were pervasive within

these activities as they ranked highest in at least two (i.e., PCS5=discriminatory; PCS4=bribery;

PCS3=discriminatory; PCS2=collusive; PCS1=collusive; CTS4=bribery; CTS3=bribery;

CTS2=bribery; PCP4=collusive). For instance, PCS4, CTS4, CTS3, CTS2 were all identified to be

plagued with bribery acts, whereas PCS5 and PCS3 also had discriminatory practices and also, PCS2,

PCS1, and PCP4 were identified to be mostly plagued with collusive practices.

In contrast, the results for the developed countries revealed that out of the ten critical activities

identified, six experienced collusive practices while the remaining four were plagued with bribery acts.

When all 19 significant activities were considered, the three most pervasive corruption forms were

identified as collusive practices, bribery acts, and discriminatory acts. Furthermore, of the four main

stages in each context, these three critical corruption forms were predominantly identified at the pre-

contract and contract stages in the case of developing countries and the pre-contract stage and post-

contract phase in the case of the developed countries. The pre-contract stage is, therefore, the only

common stage or construct across the two contexts that are plagued with corruption forms. The contract

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stage is identified to be more critical or skewed towards the developing countries, and the post-contract

phase tends to be critically susceptible in the developed countries.

8.2.4 Discussions

The procurement process is regarded as vulnerable to corrupt practices (c.f. Tabish and Jha 2011; Deng

et al. 2014; Le et al. 2014). However, this varies across diverse norms and jurisdictions (Jain, 2001).

Previous studies reported upon critical examples of corrupt practices that occur during the procurement

of infrastructure works. For instance, Tabish and Jha (2011) examined the irregularities of Indian’s

public procurement sector and identified over 60 factors that render the entire procurement process of

India susceptible to the acts and effects of corrupt practices. Similar studies were conducted in Italy,

China, Indonesia, and Ghana by Locatelli et al. (2017), Le et al. (2014b), Tidey (2013), and Osei-Tutu

et al. (2010) respectively. In almost all the cases, activities within the contract stage (such as evaluation

of tenders and contractor selection) were besieged with corrupt practices. Since this scope has not been

critically explored in different contexts, the manifestations of corrupt practices at different sections of

the procurement process in different countries are not readily available in literature.

It must be emphasized that even though developed countries record low mean values regarding the

criticality, this finding should not be interpreted as meaning corrupt practices were not being

experienced. For example, TI’s (2017) countries rankings show that all countries experience some form

of corruption. Moreover, even though the contract stage in developing countries was identified to be

the most critical construct, there were some individual variables within each construct or stage

identified to be susceptible to corrupt practices. These include CT1, CT2, CT3, PCS4, PCS5, CAS4,

PCP3, and PCP4. These activities within their respective constructs can be considered as the most

critical areas to be considered in dealing with corrupt practices throughout the procurement process in

developing countries. Hence, participating experts concur that if these activities within their respective

stages are brought to check, corruption practices within the procurement process of most developing

countries can be controlled in the short run and extirpated in the long run.

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Even though all the activities recognized under the pre-contract stage, are susceptible to corrupt

practices or render the entire process to the risks of the consequences of corruption, the leading

activities raised by PCS4 and PCS5 are raised by the experts as the most critical area of concern. Sohail

and Cavil (2007) reported the presence of some forms of corruption during this stage (i.e., pre-contract

stage) in projects across diverse contexts. The authors (ibid) indicated the possibility of corruption to

initiate the selection of profligate or uneconomical projects only to create some room to exploit

resources allocated for the project. Examples such as political patronage, (which is captured under

collusive practices in the study of Owusu et al. (2017) and financial kickbacks (identified under the

bribery construct) are often identified. The typical CFs of the examples mentioned can be traced in Fig.

8.2 and 8.3, where the most dominating and critical forms of corrupt practices within the pre-contract

stage are bribery and collusive acts. The decision making of high-level government officials and

politicians who become seduced by bribery provides a typical example of how profligate projects

manifest within contemporary procurement practice.

Moreover, one typical case can be traced to the highlands water project in Lesotho, South Africa.

According to Wells (2015), corrupt practices were discovered when over twelve international

companies and consortiums were found to have been paid bribes to the project's Chief Executive, who

fraudulently awarded some of the contracts. Such acts are inevitable at the pre-contract stage where

consenting parties or officials may communicate with one another or come to a common ground of

distorting the process to benefit their selfish desires (Owusu et al. 2017). Other examples reported by

Stansbury and Stansbury (2008) at the pre-contract stage include price-fixing by a cartel of contractors,

design manipulation, and disclosure of tender information to a specific bidder.

The contract stage is the most susceptible to corruption within developing countries and the 3rd out of

4 stages within developed countries; in descending order, the noted critical stages happened to be

contractor selection (CT3), tender evaluation (CT2), and contract award (CT4). However, these three

activities within the CTS construct are interrelated since evaluating submitted tenders leads to the

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selection of contract award to either a corrupt or a genuine bidder. Thus, once the earliest activity is

corrupt, the probability that the succeeding activities would undergo similar distortions, increases.

According to Tabish and Jha (2007), some of the noted corrupt practices at this stage include bid

suppression, where one or more bidders concur to either cease from bidding or withdraw tenders

previously submitted. Bidders who retract their bids do so to push an agreed-upon bidder to win (Tabish

and Jha 2007). This is similar to price-fixing reported by Stansbury and Stansbury (2008) where a group

of bidders competing for a similar project contrive the most competitive (winning) tender while other

tenderers submit overly-estimated bids. Since their intent is to share the market among themselves, they

run this system in turn such that every bidder within the group wins a project. This form of corrupt

practice is analogous to 'dividing the pie' as well as 'complementary bidding' (c.f. Tabish and Jha, 2007).

Other forms identified and reported include low balling (which is termed as deliberate under-

estimation), front companies, facilitation payment, and solicitation either by contractors or project

consultants.

Respondents from developing countries indicated that the administration of the project's interim or

progress payment was the most susceptible activity within the contract administration stage. This may

not be unsurprising as it is closely linked to project execution. Thus, the required interim reports (e.g.,

specification valuations and financial claims) are susceptible to corrupt practices. Noted examples of

corrupt practices include inflated claims, submission of erroneous or misleading interim certificates,

concealing defects, and presenting claims for defected works as completed works.

Lastly, finalizing financial audits (PCP3) and verification of completed works (PCP4) were identified

to be the most susceptible activities at the post-contract stage. Tabish and Jha (2007) and Shan et al.

(2017) indicated that kickbacks are often offered to persuade inspectors (in this case, auditors) to

overlook parts of the contract requirements that were unexecuted and conceal defects discovered. Thus,

bribes and other facilitation payments are paid to related project officials to approve unduly executed

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tasks or specify that works executed were completed in accordance with stipulated specifications. Thus,

at this stage, it can be inferred or deduced that bribery acts and fraudulent practices were widespread at

this stage. These reflections are depicted in both Fig. 8.2 and 8.3 as bribery and fraudulent acts are

indicated by the respondents from both contexts to be the dominant forms within this construct.

8.2.5 Section Concluding Remarks

At the outset, this section of the study sought to investigate three focused objectives to answer how

susceptible the stages involved in project procurement are to the incidence of corrupt practices and also

determine the critical forms prevalent at each stage in the context of the developed and the developing

countries. Thus, this research presented the empirical review of international experts’ opinions on the

vulnerability of the procurement stages to corrupt practices and the pervasiveness of CFs in the supply

chain of the procurement process. Contributing respondents expressed their opinions regarding the

prevalence of corruption and the effectiveness of anti-corruption measures guiding the procurement

works of their respective countries. Whereas the respondents from the developing world indicated a

high prevalence of corrupt practices coupled with the low effectiveness of ACMs, respondents from

the developed economies indicated the very opposite, that is, low prevalence and high effectiveness of

ACMs.

Regarding the individual ratings for developed countries, the mean values for their susceptibility levels

were relatively lower compared to that of developing countries. However, all the 21 activities within

the four stages demonstrated significant levels in their respective ratings. Moreover, the contract

administration stage had the highest level of vulnerability, and the top-rated susceptible activities were

identified to be the phase (where contract amendments are issued) and at the very beginning of the

process (where project infrastructure requirements are defined). In examining the prevalent CFs at the

different stages of the procurement process, collusive and bribery acts were identified to be the

dominant pervasive CFs throughout the procurement process even though fraudulent acts were also

recorded by some of the respondents. Unlike the case (results) of developed countries, the developing

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countries demonstrated a statistically different set of opinions regarding the issue of corruption in their

procurement process.

First, just as the respondents indicated a high prevalence of corruption and low effectiveness of ACMs,

the vulnerability levels of the stages and activities of the procurement process was relatively higher.

Moreover, dissimilar to the case of developed countries, the CTS (contract stage) was identified to be

the leading vulnerable stage to corruption in the developing economies, with the construct containing

the first three vulnerable activities among the overall 21 stages. They are the contractor selection stage,

tender evaluation, and the contract awarding stage. Regarding the prevalence of the CFs at the different

stages of the procurement process, three different forms (i.e., collusive, bribery and extortionary

practices) dominated the first half of the process whereas collusion, bribery, and fraudulent acts were

identified to be pressing at the last half of the process. PCP1, through to PCP6, recorded high levels of

collusive practices. Lastly, the MWU test results also revealed the statistically significant difference

between the paired activities of the procurement process. Twenty paired activities of the developing

and developed countries were identified to be different out of the 21, which indicates a very high

significant difference.

With the realization of these susceptibility indexes revealed at the different levels of the procurement

process (which was the main question the study sought to answer), the development of stringent and

practical anti-corruption tools can be developed. Thus, the findings are beneficial not only to deepen

academic understanding of the dynamics of corruption in procurement works but also beneficial to

industry practitioners, policymakers, and anti-corruption institutions. Such knowledge could be used to

develop specific and pragmatic corruption mitigation measures in the supply-chain of procurement of

infrastructure works.

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8.3 Anti-Corruption Measures

In the quest of giving a distinct definition of corruption, several works of literature on the subject matter

of corruption from criminology, sociology, organizational behavior, law, and politics as well as

construction management share a common consensus that the subject remains a decidedly disputed

concept. To this present time, there is still an absence of resolutely grounded theories of corruption as

well as a limited shared understanding (Moore 2009; Kleinig and Heffernan 2004; Williams, 2000).

However, the general public to whom this social menace affects, possess very little knowledge on the

different constructs of the topic (such as different forms of corruption, causes, and anti-corruption

measures), the nature and behavioral dynamics of corruption in different regions and different contexts

and so on. However, even though the subject of corruption tends to be extremely broad, this section of

the study lends itself towards the context of construction project management.

Several studies have been conducted on this subject with the discussion of associated subheadings under

the main topic and with the identification and discoveries of several causal factors influencing the

nature of corruption in different construction public sectors and the management of different

construction projects. The subject of corruption has been an integral causal factor of the derailment to

achieving the contributing factors of the eternal triangle in construction project management (i.e.,

quality, time, and cost) (Shan et al. 2017; Le et al. 2014a). The destructive impact of corruption on

construction projects and associated sectors include loss of human lives, short lifespan of buildings, the

setback of economic growth and development, misappropriation of public funds among numerous

impacts. These impacts have been discussed in several world reports, newspapers, and other scholarly

works. They continue to thrive not only because of the secret or persistent thriving nature of corrupt

practices but also to an extent attributed to the ineffectiveness of existing ACM stipulated to check the

menace of corrupt practices. The ineffectiveness also erupts as a result of the absence of reviewing the

potency of already existing ACM in CPM since a consistent review can help in eliminating the

loopholes or risks associated with reviewed measures (Owusu et al. 2017; Shan et al. 2015). Measuring

the effectiveness of ACM in CPM, therefore, contributes to the development of new or the enhancement

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of existing ACM towards the creation of a more holistic approach in dealing with corruption in the

modus operandi of CPM.

Even though some studies have been conducted on the subject of corruption in CPM, the empirical

assessment of the effectiveness of ACM is relatively limited. This section of Chapter 8, therefore,

examines the effectiveness of the prevailing ACM in CPM. In achieving the stipulated aim, the

following objectives are set: (1) examine the level of effectiveness of each of the identified ACM in the

contexts of the developed and the developing world and (2) determine the statistical differences in the

level of effectiveness between the two mentioned contexts. This section of the study contributes to the

strategic formulation of ACM in CPM, add to the body of knowledge on corruption-related topics in

CPM coupled with the contribution of deepened understanding on the subject matter (i.e., anti-

corruption measures in CPM). It serves as one of the leading references to the identification of the

effectiveness of ACM in CPM.

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Table 8.5: Descriptive Statistics of the Effectiveness of Anti-Corruption Measures

Code Anti-Corruption Measures Overall Developed Regions Developing Regions
Mean SD N-value Rank SWT Mean SD Rank N-value Mean SD Rank N-value
AC1 Transparency mechanism 3.77 1.16 0.65* 4 0.000 4.03 0.95 9 0.65* 3.50 1.30 3 0.65*
AC2 Raising awareness 3.63 1.15 0.50* 12 0.000 4.09 0.84 7 0.73* 3.16 1.25 19 0.35
AC3 Contract monitoring 3.91 1.16 0.79* 2 0.000 4.18 0.81 3 0.85* 3.61 1.39 2 0.74*
AC4 Good Leadership 3.62 1.14 0.49 15 0.000 3.97 0.95 11 0.58* 3.25 1.22 15 0.43
AC5 Education 3.69 1.10 0.56* 7 0.000 4.03 0.95 9 0.65* 3.34 1.15 12 0.51*
AC6 Contractual compliance 3.68 1.21 0.55* 8 0.000 4.15 0.91 4 0.81* 3.19 1.31 18 0.38
AC7 Whistle-blowing mechanism 3.68 1.05 0.55* 8 0.000 3.94 0.90 12 0.54* 3.41 1.13 8 0.57*
AC8 Professional associations 3.48 1.08 0.34 19 0.000 3.52 1.03 20 0.00 3.44 1.13 6 0.59*
AC9 Financial disclosure / Disclosure 3.65 1.10 0.52* 11 0.000 3.88 0.96 13 0.46 3.41 1.19 8 0.57*
AC10 Rigorous technical auditing system 4.11 1.06 1.00* 1 0.000 4.30 0.88 1 1.00* 3.91 1.20 1 1.00*
AC11 Comprehensive rules and regulations 3.66 1.08 0.53* 10 0.000 4.06 0.97 8 0.69* 3.25 1.05 15 0.43
AC12 Training and development initiatives 3.63 0.99 0.50* 12 0.000 3.82 0.88 17 0.38 3.44 1.08 6 0.59*
AC13 Ethical code 3.15 1.20 0.00 20 0.000 3.55 1.18 19 0.04 2.75 1.11 20 0.00
AC14 Debarment/ Promoting fair debarment 3.63 1.07 0.50* 12 0.000 3.79 0.82 17 0.35 3.47 1.27 4 0.62*
procedures.
AC15 Procedural compliance 3.59 0.92 0.46 17 0.000 3.88 0.89 13 0.46 3.28 0.85 13 0.46
AC16 Harsh punishment or penalty 3.80 1.06 0.68* 3 0.000 4.12 0.78 5 0.77* 3.47 1.22 4 0.62*
AC17 Access to information 3.62 1.20 0.49 15 0.000 3.85 0.91 15 0.42 3.38 1.41 10 0.54*
AC18 Compliance to fairness and transparent 3.75 1.12 0.63* 5 0.000 4.12 0.89 5 0.77* 3.38 1.21 10 0.54*
procedures
AC19 Rigorous supervision among others 3.75 1.02 0.63* 5 0.000 4.21 0.69 2 0.88* 3.28 1.09 13 0.46
AC20 Increase in accountability 3.55 1.13 0.42 18 0.000 3.85 0.87 15 0.42 3.25 1.29 15 0.43
Note: Cronbach’s 0.935 (overall); 0.907 (Developed); 0.931 (Developing); N = 65; Critical Chi-Square value (at p value of 0.05) = 30.14; Actual Chi-Square value =
68.769; Asymp. Sig. = 0.000 (for overalls; Developed and Developing regions); Df = 19; SWT represents Shapiro-Wilk test; SWT results indicates data were statistically
significantly; Normalization (N) value = (actual mean-minimum mean)/(maximum mean-minimum mean)

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8.3.1 Results and Discussions

17 out of the 20 measures were identified to be less effective. Thus, supporting the views or propositions

that reveals the widespread of corrupt practices in the developing world and the ineffectiveness of

ACMs. In descending order, rigorous technical auditing system [AC10] was identified by the experts

from the developing world to be the leading or most effective ACM in the context of the developing

world. In order, words, corruption in CPM have been checked to an extent due to periodic audits of

project’s interim reports and other contractual documents regarding a project. With a mean score of

3.91, the experts share a common view that even though corruption in the CPM of most developing

regions may be prevalent in public construction and procurement sectors. One of the reasons why the

regions within the context may be making some little or good efforts to an extent towards the

expurgation of corrupt acts with their accompanying detrimental effects can be attributed to the

stringent auditing measures adopted in certain jurisdictions of the developing contexts.

Regular audits either on projects or public sectors may include financial audits to ensure that interim

payments made correspond to the amount specified in a contract document. Others include internal or

operational audits to appraise respective entities responsible for executing a project, forensic audits,

compliance audits, among others (Hussain and Hadi 2018; Tan and Libby 1997; Mills 1987). Aside

from auditing the process and activities involved in CPM to mitigate the risk of corruption, the act of

auditing also contributes to the effectiveness of other stipulated ACMs such as an increase in

accountability and transparency mechanism (Owusu et al. 2017). This variable was identified in the

study of Owusu et al. (2017) as one of the most discussed probing measures. It has been adopted by

several institutions such as the Independent Commission Against Corruption (ICAC) of Hong Kong

(Wai 2006), Corrupt Practices Investigation Bureau (CPIB) of Singapore and other thriving

investigative bodies to help reveal the secret corrupt activities prevalent in public sector projects.

Comparatively, this ACM is identified to be highly significant than over 16 other ACMs, as indicated

by Wilcoxon’s signed-rank test result in Table 8.5.

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The second most effective construct identified in the developed context was contract monitoring [AC3].

Contract monitoring can be described as the process of evaluating contractor’s performance on the

premise of quantifiable deliverables as well as verifying contractor’s compliance per the requirements

and conditions stipulated in the contract guiding the execution of a project (Krishnan 2009; Owusu et

al. 2018; Valdes-Vasquez and Klotz 2012). Contract monitoring is somewhat analogous to contract

auditing. However, whereas both are aimed at identifying potential risks or corrupt practices to provide

mitigating measures, contract monitoring enhances compliable contractual performance right at the

point of signing a contract throughout the contract period to contract close-out whereas auditing is

performed at given intervals which may not necessarily commence immediately after awarding and

signing of the contract. Moreover, contractual monitoring agencies may be different from audit

institutions or parties.

This variable was as well captured by Owusu et al. (2018) as one of the most discussed ACM under the

construct of probing measures. It was, however, regarded by the developing world experts through

shared views to be the second most effective or somewhat successful ACM in CPM. Transparency

mechanism [AC1] was the third and last most effective ACM identified in the context of the developing

world’s CPM. In simple terms, transparency mechanism can be described as the all-inclusive measures

such as frequent stringent audits, financial disclosures, contract monitoring, etc. aimed at creating an

open and accountable environment that is free from any association or identification of corrupt practices

or the risks or outcomes associated with corruption. In accessing this construct in some specific

developing regions, Shan et al. (2015) examined the potency of some anti-corruption strategies aimed

at enhancing transparency and combating corruption in the Chinese public construction sector. Among

the constructs that were assessed included stipulated rules and regulations and good leadership. Tabish

and Jha (2008) and Ameyaw et al. (2017) also examined some ACMs in India and Ghana specifically

to explore the nature of corruption in these regions as well as suggest recommendatory measures

towards corruption elimination and transparency enhancement. Transparency mechanism was however,

identified by Owusu et al. (2017) as the most discussed managerial ACM in CPM studies and was as

well regarded as one of the most important and effective ACM in the context of the developing world.

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In summary, the three most effective ACMs in the context of the developing world stems from only

two out of the six constructs developed in the study of Owusu et al. (2018), namely probing and

managerial measures. That is, whereas, rigorous technical auditing system and contract monitoring are

categorized under probing measures, transparency mechanism emanate from managerial measures.

Apart from these top three variables from identified under the two constructs, the remaining 17

variables, coupled with the other four constructs, were all regarded to be less effective in the developing

world context.

This is further explicated by the Wilcoxon’s signed-rank test result in Table 8.6. It can, therefore, be

argued that the high prevalence of corruption in most developing regions are not only attributed to the

evolution of the diverse forms of corrupt practices coupled with their associated causal measures and

risk indicators but also the ineffectiveness of the majority of the stipulated ACM in existence. Bowen

et al. (2012) and Ameyaw et al. (2017) specifically reported on most of the constraining factors that

suppress the effectiveness of these ACM. Among the many barriers identified in the context of the

developing world included political and structural constraints, psychological factors such as fear of

rejection, losing job, being marginalized as well as other social and organizational obstructions. Others

include organizational, social and political barriers. Therefore, devising new strategies to augment or

enhance the effectiveness of existing ACM should as well consider appropriate measures needed to

check the obstructing measures that tend to thwart or suppress the potency of the existing ACM.

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Table 8.6: Pairwise Comparisons of the Effectiveness of ACM in the developing context
Code AC10 AC3 AC1 AC16 AC14 AC12 AC8 AC7 AC9 AC18 AC17 AC5 AC15 AC19 AC11 AC4 AC20 AC6 AC2 AC13
a a a a a a a a a a a a a a
AC10 * 0.460 0.021 0.027 0.020 0.024 0.041 0.012 0.061 0.097 0.087 0.034 0.014 0.032 0.003 0.022 0.042 0.021 0.008 0.000a
AC3 * 0.578 0.576 0.283 0.446 0.302 0.183 0.452 0.159 0.171 0.408 0.194 0.083 0.208 0.032a 0.043a 0.005a 0.007a 0.002a
AC1 * 0.821 0.987 0.645 0.907 0.834 0.875 0.569 0.461 0.505 0.346 0.385 0.115 0.203 0.323 0.189 0.104 0.002a
AC16 * 0.910 0.911 0.900 0.828 0.617 0.590 0.504 0.520 0.388 0.331 0.276 0.199 0.307 0.233 0.170 0.011a
AC14 * 0.860 0.971 0.805 0.646 0.942 0.864 0.508 0.211 0.522 0.247 0.715 0.611 0.569 0.402 0.022a
AC12 * 0.974 0.905 0.861 0.942 0.878 0.590 0.461 0.641 0.278 0.555 0.489 0.312 0.246 0.002a
AC8 * 0.884 0.672 0.850 0.924 0.537 0.314 0.603 0.344 0.870 0.680 0.578 0.460 0.016a
AC7 * 0.939 0.680 0.934 0.781 0.480 0.683 0.430 0.927 0.881 0.701 0.660 0.024a
AC9 * 0.634 0.771 0.823 0.516 0.537 0.523 0.378 0.342 0.161 0.149 0.005a
AC18 * 1.000 0.895 0.516 0.642 0.633 0.428 0.659 0.405 0.242 0.013a
AC17 * 0.918 0.663 0.648 0.907 0.538 0.526 0.293 0.182 0.011a
AC5 * 0.591 0.965 0.733 0.790 0.726 0.578 0.462 0.007a
AC15 * 0.953 0.857 0.869 0.918 0.704 0.594 0.043a
AC19 * 0.789 0.833 0.909 0.636 0.462 0.039a
AC11 * 0.875 0.930 0.778 0.619 0.030a
AC4 * 0.905 0.817 0.203 0.048a
AC20 * 0.642 0.564 0.009a
AC6 * 0.873 0.059
AC2 * 0.035a
AC13 *
Note: a indicates Wilcoxon’s signed rank test result is significant at p-value < .05, indicating that the stage-by-stage comparisons were statistically different

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Unlike the ratings of the developed regions, the respondents of the developed world indicated the

relative importance of each of the identified ACM per their degree of effectiveness. All the ACMs were

mutually concurred by the corresponding experts to be effective with the various MS ranging from 3.5-

4.5. The comparative statistical significance of some of the top ACM in the context of the developed

world such as [AC10], [AC19], and [AC6] are presented by the Wilcoxon’s signed rank test result in

Table 8.7. In descending order of importance, the top three most effective ACM in this context were

identified to be rigorous technical auditing system [AC10], rigorous supervision [AC19], and contract

monitoring [AC3].

Analogous to the findings of the developing world, two out of the top three most effective ACM were

identified in this context as well. From the deductions of the experts from both contexts, even though

there are numerous ACMs ranging from proactive measures to reactive measures stipulated to curb the

menace of corruption in CPM, the list can never be complete without the inclusion of stringent technical

auditing and contract monitoring which is inclusive of effective project supervision. Given the

explications made in the previous section concerning the two identical ACM among the top three, a

more detailed consideration will be conducted on rigorous supervision, which coins the other two

ACMs together. The term ‘supervise’ stems from the amalgamation of the medieval Latin words ‘super’

which means over and ‘videre,’ meaning, to see (Merriam-Webster 2018). In short, the word is

simplified to mean to oversee or manage a project. A project can never be successful (i.e., achieve the

full benefit of the eternal triangle, which includes cost, time, and quality) without the appropriate

stringent project supervision.

Moreover, even though stringent project supervision contributes to checking the widespread of

corruption in CPM, Chan et al. (2004) identified this variable to be one of the topmost project

management actions towards the realization of project’s success. Owusu et al. (2017) also identified

this managerial task to be one of the most discussed ACM that has a perfect indirect correlation with

corruption. That is, an enhancement in project supervision decreases the tendencies or opportunities for

corruption to occur. As discussed in the next section, one of the major statistical connotations that

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distinguish the developed regions from the developing towards the elimination of corruption in the

mentioned contexts lies in the supervision of major public infrastructural projects. There are several

studies that have reported on different kinds of project failure because of poor project supervision. In

the context of India, China, Ghana, and Zambia among several others, respective studies which include

Tabish and Jha (2011) Le et al. (2014), Ameyaw et al. (2017) and Sichombo et al. (2009) have directly

or indirectly attributed the thriving of most corrupt causal factors with associated risk indicators to the

absence of effective and stringent project supervision. The difference in enforcing stringent project

supervision coupled with other important ACM contribute to the wide difference in corruption

prevalence and control between the developed and the developing regions. The succeeding section after

Table 8.7 indicates other significant disparities regarding the effectiveness of the identified ACM

between the developed and developing regions.

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Table 8.7: Pairwise Comparisons of the Effectiveness of ACM in the developed context
Code AC10 AC19 AC3 AC6 AC16 AC18 AC2 AC11 AC5 AC1 AC4 AC7 AC15 AC9 AC20 AC17 AC14 AC12 AC13 AC8
a a a a a a a
AC10 * 0.552 0.475 0.166 0.147 0.157 0.097 0.159 0.128 0.103 0.144 0.077 0.022 0.003 0.015 0.003 0.008 0.009 0.003 0.001a
AC19 * 0.890 0.635 0.548 0.518 0.594 0.500 0.511 0.319 0.256 0.124 0.019a 0.045a 0.072 0.046a 0.016a 0.096 0.009a 0.002a
AC3 * 0.723 0.785 0.512 0.461 0.475 0.320 0.197 0.197 0.219 0.117 0.142 0.052 0.092 0.031a 0.035a 0.003a 0.006a
AC6 * 0.523 0.782 0.600 0.640 0.575 0.554 0.446 0.242 0.020 0.039 0.084 0.046a 0.023a 0.070 0.011a 0.002a
AC16 * 1.000 1.000 0.646 0.695 0.688 0.376 0.198 0.096 0.278 0.109 0.215 0.068 0.210 0.007a 0.012a
AC18 * 0.957 0.751 0.906 0.670 0.540 0.299 0.083 0.135 0.097 0.109 0.032a 0.186 0.025a 0.016a
AC2 * 0.906 0.812 0.683 0.520 0.382 0.244 0.366 0.160 0.292 0.072 0.020a 0.004a 0.008a
AC11 * 0.764 0.822 0.438 0.456 0.413 0.299 0.090 0.182 0.145 0.142 0.006a 0.022a
AC5 * 0.893 0.660 0.616 0.307 0.543 0.163 0.431 0.189 0.193 0.018a 0.007a
AC1 * 0.698 0.773 0.441 0.408 0.265 0.265 0.159 0.265 0.019a 0.067
AC4 * 0.883 0.540 0.623 0.499 0.479 0.268 0.454 0.076 0.009a
AC7 * 0.663 0.667 0.660 0.575 0.320 0.557 0.122 0.028a
AC15 * 0.890 0.861 0.765 0.439 0.986 0.213 0.054
AC9 * 0.868 0.782 0.651 0.752 0.162 0.084
AC20 * 1.000 0.653 0.864 0.115 0.071
AC17 * 0.804 0.600 0.097 0.068
AC14 * 0.723 0.263 0.099
AC12 * 0.118 0.167
AC13 * 0.873
AC8 *
Note: a indicates Wilcoxon’s signed rank test result is significant at p-value < .05, indicating that the stage-by-stage comparisons were statistically different

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8.3.2 Significant disparities as indicated by the MWU test results

The MWU test results indicate that the statistical distinctiveness regarding the effectiveness of ACMs

that has led to the low level of the pervasive nature of corrupt activities in the developed world.

Moreover, the success in the fight against corruption that differentiates the developed regions from the

developing world can be attributed to the significant variables identified by the MWU test statistics.

The contextual disparities of the identical ACMs were discussed based on their respective constructs.

They are promotional measures, compliance, probing, organizational, reactive, and managerial

measures. The MWU test revealed that the overall variables under this construct indicated strong

statistical disparities between the identical variables in both contexts. The variables captured under the

compliance section included Compliance with fairness and transparent procedures [AC18], Contractual

compliance [AC6], and Procedural compliance [AC15].

Even though there were clear dissimilarities in these variables concerning their levels of effectiveness,

the results do not necessarily show that there is zero compliance in the case of the developing world

neither do they depict full compliance in the context of the developed world. The concept of the

different types or levels of compliance is presented in the study of Worthy et al. (2017). In descending

order, the five levels of compliance explicated in the study of Worthy et al. (2017) are concordance,

full compliance, partial compliance, lesser compliance, and non-compliance. It is, therefore, possible

that the differences in the compliance levels presented by the respondents from the two contexts may

range from the different levels indicated.

However, it is obvious per the MS and MWU test results that compliance with anti-corruption

stipulations in the developed world CPM far outweighs that of the developed. It may, therefore, be

regarded as an area of concern for the developing regions towards the enhancement and potency of the

existing and new to be developed ACM. Under Probing and supervisory measures, the identical

variables of both Whistle-blowing mechanism [AC7] and Rigorous supervision [AC19] [were

identified to be statistically different on the contextual levels. A number of factors have been identified

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in different reports as hampering measures that obstruct the effective reporting or whistleblowing in

the context of the developing world. On the other hand, corruption has been checked to an extent in the

developed regions partly due to the systematic and effective systems of reporting corrupt cases and

checking or providing strategic measures to obliterate the obstructing measure that affect the effective

application of ACM in the developed regions (Owusu et al. 2018).

Table 8.8: Mann-Whitney U Test Statisticsa indicating significant disparities of variables

C AC1 AC2 AC3 AC4 AC5 AC6 AC7 AC8 AC9 AC10
U 410.000 293.000 430.000 346.000 347.000 299.000 383.500 513.000 401.500 437.500
W 938.000 821.000 958.000 874.000 875.000 827.000 911.500 1041.000 929.500 965.500
Z -1.609 -3.227 -1.371 -2.507 -2.513 -3.121 -1.970 -.205 -1.744 -1.273
P .108 .001a .170 .012a .012a .002a .049a .838 .081 .203

C AC11 AC12 AC13 AC14 AC15 AC16 AC17 AC18 AC19 AC20
U 293.000 419.500 316.000 478.000 344.500 365.500 448.500 337.000 270.000 404.500
W 821.000 947.500 844.000 1006.000 872.500 893.500 976.500 865.000 798.000 932.500
Z -3.223 -1.515 -2.860 -.688 -2.548 -2.242 -1.087 -2.625 -3.588 -1.706
P .001a .130 .004a .492 .011a .025a .277 .009a .000a .088
Note: a Grouping Variable: Developed and Developing Regions; * represents C = Codes of individual ACM; U =
Mann-Whitney U Test Statistics; W = Wilcoxon W; Z – Z values; P = Significance level (Asymp. Sig.)

Promotional measures such as raising awareness [AC2], holding seminars, and educating the general

public [AC5] or specific class of people on the subject of corruption may not be very much enforced as

compared to the others. However, it is encouraging in the developed regions as compared to developing.

Aside from the statistical evidence fetched from the views of the respondents, there are a number of

real-life scenarios. Some examples include the Global Anticorruption Education and Training Project

(Smith 2009); the Construction Sector Transparency Initiative to promote transparency in international

construction projects (World Federation of Engineering Organizations (WFEO) 2016; Krishnan 2009),

Construction Industry Ethics and Compliance Initiative with the aim to promote and advance of ethical

conduct and compliance in the construction industry (WFEO 2016). These are just a few of several

initiatives in the developed world instigated to promote and raise awareness of how to create an ethical

atmosphere in the construction industry. It also to thwart and annihilate corrupt practices with its

detrimental effects not only on the construction and engineering sectors but also on projects, resources

and the very lives that make use of the projects. Contrastingly, such initiative may exist on a broader

scale but not specific to the construction and engineering sectors nor towards the management of

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construction projects in the developed world. The disparities noted in promotional measures such as

training initiatives and others reveal another area of focus that differentiates the success in the fight

against corruption in the developed regions as compared to the developing. The regulatory measures

identified in this section of the study were Ethical code [AC13] and comprehensive rules and

regulations [AC11].

The MWU test also revealed significant statistical disparities between the developed and developing

contexts concerning these measures. [AC13] which was identified by Owusu et al. (2017) as one of the

most discussed ACMs, was relatively ranked lower in both contexts but identified to be significant in

the developed context and the least effective ACM in the developing world. Per the results and

deductions of the MUW test, it constitutes one of the primary factors that differentiate the two contexts

from one another. Analogous to the reactive and compliance measures, both the MS and the MUW tests

show that the effectiveness and the compliance to some stipulated ACMs contribute enormously to the

success in the fight against corruption in the developed regions that differentiates them from the

developing world. They include ethical and professional standards, rules, and regulations that govern

the contractual demands of a project and the behavior of parties and professionals concerned with a

project or in a given context. Lastly, the MUW test revealed one identical variable that demonstrated a

statistically significant difference concerning the level of criticality measured between the two contexts.

The identified variable is harsh punishment or penalty [AC16]. It was revealed that not only do the

developed regions have effective reporting systems as well as measures to expunge the barriers that

hinder the effective application of ACM but also have a stricter measure to make sure that the stipulated

ACMs are adhered to. Stricter or strong regulatory system represents a sturdy indicator for a serene and

corruption-free environment. On the other hand, a jurisdiction where the regulatory system is flawed

with accompanying and the necessary reactive measures are not meted out in the event of a corrupt

practice, that particular jurisdiction is likely to experience high-level corruption. This is common in the

case of the developing regions as corrupt officials (government officials and senior management of

project parties) easily get away with high levels of corruption (Ameyaw et al. 2017; Le et al. 2014;

Tabish and Jha 2011; Sichombo et al. 2009). Lastly, all the identified ACM that demonstrated statistical

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differences in both contexts can be argued to have resulted partly from differences associated with

managerial measures such as Good Leadership [AC4]. Whereas good leadership seeks to achieve the

objectives concerned with either a project or its organization, corrupt leadership in this context often

looks out for any possible opportunity to misappropriate funds or resources, and where there is no

opportunity, they create one (Owusu et al. 2017). The summary of the MWU test results showing the

statistical disparities between the identical constructs of the two regions is presented in Table 8.8.

Moreover, the mean disparities highlighting the effectiveness of the ACM with their associated

constructs in both contexts are presented in Fig. 8.4.

5
Developed Developing
4

0
E-RGM E-MAM E-PBM E-COM E-PRS E-REM

Figure 8.4: Graphical illustration of MS disparities of ACM constructs

After determining the conditions that depict that statistical differences between the two contexts, the

results as well indicated that the ACMs that were identified to be effective in the developing world

were statistically indifferent from the identical variables in the developed context. Therefore, the null

hypotheses for the ACM, which include transparency mechanism [AC1], rigorous technical auditing

system [AC10], and contract monitoring [AC3] were accepted since per the MWU test results the

effectiveness of these ACMs was analogous to the case of the developed regions. The explicit

distinctiveness in corruption pervasiveness and control that have been reported on longitudinal bases

can be attributed to the difference in the identical variables measuring the effectiveness of ACM. It can,

therefore, be postulated that giving critical attention to the areas of differences to level up the efforts of

the developing regions to that of the developed will contribute enormously to the effectiveness of the

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identified ACM in the developing world. Thus, aiding to the fight against corrupt practices in CPM and

enhancing corruption-free atmosphere, benefiting the practice.

8.4 An empirical assessment of the Barriers

8.4.1 Introduction

This section of the chapter examines the critical barriers that obstruct the full potency and the intended

effectiveness of anti-corruption measures enforced to mitigate the pervasiveness of corrupt practices in

project procurement and execution. To achieve this aim, a comprehensive review of literature was

conducted and resulted in the identification of 17 critical barriers. A questionnaire survey was

conducted with 65 experts from around the world involved in infrastructure project procurement and

management using the purposive sampling technique. The analysis was conducted on a contextual

comparative basis. Thus, comparing the views of experts from the developed countries against the

experts from the developing countries. The leading barriers identified by the respondents from the

developing context were; the absence of political will by government officers and statutory professional

councils to fight corruption and personal attitudes, which include the lack of will to become involved

in fighting corruption.

The respondents from the developed world revealed that non-familiarity with ethical codes, the fear of

being caught reporting, and personal attitude was the leading barriers. The Mann-Whitney U test was

employed to analyze the statistical difference regarding the barriers’ criticality between the two

contexts. Analogous to the other sections, this section of the study contributes to a deepened

understanding of corruption by examining the criticalities of barriers to the effectiveness of anti-

corruption measures, which have not received the needed attention in the past years.

8.4.2 Data Analysis and Survey Results

The gathered responses were subjected to descriptive and factor analysis to explicate the issue under

study. These responses represent the first empirical study to report on this subject related to barriers

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that adversely affect the effectiveness of ACMs. The mentioned tools were adopted based on their

ability to realize the objectives of the study. Other justifications for the adoption were attributed to the

associated advantages over other tools and their wide adoption and use in other construction project

management and corruption-related studies as listed in the succeeding sections. The succeeding

sections present the statistical results in detail. The gathered data were analyzed using the 23rd version

of the Statistical Package for the Social Sciences (SPSS) and Ucinet version 6.585.

The data were first examined to determine their appropriateness and reliability prior to further analysis

because that constitutes a requirement to enhance the justifications for the results. The reliability test

was therefore conducted in this study using the Cronbach’s alpha test tool in SPSS. Because it is

extensively used in different studies and especially in construction management-related research, the

Cronbach’s alpha tool was used in this study to perform the previously mentioned tasks. Given the two

divisions of the total sample (i.e., 33 for developed countries and 32 for developing countries), the test

was performed on each group because most of the analysis and discussions were made on comparative

bases (i.e., between developed and developing countries). Complying with a scale from 0 to 1 in which

0 represents no reliability and 1 stands for full reliability, the closeness of the alpha value to 1 depicts

an increasing level of reliability and vice versa with a given threshold of 0.7 (Chan et al. 2018; Santos

1999). The respective alpha values in each context are presented in Table 8.9.

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Table 8.9: Descriptive and Mann-Whitney U Test Statistics of individual barriers

Overall Developed Countries Developing Countries Mann-Whitney U Test Statisticsa
Code Mean SD p-value Rank SWT Mean SD Rank N-value Mean SD Rank N-value U Stat* W* Z p-value
BAC1 3.47 1.24 0.001 2 0.000 2.97 1.21 5 0.76 a 4.00 1.05 3 0.89a 276.500 837.500 -3.394 0.001a
BAC2 3.25 1.21 0.000 6 0.000 2.88 1.11 7 0.64 a 3.63 1.21 5 0.45 329.000 890.000 -2.755 0.006 a
BAC3 3.02 1.38 0.000 13 0.000 2.64 1.39 12* 0.32 3.41 1.26 15 0.19 356.000 917.000 -2.306 0.021 a
BAC4 3.02 1.07 0.000 13 0.000 2.58 0.97 16 0.24 3.47 0.98 11 0.26 281.500 842.500 -3.362 0.001 a
BAC5 3.11 1.15 0.000 11 0.000 2.64 1.06 12* 0.32 3.59 1.04 6 0.40 285.500 846.500 -3.282 0.001 a
BAC6 3.35 1.21 0.000 3 0.000 3.10 1.16 2 0.93 a 3.63 1.21 5 0.45 376.500 937.500 -2.106 0.035 a
BAC7 3.02 1.17 0.000 13 0.000 2.64 1.19 12* 0.32 3.41 1.01 15 0.19 327.000 888.000 -2.729 0.006 a
BAC8 3.20 1.19 0.000 9 0.000 2.94 1.14 6 0.72 a 3.47 1.19 11 0.26 398.000 959.000 -1.758 0.079
BAC9 3.06 1.04 0.000 12 0.000 2.70 0.95 10 0.40 3.44 1.01 14 0.23 306.000 867.000 -3.070 0.002 a
BAC10 3.25 1.26 0.000 6 0.000 2.67 1.05 11 0.36 3.84 1.19 4 0.70 a 225.500 786.500 -4.098 0.000 a
BAC11 3.03 1.09 0.000 16 0.000 2.82 1.05 9 0.56 a 3.25 1.11 17 0.00 392.000 953.000 -1.875 0.061
BAC12 3.20 1.18 0.000 9 0.000 2.85 1.00 8 0.60 a 3.56 1.24 8 0.37 326.500 887.500 -2.726 0.006 a
BAC13 3.35 1.39 0.000 3 0.000 2.64 1.17 12* 0.32 4.09 1.20 1 1.00 a 202.500 763.500 -4.377 0.000 a
BAC14 2.94 1.27 0.000 17 0.000 2.40 0.99 17 0.00 3.50 1.30 9 0.30 266.000 827.000 -3.522 0.000 a
BAC15 3.25 1.09 0.000 6 0.000 3.00 0.94 3* 0.80 a 3.50 1.19 9 0.30 387.000 948.000 -1.923 0.055
BAC16 3.31 1.09 0.000 5 0.000 3.15 0.94 1 1.00 a 3.47 1.22 11 0.26 432.500 993.500 -1.304 0.192
a a
BAC17 3.51 1.12 0.001 1 0.000 3.00 1.00 3* 0.80 4.03 0.99 2 0.93 244.500 805.500 -3.850 0.000 a
Note: Cronbach's Alpha (for overalls) = 0.926; (for Developed countries) = 0.938; (for Developing countries) = 0.846; Critical Chi-Square value (at p value of 0.05)
= 26.30; Actual Chi-Square value (for overalls) = 56.746; (for Developed countries) = 49.850; (for Developing countries) = 44.633; Asymp. Sig. = 0.000 (for overalls;
Developed and Developing countries); Df = 16; SWT represents Shapiro-Wilk test; SWT results indicates data were statistically significantly; Normalization (N)
value = (actual mean-minimum mean)/(maximum mean-minimum mean); a Grouping Variable: Developed and Developing Countries; U Stat*: Mann-Whitney U
Test Statistics; W*: Wilcoxon W; MUW at significant; level of 0.05

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Table 8.10: Degree and Betweenness Centrality of the Barriers

Code BAC1 BAC2 BAC3 BAC4 BAC5 BAC6 BAC7 BAC8 BAC9 BAC10 BAC11 BAC12 BAC13 BAC14 BAC15 BAC16 BAC17

Dpd/DC 6.608 8.071* 5.419 7.659 7.905 6.654 7.755 7.657 8.168 7.965 7.894* 7.742* 8.544* 2.211 4.367 2.897 4.874

Dpg/DC 0.923 4.308* 2.593 2.315 4.509 2.830 5.123* 3.320 3.247 3.418 3.020 3.490 1.253 2.957 4.632* 4.915* 2.407

Dpd/BC 1.531 7.033# 1.547 1.639 1.964 3.603 5.008 2.033 3.161 5.097 8.647# 12.800# 8.158# 0.100 3.056 0.211 4.411

Dpg/BC 0.000 14.867# 0.000 0.200 4.367 0.575 31.200# 0.775 5.350 6.883 3.233 0.775 0.200 13.842 9.317# 17.417# 1.000

Note: Dpd = Developed countries; Dpg = Developing Countries; BC = Betweenness centrality; DC = Degree centrality; *# top nodes/barriers with a relatively higher degree values of
centrality* and betweenness #

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8.4.3 The criticality of Individual barriers of both contexts

It was not surprising to notice that the factors received relatively lower ratings by the respondents from

the developed world. Table 8.9 presents the individual ratings for the barriers for both contexts as well

as the amalgamated results of the two contexts (i.e., the overall column). All the individual ratings from

the developed world experts were approximated to be either neutral or less critical as predefined by the

Likert scale. However, despite the low ratings, it is not unnecessary to highlight the factors that received

high rankings regarding the position or how the experts view these barriers. Therefore, the experts from

the developed world share a common consensus that knowledge gap or non-familiarity with

organizational stipulations limit the potency of anti-corruption measures in infrastructure projects in

the developed context even though it had a lower rating with a mean value of 3.10. This is interpreted

from the context of not just knowing the ethical codes but also knowing what ought to be done and not

doing it (Owusu et al. 2017, Zhang et al. 2016; Le et al. .2014).

This may relate to one of the critical barriers observed in the case of the developing countries as well.

On other occasions, since some parties may already know the punishments that are meted out in the

case of any corrupt activity, the motivation to indulge in a corrupt act outweighs the fear after weighing

the advantages and risks involved in whether to indulge in a corrupt activity or not. Therefore, just like

in the case of investments, the portfolio that offers a high rate of return is worth investing in. Thus,

parties may get involved because of the projected high rate of returns coupled with the low risk of

getting caught or reported. Some of the leading barriers included the fear of being caught reporting,

[BAC6] which came second with a mean score of 3.10, inappropriate staffing [BAC15] and the lack of

will to become involved in fighting corruption [BAC17], both placed third with a mean score 3.00 each.

It was, however, quite startling to notice that fear of being caught reporting would be regarded as one

of the top three barriers in the context of developed countries despite the practical measures

implemented to ensure safe and efficient reporting of corruption cases in the developed world.

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In the case of the Developing world, corruption continues to hit the headlines on daily bases with

confirmations from the reports of top global indexes such as the corruption perception index by

Transparency International, the Worldwide Governance Indicators by the World Bank, the Global

Competitiveness Index by the World Economic Forum among many others. The situation of corruption

in the developing world does not seem to improve, and in some cases, the reports indicated above

reveals the declination in performance by most countries in the developing world as well as the

challenges that impede the progress or developments towards the expurgation of corrupt practices. Not

contradicting this background, it is worthy to note that most countries have taken great initiatives and

tremendous efforts by developing and enforcing practical measures to curtail corruption. However, just

as described in the previous sections, it is in these instances that these barriers also emerge to hamper

the effectiveness of the stipulated anti-corruption measures.

Moreover, most developed anti-corruption measures do not cater for the barriers that hamper their

effectiveness but are rather concentrated solely on eliminating the forms, causal factors, and the

identified risk indicators involved. It is, therefore, needful, to create a pragmatic and holistic approach

in dealing with corruption-related issues. Thus, encapsulating all the mentioned constructs of corruption

as well as supplementary incorporations of strategies to deal with anticipated barriers against anti-

corruption measures. The leading barriers that emerged in the case of the developing context were

political barriers as they were recognized in their individual criticalities and also as a construct, as

discussed later in this section. Lack of political will by government officials and statutory professional

councils to fight corruption [BAC13] as well as political and structural barriers [BAC1] came first and

third place respectively with their corresponding mean scores at 4.09 and 4.00. Since the factor analysis

clustered these two variables into a single construct, a detailed discussion on these two variables are

given at the construct criticality section. Personal attitude, for example, lack of will to become involved

in fighting corruption [BAC17] was identified to be the second critical barrier in the developing world

context with a mean score of 4.03. Just as Boyd and Padilla (2009) pointed that whenever there is a

case of corruption, the key identified parties include the demand side (the party that calls for the corrupt

act to be done), the supply side (the party that pays or offers the price for corruption) and the condoning

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side (the party that remains silent in the case of corruption). BA17 concerns or correlates most with the

third party (i.e., the condoning side). Even though society may frown upon this act; it should be noted

that some studies point out the justifications with which some people decide to fall into the category of

the condoning side (Boyed and Padilla 2009). Owusu et al. (2017) indicated that some of the general

factors with which the condoning parties stand on to justify their actions might stem from the lack of

trust in the context in which they work and the presumption that no better results will evolve even in

the event of reporting. Others include the associated risks attached to the disclosure of corrupt acts in a

given context; and the perception that no disciplinary actions will be taken against the culprit after

reporting. Therefore, to be in an undisturbed zone, the condoning party may opt to remain silent in the

event of a corrupt activity. Other factors such as the dread of being victimized, the fear of being

marginalized, social or occupational stigma and rejection contribute to condoner’s justification to keep

silent during the event of corruption related to loyalty to friends and organizations (Shan et al. 2015a;

Ameyaw et al., 2017; Bowen et al., 2012).

8.4.4 Individual Comparability

As pointed in the previous section, the Mann-Whitney U test was conducted to determine the statistical

differences of criticality between the identical barriers of the two contexts (i.e., developed and

developing). With the prior supposition or null hypothesis stating that there is no difference in terms of

the degree of criticality concerning the barriers, the null hypothesis were rejected in all cases except for

BAC8, BAC11, BAC15 and BAC16 where the significant values exceeded 0.05 (meaning there is no

significant statistical difference in the mentioned variables). The Mann-Whitney U test results partly

confirm the reports on the perception of corruption prevalence and control in these two contexts by

world reports stated earlier even though the results in this section are more skewed towards the field of

construction management and infrastructure procurement. The experts from the two different regions,

therefore, attest to the notion that there are differences regarding how the identified barriers affect the

modus operandi of construction project management. This is indicated by the mean values in each

context coupled with the Mann-Whitney U test results. That is, whereas respondents from the developed

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context attest to the low or neutral levels of the criticality of all the barriers, most of the barriers were

identified to be critical in the context of the developing world. Thus, confirming a sharp statistical

distinction of the barriers in the two contexts as revealed by the Mann-Whitney U test.

8.4.5 Factor and Network Analyses Results

FA was performed to identify the statistical correlations among the variables and to categorize them

into their associated constructs. Even though the factor analysis draws significant constructs after some

number necessary rotations, the network analysis amplifies the correlations by highlighting the

variables’ degree of betweenness and centrality. Table 8.11 presents the summary of the factor analysis

results and Fig. 8.45 and 8.6 illustrates the graphical presentation of the network analysis results.

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Table 8.11: Factor Analysis of Barriers in both contexts

Developed Countries x̄ = Developing Countries x̄ =
∑ 𝑥𝑖⁄ ∑ 𝑥𝑖⁄
𝑛 𝑛
Code Variable SB PPB OB Code Variable PSB SB OB PB
Social Barriers (SB) 2.734 Psychological barriers (PSB) 3.507
BAC5 .846 2.64 BAC12 .861 3.56
BAC10 .843 2.67 BAC6 .835 3.63
BAC4 .828 2.58 BAC8 .803 3.47
BAC7 .794 2.64 BAC11 .783 3.25
BAC6 .721 3.10 BAC2 .741 3.63
BAC11 .671 2.82 BAC14 .569 3.50
BAC9 .580 2.70 Social Barriers (SB) 3.538
Psycho-political Barriers (PPB) 2.845 BAC10 .832 3.84
BAC13 .818 2.64 BAC3 .773 3.41
BAC3 .760 2.64 BAC5 .713 3.59
BAC1 .713 2.97 BAC7 .697 3.41
BAC17 .694 3.00 BAC9 .550 3.44
BAC2 .665 2.88 Organizational Barriers (OB) 3.618
BAC8 .599 2.94 BAC17 .771 4.03
Organizational barriers (OB) 2.850 BAC4 .753 3.47
BAC16 .804 3.15 BAC15 .707 3.50
BAC14 .605 2.40 BAC16 .690 3.47
BAC15 .596 3.00 Political Barriers (PB) 4.045
BAC12 .568 2.85 BAC13 .698 4.09
BAC1 .581 4.00
Eigenvalues (EV) 8.807 1.851 1.463 Eigenvalues (EV) 5.230 4.117 1.466 1.054
Variance (VA) 51.803 10.891 8.608 Variance (VA) 30.762 24.217 8.626 6.200
Cumulative Variance (CV%) 51.803 62.694 71.302 CV% 30.762 54.979 63.605 69.805
N-values 0.000 0.957 1.000 N-values 0.000 0.0576 0.206 1.000
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.765 Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.568
Bartlett's Test of Sphericity Approx. Chi-Square 462.495 Bartlett's Test of Sphericity Approx. Chi-Square 341.126
df 136 df 136
Sig. 0.000 Sig. 0.000
∑ 𝑥𝑖⁄
x̄ = 𝑛 . . . 𝑒𝑞𝑢𝑎𝑡𝑖𝑜𝑛 (1); where x̄ represents the mean, ∑ 𝑥𝑖 is the summation of sampled values or frequency; n represents number of respondents or items.

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Figure 8.5: Network Analysis of the ACMs barriers in the developed context.

Figure 8.6: Network Analysis of the ACMs barriers in the developing context.

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Of the several SNA technique metrics such as the clustering coefficient, eigenvector centrality, bridge,

cohesion among other metrics, the four most widely adopted measures of centrality include the

eigenvector centrality, degree centrality, closeness and betweenness (Scott 2017; Freeman 2011).

However, this section employed two out of the four common techniques.

The two techniques adopted are the degree of centrality and betweenness. These two measures of

centrality were considered adequate and apropos to execute the objectives for which the SNA technique

was adopted. In a nutshell, even though the technique is employed to connote or represent a complex

set of relationship between individuals in the social structure and the different kinds of interdependence,

the degree of centrality and betweenness were employed in this section to illustrate the degree or extent

of the relationship among the variables or nodes, (i.e., barriers) under the two given contexts. With the

centrality measuring the critical power of nodes based on how well they connect the network, the

betweenness depicts the extent to which a node or variable lies amid other nodes of variables in the

network (Scott 2017; Kim and Hastak 2018).

Even though the inference from the application of the network analysis technique is to supplement the

degree of relationship presented by the factor analysis results, the conclusion drawn from this approach

indicates that the elimination of one barrier can greatly influence or affect the performance of another

in a given context. It can therefore be seen from Fig. 8.5 and 8.6 that the degree of relationships (i.e.

the degree of centrality and betweenness) of the nodes vary in the two contexts. Whereas the graphical

presentation in the case of the developed world demonstrates a relatively higher degree of correlated

nodes, the case is somewhat loosed in the developing world. The elimination of the nodes with a high

degree of centrality such as BA2, BAC11, BAC12, and BAC13 in the developed context as well as the

nodes BAC2, BAC7, and BAC16 in the developing context will, however, cause a very high significant

impact on the other nodes and the entire network.

In effect, the implication or inference that can be drawn is that it will be easier to eliminate these nodes

barriers in the developed context due to their close connectivity and the influence of one node on the

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other than in developing context which depicts a relatively loosed node-connectivity in the network

regarding the degree of centrality and betweenness. However, this conclusion can be regarded as a

supposition until it is tested on real-life projects.

8.4.6 Construct’s Criticality

The identified barriers were regarded suitable for factor analysis in both cases due to the realization of

meeting the requirements, which include the KMO and Bartlett’s sphericity test. Both the KMO and

Bartlett's Test of Sphericity of the two respective regions is presented in Table 8.11. The correlation

matrices in both cases were identified to be nonidentity matrices, thus suitable for further analysis. The

correlations among the variables were also sturdy in both contexts, even though stronger in the results

for the developed context than the developing. This is confirmed by the network structures in Fig. 8.5

and 8.6, as well as Table 8.10. From both figures, the correlated variables are higher in the case of the

developed than in the developing. This can be explained in two dimensions, namely betweenness and

degree centrality.

Lastly, the variances in both cases were as well adequately homogenous, hence, apropos for factor

analysis. With the application of the principal component analysis coupled with varimax rotation

methods, the factor analysis rotations generated three distinct components under the developed context,

and four under the developing context with their respective eigenvalues and total variance explained

presented in Table 8.11. All the generated factors in each case satisfied both the eigenvalue criteria of

1.0, as well as the total variance explained over 70% in each case (Norusis 2008). The naming of the

components was done using the common themes that run through the variables (Owusu et al. 2017;

Chan and Owusu 2017). Moreover, in the case where no common theme exists, the naming was done

using a combined theme of the variables with the maximum cross factor loadings and discarding the

ones with lower loading (i.e., <0.4) (Zhang et al. 2016; Le et al. 2014). The shared themes that run

through all the components were relatively similar. Moreover, a second technique to supplement the

categorization of the constructs was adapted from the study of Lee et al. (2004). Since the factor analysis

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technique was employed to analyze the same variables under two different contexts, a higher probability

of unequal generation of the components or factors was anticipated. Simply put, it was expected that

should there be three constructs formed under the developing contexts, the case of the constructs

development in the developed context is likely to vary. This, therefore, triggered the adoption of a

common label for a construct that shares at least two identical variables under the two different contexts.

For instance, the construct labeled Social Barriers was developed in both contexts because they shared

four identical variables (i.e., BA5, BA7, BA9, and BA10). Therefore, even though other variables were

found under the same construct, to harmonize and structure the labeling of the factors in a systematic

order, the approaches of Zhang et al. (2016) and Lee et al. (2004) among similar studies were identified

to be apropos for adaption.

However, one component named psycho-political in the context of the developed countries was split

into two stand-alone constructs, namely psychological barriers and political barriers in the case of the

developing context. In descending order, the three components in the developed context were

organizational barriers with a construct mean of 2.850, psycho-political barriers, and social barriers

with mean values of 2.845 and 2.734, respectively. Ranking from top to bottom, the constructs

developed in the context of the developing countries are political barriers with MS of 4.045,

psychological barriers, social barriers and organizational Barriers with respective means of 3.618, 3.538

and 3.507. Unlike the causal factors that trigger of corruption in construction projects, the barriers to

the effective enforcement and application lend themselves to administrative concerns rather than project

concerns even though these barriers have either direct or indirect influences on projects.

8.4.5.1 Political Barriers

Political barriers connote the obstructing measures posed by government officials (use or abuse of

power) directly or indirectly to thwart the effective functioning and enforcement of anti-corruption

measures (Owusu et al. 2017; Bowen et al. 2015). These kinds of barriers are often critical in

kleptocracy states where governments commonly account to no external authority and abuses delegated

power to exploit state’s resources. In effect, officials extend their power to boomerang sanctions in

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situations they are recognized to be offenders or culprits. This is largely identified in the procurement

of infrastructure works where large sums of monies are expended. It was, therefore, not surprising to

identify the political barriers as the leading construct to obstruct the effectiveness of ACM measures in

the developing world, especially given the weak political systems in most developing countries. The

leading barrier identified under this construct was the absence of political will, which is explicated to

be the political unwillingness by statutory councils and government officials to fight corruption since

they may be involved in it one way or another. This variable had the overall highest MS of 4.09 in both

contexts. The second variable in this construct is political and structural barriers with MS of 4.0. This

signifies that the primary area of concern with respect to dealing with the barriers to the effectiveness

of ACM in the developing world should always start from the top.

8.4.5.2 Psychological barriers

Psychological barriers happened to be one of the stand-alone constructs in the developing world context.

Even though it was the least ranked construct, it had the highest number of variables per the results of

the FA. Psychological barriers can be described as human-related factors (psychosomatic, mental or

emotional) that affect one’s behavior in a given setting and under a given condition (Owusu et al. 2017;

Greitzer 2013). Therefore, the response to an act in a given situation is influenced by the psychological

make-up of a person. However, one’s disposition towards the fight against corruption is not only

influenced by external factors such as institutional structures but also the influence of the external

factors on his psychological make-up. Studies, therefore, pointed that most ACMs in the context of the

developing world are not effective as they ought to be due to the psychological restraints captured under

this construct (Bowen et al. 2012; Ameyaw et al. 2017). Per the results, the top three variables identified

under this construct included the fear of being caught reporting coupled with the fear of insecurity which

includes dread of losing one’s job and the perception of no better result, distrust in system (Shan et al.

2015b; Alutu 2007; Bowen et al. 2012). The lack of trust in the governmental and institutional structures

in developing countries has been one of the paramount obstructions to the effectiveness of ACMs in the

developing context (Owusu et al. 2017). With the notion and perception that either less or no rigorous

efforts would be taken by states to bring offenders and culprits to check, put a high percentage of the

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general populates to either report a corrupt practice. Other variables identified in this construct included

bureaucratic process of reporting corrupt cases and lengthy processes of reporting corrupt cases.

Inappropriate internal institutional coordination / inter-agency relations and the lack of understanding

and knowledge of their rights within a contractual environment, difficulty in providing concrete

evidence, were all identified to be critical barriers (Owusu et al. 2017; Shan et al. 2017; Stansbury 2009;

Bowen et al. 2012).

8.4.5.3 Organizational Barriers

The barriers that contribute to the ineffectiveness of ACMs are not only limited to political or human-

related factors but also organizational or institutional factors. These are either direct or indirect factors

associated with or stemming from institutions involved in the realization of construction and other

infrastructure projects. The OG construct forms one of the two categories developed under the two

contexts (i.e., developed and developing countries) due to the commonalities that exist between the two.

Per the normalization values, this construct is highly relevant in the developed context as compared to

the developing even though its MS in the developing countries is more significant as compared to the

developed. It can, therefore, be considered to be relevant in both contexts as compared to the other

shared construct. The shared barriers between the developed and the developing included the lack of

knowledge or non-familiarity with ethical codes/ organizational codes of ethics and Inappropriate

staffing (Bowen et al. 2007; Stansbury 2009; Shan et al. 2015b). Other obstructing factors exclusive to

only the developing countries included personal attitude, for instance, in a situation where people are

not concerned with fighting the pervasiveness of corruption and social misrepresentation. In the context

of the developed world, the organizational barriers specific to this context included the lack of

understanding and knowledge of their rights within a contractual environment, difficulty in providing

concrete evidence and lastly the perception of no better end result, distrust in system (Ameyaw et al.

2017; Chan and Owusu 2017; Zou 2006; Iyer and Sagheer 2009).

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8.4.5.4 Psychosocial Barriers

Following the attributes of psychosocial-specific causal construct that was developed in the study of

Owusu et al. (2017), the psychosocial barriers can simply be defined as the relationship that exists

between the psychological attributes or behavior of a person and or on social or environmental factors.

The barriers under this construct, therefore, reveal the psychological connotations of a person as

influenced by the environment that causes a person to act lackadaisically towards the enforcement or

application of enforced ACMs or rather disregard stipulated ACMs which in turn contributes to the

pervasiveness of corrupt practices and the ineffectiveness of ACMs. Most of the social barriers against

the effectiveness of anti-corruption measures exist because of the negative strings and the harmful

effects attached to it. Krishnan (2009) presented several examples from different international reports

on why most people fear to report corrupt cases or aid to the effectiveness of ACMs.

Among the examples was death report on a civil engineer from India who blew the whistle against a

corrupt act. No one would prefer to go through such experience for reporting a case may be indirectly

connected to him. However, because there may be no stringent stipulations instituted to protect

whistleblowers or potential candidates who aim to help curb corruption, the situation worsens especially

in the developing world. This construct was identified in both the developed and the developing world

because they shared common underlying variables, which are fear of victimization, fear of being

marginalized, social or occupational stigma and rejection and lack of independence (Bowen et al. 2012;

Krishnan 2009). Other critical barriers identified include fear of losing life in the context of the

developing world and social misrepresentation, fear of being caught reporting, and the inappropriate

coordination of internal structures of an institution/ interagency relation (Ameyaw et al. 2017; Krishnan

2009; Stansbury 2009). Effective ACMs targeted at eliminating psychosocial and project-specific

causal factors of corrupt practices may incorporate strategies for curbing the identified variables under

this construct. original

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8.4.5.5 Psycho-political Barriers

The validity of the term psycho-political was coined by Prilleltensky (2003), which was defined as a

way to assess the psychological patterns of a person or a given group of people within an organization

or a community and their responsiveness to and engagements with the dynamics of power, analysis of

structural levels and social justice promotion. Thus, the term amalgamates the interplay of the theories

behind psychology and politics and the inference of the term on human behavior towards political,

structural, and social stipulations and enhancements. This construct came second place with MS of

2.845. Even though the MS indicates a neutral level of criticality, the normalization value indicates a

high level of significance of the construct’s criticality, which is 0.957.

Five variables were captured under this construct, and they are lack of political will, a lack of political

will by government officials and statutory professional councils to fight corruption, political and

structural barriers. The remaining were personal attitude, for example, lack of will to become involved

in fighting corruption, fear of insecurity which includes fear of losing job and the bureaucratic process

of reporting corrupt cases (Porter 1993; Tabish and Jha 2011; Sohail and Cavill 2008; Ameyaw et al.

2017; Bowen et al. 2012). The distinct demarcation between the two constructs lies in the notion that.

In contrast, psycho-social barriers are more centered on the correlations and the influences of

psychological factors on social behavior and vice versa, the psycho-political construct, on the other

hand, demonstrates the relationship and influences between psychological factors and political or

governmental structures. Fig. 8.7 presents mean indexes of the constructs developed for each context.

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Developed Developing
5

1
PPB OB SB PSB PB

Figure 8.7: Constructs' Comparison of the developed and developing contexts

8.4.7 Section Summary

This section of the study sought to conduct an empirical survey on the barriers that hamper the

effectiveness of existing anti-corruption measures developed to mitigate corrupt practices in the

procurement and management of construction and other infrastructure-related works. The rationale

stems from the reported notion that despite the good efforts in implementing anti-corruption measures

to mitigate the prevalence of corruption in projects and the industry, the accounts for factors that

normally obstruct the effectiveness of these measures are not fully considered (Bowen et al. 2012;

Owusu et al. 2017). Literature as well remains silent on this issue even though due considerations and

attention have been given to other constructs of the subject matter of corruption. Therefore, in order to

aptly reach the target, four objectives were set. The second objective was to examine the criticality of

the factors or variables collated during the review study with experts from different contexts (primarily

segmented into emerging and established economies or jurisdictions). The results revealed the

unwillingness of people to get involved in the fight against corruption represents the number one

impediment to the potency of existing anti-corruption measures. Other critical factors included political

and structural barriers and the fear of being caught reporting. Even though a number of constructs

namely psychological, social, organizational, political, and psycho-political, emerged after the variables

were categorized using the factor analysis technique, the root cause or rationale underpinning the

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unwillingness of persons to get involved in the fight against corruption needs to be examined in the

future. Using a total number of 65 responses which were regarded valid for the data analysis, 33 of the

responses came from experts from the developed countries and 32 from the developing. Moreover, in

determining the statistical significant difference between the views of the respondents of the two

contexts, the Mann-Whitney U test results indicated that four identical variables (BAC8, BAC11

BAC15, BAC16) were identified to be statistically insignificant in terms of their differences. However,

the remaining thirteen variables were identified to be statistically significant regarding the differences

in their levels of criticality. In essence, it can be deduced that whereas these thirteen barriers may be

considered critical by the views of the respondents from the developing context, the case is somewhat

different per the views of the experts from the developed context.

The practicality of corruption research aimed at annulling the menace in projects and the industry is as

well hindered by these factors, which this study reports (Ameyaw et al. 2017). Even though this section

of the study may be subjected to a number of limitations, there is no doubt that theoretically, it

contributes to the body of knowledge on the subject matter of corruption in addition to a deepened

holistic understanding of the topic of corruption in construction management research. It extends the

body of knowledge by first conducting a systematic review of the barriers and empirically examines

their criticality in relation to infrastructure procurement. Aside from the individual levels of the barriers’

criticalities, this section also reveals the factors that have stronger influences on factors when viewed

under the scope of their connectivity in a network. Thus, informing anti-corruption practitioners on

probable areas to tackle first in dealing with these barriers. Practically, as academic and industrial

researchers continually develop tool kits, frameworks, and policies against corrupt practices, this

section is intended to extend the coverage of dealing with corrupt practices. This section practically

reports on taking a further step in the approach in combating corruption by extending the scope beyond

the traditional causal factors with their associated vulnerabilities to cover the barriers that impede the

efficacy of existing anti-corruption measures.

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8.5 Exemplary Lessons: The Case of Hong Kong14

Throughout history to this very day, the notion and practicality of building a clean city is not only

attributed to the tangible and measurable elements around us such as clean air, high mobility healthy

and sustainable buildings among others but also the intangible characteristics that make up the city and

the people within it such as behavior, morality and ethical standards (Chan and Owusu 2017). As such,

while there are progressive scholarship and contributions towards the measurable components of a city,

the situation is somewhat opposite for the case of the intangible attributes of what makes up a clean

city. The subject of corruption has not been only a scholarly topic studied for the past centuries but also

a devastating socio-economic issue that has lived with humans for more than five millenniums (Noonan

1984). Even though corruption is regarded as the exploitation of public resources for private gain in

diverse contexts including the social and political settings, the context of procurement regard corruption

as the distortion of any of the stages within the procurement process with the intention of

misappropriating project’s resources (Le et al. 2014; Owusu et al. 2018). The resources may range from

monetary to valuable properties and other gains, such as illegal favors, among others (Stansbury and

Stansbury 2009).

Several studies have been conducted to explore the diverse constructs of corruption in order to

demystify the complex and clandestine nature of corrupt practices to identify its causes, contextual risks

indicators, anti-corruption measures and the barriers that hinder the effective application of anti-

corruption measures not only in the political and business arenas but also in the procurement, execution,

and management of infrastructure projects (Le et al. 2014; Owusu et al. 2017). This section focuses on

anti-corruption measures, which may be regarded as the tools, policies and frameworks developed and

enforced to thwart the incidence and proliferation of corrupt practices in the short term as well as

extirpate its effects in the long run (Shan et al. 2015). Even though some studies regarding the generic

14
Owusu, E. K., Chan, A. P., Yang, J., & Pärn, E. (2020). Towards corruption-free cities: Measuring the
effectiveness of anti-corruption measures in infrastructure project procurement and management in Hong Kong.
Cities, 96, 102435.

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application of these established measures have been conducted, not many works have been undertaken

on the specificity of their application, especially in the context of infrastructure procurement and

management. Moreover, the contextual explorations on the subject matter remain few with a number of

the empirical studies focused on the developing countries (Ameyaw et al. 2017; Tabish and Jha 2012;

Shan et al. 2015; Zou 2006; Sichombo et al. 2009) among others. This section, however, advances the

existing knowledge by conducting an empirical assessment of the comprehensive list of the anti-

corruption measures in the developed region with other vital measures, peculiar to the context. With

this being one of the first empirical studies to be conducted in a developed context, policymakers, and

project stakeholders in other developed contexts to assess the performance of projects regarding their

resistance to corrupt activities and, in turn, assess the effectiveness of anti-corruption measures.

8.5.1 Pretests

In advance of the commencement of detailed analysis, there is a wide consensus among different

scholars on the need to determine the statistical normality and reliability of the data to be analyzed

(Spiliotopoulou 2009; Santos 1999; Shan et al. 2017). The determination of these two tests is considered

to be vital as they form part the basic and most important pre-tests to be conducted as well as their

ability to influence the selection of suitable statistical tools and techniques to be adopted (in the case of

examining data normality). Moreover, they determine whether further analysis of the data can be

conducted (in the case of reliability). The data reliability was determined by conducting the Cronbach

Alpha’s (CA) test. Per the stipulation of Nunally (1978), the threshold for establishing a statistically

reliable dataset should not be less than 0.7. With the given range of 0 to 1 as the extreme variants, the

greater the calculated reliability nears zero, the lesser its reliability and vice versa. Zero, therefore

indicates no reliability, whereas one indicates full reliability. The actual estimated CA for this section

of the study was 0.958, which reflects an extremely high level of reliability. However, the second pre-

test (i.e., data normality test) was not conducted as the tools employed in this section of the study did

not require any pattern of the distribution of data (whether normal or non-normal).

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8.5.2 Mean Index Estimations

The mean index approach was primarily adopted to examine the variable identified at first hand. As a

standard tool in research, the mean technique is often used to determine the central tendency a given

data (Kothari, 2004). Mathematically, the mean index for the variables is estimated using the formula

below:

∑(𝑓. 𝑠)
𝑀𝐼 = ⁄ , where MI represents the mean index, f represents the number of ratings (i.e., 1-5) for
𝑁

each anti-corruption variable; s represents the score assigned to each ACM by the experts which range

from 1-5 (i.e., 1= least effective to 5=most effective); and N represents the total number of responses

retrieved for a specific ACM.

8.5.3 Measuring the effectiveness of the measures

Analogous to the FSE applications conducted in the previous chapters, the following steps are followed

to arrive at the overall effectiveness index as well as the model for evaluating the effectiveness of anti-

corruption measures:

8.5.3.1 Developing the Assessment Index System

With the establishment of six interrelated anti-corruption constructs, an evaluation index criterion is

developed by defining the anti-corruption constructs as the first level index criteria. This is presented

as 𝑓𝑎𝑐𝑚 = (𝑓1 , 𝑓2 , 𝑓3 .., 𝑓𝑚 ) (Ameyaw and Chan, 2015; Shao, 2004; Li et al. 2013). The measures

(variables) within their respective constructs (factors) are defined as the second level index criteria 𝑓2 =

{𝑓21 , 𝑓22 , 𝑓23 .., 𝑓2𝑚 }. These established input criteria will, therefore, be used as the input variables for

the analysis of the FSE technique.

8.5.3.2 Evaluating the membership functions for the AC Variables and Constructs

The membership functions of both the variables and their respective constructs of the anti-corruption

measures are computed using the fuzzy mathematics and with their reference to the grading systems

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employed to evaluate the effectiveness of the measures which is presented by 𝑔= (1,2,3,4,5), where

𝑔1 = very low, 𝑔2 = low, 𝑔3 = neutral, 𝑔4 = high, 𝑔5 = very high. Thus, the membership functions are

computed using the formula below:

𝑧1 𝑓 𝑧2 𝑓 𝑧3 𝑓 𝑧4 𝑓 𝑧5 𝑓 𝑧1 𝑓 𝑧𝑓 𝑧5 𝑓
𝑖𝑛 𝑖𝑛 𝑖𝑛 𝑖𝑛 𝑣𝑖𝑛
𝑀𝐹𝑓𝑖𝑛 = 𝑔1
+ 𝑔2
+ 𝑔3
𝑖𝑛
+ 𝑔4
+ 𝑔5
= 𝑣𝑒𝑟𝑦 𝑖𝑛
𝑙𝑜𝑤
+ 𝑙𝑜𝑤
𝑖𝑛
+. . . . + 𝑣𝑒𝑟𝑦 ℎ𝑖𝑔ℎ equation (1)

where𝑀𝐹𝑓𝑖𝑛 represents the membership function of a specific anti-corruption variable; 𝑓𝑖𝑛 connotes the

𝑓𝑡ℎ anti-corruption variable of a specific construct 𝑖 (𝑖=𝑓1 , 𝑓2 , 𝑓3 , 𝑓4 , 𝑓5 , 𝑓6 ), 𝑍𝑘 𝑓 (𝑘=1,2,3,4,5)

𝑖𝑛

constitutes the percentage of the experts who graded 𝑘 for every specific anti-corruption measure 𝑓𝑖𝑛 ,
𝑧1 𝑓𝑖𝑛
which represents the degree of MF. The term ⁄𝑔1 connotes the relation between 𝑧1 𝑓 and its grade
𝑖𝑛

systems rather than a fraction and also ‘+’ represents a symbol rather than an addition. Thus, given the

interpretation above, equation (1) can be rewritten as 𝑀𝐹𝑓𝑖𝑛 = (𝑧1 𝑓𝑖𝑛 + 𝑧2 𝑓𝑖𝑛 + 𝑧3 𝑓𝑖𝑛 + 𝑧4 𝑓𝑖𝑛 + 𝑧5 𝑓𝑖𝑛 )

– equation (2). The units within every membership function range between 0 to 1 and their summation

must equate 1 (i.e., ∑5𝑘=1 𝑍𝑘 𝑓 = 1) – equation (3).

𝑖𝑛

8.5.3.3 Determining the weightings of each ACM variable and construct

The weight function of either an ACM variable or a construct can be regarded as the relative importance

of the variable/construct as estimated by the experts and from their responses. The weighted function

can be determined from the normalized mean method (Lo 1999) and the analytic hierarchy process

(AHP) (Hsia1998). The normalized mean method is adopted to estimate the weights of both the ACM

variables and constructs for this section also as it has been identified to be straightforward, easy and has

been employed by other analogous studies (Xu et al. 2010; Ameyaw and Chan 2015). The normalization

of the mean values of each ACM variable and construct is calculated using the formula below:

5
𝑀𝑖
𝑦𝑖 = , 0 < 𝑤𝑖 < 1, 𝑎𝑛𝑑 ∑ 𝑤𝑖 = 1
∑5𝑖=1 𝑀𝑖
𝑖=1

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where 𝑦𝑖 represents the weighting function of each ACM variable or construct 𝑖 regarding their levels

of effectiveness and 𝑀𝑖 represent the mean index of a particular variable or construct obtained from the

survey. A set’s weighting function can thus be presented by; 𝑦𝑖 = (𝑦1 , 𝑦2 , 𝑦3 , . . . 𝑦𝑛 ) equation - (5).

8.5.3.4 Developing a multi-level and multi-criteria FSE model

The evaluation of the effectiveness of the anti-corruption measures (both at the variables’ level and the

construct level) is regarded as a multi-level and a multi-criteria activity encapsulating four stages. With

stage one already completed (i.e., the elicitation of the experts’ judgment regarding the effectiveness of

the variables and the statistical computation of the measures, stage 2 comprises the establishment of

both the weighting and membership functions of the anti-corruption measures (variables) based on the

experts’ responses from the survey. Analogous to the second stage, the third stage establishes the

weighting and the membership functions at the level of the construct and then determine their respective

levels of effectiveness. The last stage encapsulates all the estimated constructs and computes the overall

effectiveness index, which is indicated by a single index (i.e., OEI, the overall effectiveness index).

Thus, to estimate the effectiveness of an ACM construct, a fuzzy matrix is developed for every ACM

construct after the computation of the fuzzy MFs for all the variables within their constructs. Therefore,

following equation 2, the MFs for all the variables within their respective constructs can be presented

in the fuzzy matrix presented below:

𝑀𝐹𝑓𝑖1 𝑧1 𝑓𝑖1 𝑧2 𝑓𝑖1 𝑧3 𝑓𝑖1 𝑧4 𝑓𝑖1 𝑧5 𝑓𝑖1

𝑀𝐹 𝑧2 𝑧1 𝑓𝑖2 𝑧1 𝑓𝑖2 𝑧1 𝑓𝑖2 𝑧1 𝑓𝑖2
| 𝑓𝑖2 | | 𝑓𝑖2
Ri= 𝑀𝐹𝑓𝑖3 = 𝑧3 𝑓𝑖3 𝑧1 𝑓𝑖3 𝑧1 𝑓𝑖3 𝑧1 𝑓𝑖𝑛3 𝑧1 𝑓𝑖2 | – equation (6), elements are presented by 𝑍𝑘 .
| | ⋯ 𝑓𝑖𝑛
|
⋯ ⋯ ⋯ ⋯ ⋯ |
𝑀𝐹𝑓 𝑧1 𝑓𝑖𝑛 𝑧2 𝑓𝑖𝑛 𝑧3 𝑎𝑖𝑛 𝑧4 𝑎𝑖𝑛 𝑧5 𝑎𝑖𝑛
𝑖𝑛

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Therefore, with reference to the equation (6) and the application of the weighted function set of the

ACM variables within their respective constructs, the fuzzy evaluation matrix is estimated using the

formula below: 𝑃𝑖 = 𝑌𝑖 ●𝑅𝑖 , = (𝑝𝑖𝑛 , 𝑝𝑖𝑛 , 𝑝𝑖𝑛 , … 𝑝𝑖𝑛 ) − 𝑒𝑞𝑢𝑎𝑡𝑖𝑜𝑛 (7).

𝑧1 𝑓𝑖1 𝑧2 𝑓𝑖1 𝑧3 𝑓𝑖1 𝑧4 𝑓𝑖1 𝑧5 𝑓𝑖1

𝑧2 𝑧1 𝑓𝑖2 𝑧1 𝑓𝑖2 𝑧1 𝑓𝑖2 𝑧1 𝑓𝑖2
|𝑧 𝑓𝑖2 𝑧1 𝑓 𝑧1 𝑓 𝑧1 𝑓 𝑧1 𝑓 | = (𝑝𝑖𝑛 , 𝑝𝑖𝑛 , 𝑝𝑖𝑛 , … 𝑝𝑖𝑛 ).
Therefore 𝑃𝑖 = (𝑦1 , 𝑦2 , 𝑦3 , . . . 𝑦𝑛 )● 3 𝑓𝑖3
| ⋯ ⋯
𝑖3
⋯
𝑖3
⋯
𝑖𝑛3
⋯ |
𝑖2

𝑧1 𝑓 𝑧2 𝑓 𝑧3 𝑎 𝑧4 𝑎 𝑧5 𝑎
𝑖𝑛 𝑖𝑛 𝑖𝑛 𝑖𝑛 𝑖𝑛

Where 𝑃𝑖 represents the membership degree of the grading systems 𝑔𝑖 , concerning a given construct 𝑖,

the notation ‘●’ represents a composite operation in the fuzzy environment. The estimated matrices

𝑃𝑖 (𝑖 = 1, 2, 3, 4, 5, 6) will now represent the fuzzy matrix 𝑅̅ to estimate the

𝑀𝐹1 𝑝11 𝑝12 𝑝13 𝑝14 𝑝15

𝑀𝐹2 𝑝21 𝑝22 𝑝23 𝑝24 𝑝25
|𝑀𝐹 | |𝑝 𝑝32 𝑝33 𝑝34 𝑝35 |
3 31
OEI of the measures (ACM). Thus 𝑅̅ = = 𝑝 𝑝42 𝑝43 𝑝44 𝑝45 | – equation (8).
𝑀𝐹4 41
| | |
𝑀𝐹5 𝑝51 𝑝52 𝑝53 𝑝54 𝑝55
𝑀𝐹6 𝑝61 𝑝62 𝑝63 𝑝65 𝑝65

It must be noted that the numbers presented in the set 𝑃𝑖 (𝑖 = 1, 2, 3, 4, 5, 6) represent the respective

constructs of the ACM. Thus 1= RGM, 2= MAM, 3=COM, 4=PRM, 5=PBM, 6=REM. Therefore, with

reference to equation (7), 𝑅̅ is again subjected to the normalization process through the weighted

function of the individual constructs(𝑦′1 , 𝑦′2 , 𝑦′3 , . . . 𝑦′𝑛 ) to obtain the FSE matrix at the fourth stage as

explicated in point 4, ‘Developing a multi-level and multi-criteria FSE model’. Therefore,

𝑝11 𝑝12 𝑝13 𝑝14 𝑝15

𝑝21 𝑝22 𝑝23 𝑝24 𝑝25
|𝑝31 𝑝32 𝑝33 𝑝34 𝑝35 |
𝑃̅ = 𝑌̅●𝑅̅ ≈ (𝑦′1 , 𝑦′2 , 𝑦′3 , . . . 𝑦′𝑛 )● 𝑝 𝑝42 𝑝43 𝑝44
′ ′ ′ ′ ′
𝑝45 | = (𝑃 1 , 𝑃 2 , 𝑃 3 , 𝑃 4 , 𝑃 5 ) −
| 41
𝑝51 𝑝52 𝑝53 𝑝54 𝑝55
𝑝61 𝑝62 𝑝63 𝑝65 𝑝65

equation (9).

Where 𝑃̅ (𝑖. 𝑒. , 𝑃 ′1 , 𝑃 ′ 2 , 𝑃 ′ 3 , 𝑃 ′ 4 , 𝑃 ′ 5 ) represents the membership function or the fuzzy evaluated matrix

for the anti-corruption effectiveness index for the procurement, execution, and management of

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infrastructure projects in the developed context, which is further captured by incorporating the grading

systems (g=1, 2, 3, 4, 5). This is completed using the formula below:

∑5𝑖=1 𝑃̅ × 𝐺 𝑡 = (𝑃 ′1 , 𝑃 ′ 2 , 𝑃 ′ 3 , 𝑃 ′ 4 , 𝑃 ′ 5 ) × (1,2,3,4,5), 1 ≤ 𝑂𝐸𝐼 ≤ 5, – equation (10), where OEI

represents the overall effectiveness index of ACM. This stage is normally referred to as defuzzification.

The term is backed by the rationale that the fuzzy are at this level, converted into a more understandable

(or ‘crisp’ in the fuzzy environment) to facilitate decision-making. Hence the membership functions of

the ACM index are defuzzified with the application of the grading system 𝑔𝑡 (Ameyaw and Chan 2015;

Sadiq and Rodriguez 2004).

8.5.3.5 Application of the FSE technique

Applying the detailed FSE stages presented above, the FSE analysis of the data solicited from the

experts to determine the effectiveness of the ACM variables and their respective constructs are

presented below:

3.5.5.1. Index system development

As explicated earlier, the development of the index systems for both the constructs (first level) and the

variables (second level) captured under the ACM constructs are presented as:

𝑓𝑎𝑐𝑚 = (𝑓𝑟𝑔𝑚 , 𝑓𝑚𝑎𝑚 , 𝑓𝑐𝑜𝑚 , 𝑓𝑝𝑟𝑚 , 𝑓𝑝𝑏𝑚 , 𝑓𝑟𝑒𝑚 ) representing the first level construct and;

𝑓𝑟𝑔𝑚 = (𝑓𝑟𝑔𝑚1 , 𝑓𝑟𝑔𝑚2 , 𝑓𝑟𝑔𝑚3 );

𝑓𝑚𝑎𝑚 = (𝑓𝑚𝑎𝑚1 , 𝑓𝑚𝑎𝑚2 , 𝑓𝑚𝑎𝑚3 , 𝑓𝑚𝑎𝑚4 , 𝑓𝑚𝑎𝑚5 );

𝑓𝑐𝑜𝑚 = (𝑓𝑐𝑜𝑚1 , 𝑓𝑐𝑜𝑚2 , 𝑓𝑐𝑜𝑚3 );

𝑓𝑝𝑟𝑚 = (𝑓𝑝𝑟𝑚1 , 𝑓𝑝𝑟𝑚2 , 𝑓𝑝𝑟𝑚3 , 𝑓𝑝𝑟𝑚4 , 𝑓𝑝𝑟𝑚5 );

𝑓𝑝𝑏𝑚 = (𝑓𝑝𝑏𝑚1 , 𝑓𝑝𝑏𝑚2 , 𝑓𝑝𝑏𝑚3 , 𝑓𝑝𝑏𝑚4 , 𝑓𝑝𝑏𝑚5 );

𝑓𝑟𝑒𝑚 = (𝑓𝑟𝑒𝑚1 , 𝑓𝑟𝑒𝑚2 , 𝑓𝑟𝑒𝑚3 , 𝑓𝑟𝑒𝑚4 ) as the second level constructs.

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Table 8.12: Descriptive and Weightings of ACM Variables and Constructs

No Variables MV NV SD Sig OR CR TM WVC
Regulatory Measures 𝒇𝒓𝒈𝒎 11.15 0.116
1 Comprehensive rules and 3.84 0.61 0.718 𝑓𝑟𝑔𝑚1 7 1
regulations
2 Development of strong political 3.76 0.52 0.786 𝑓𝑟𝑔𝑚2 9 2
and ethical will to enforce
existing anti-corruption policies
and laws.
3 Ethical code 3.55 0.27 0.795 𝑓𝑟𝑔𝑚3 19 3
Managerial/Administrative 𝒇𝒎𝒂𝒎
Measures 18.10 0.189
4 Transparency mechanism 4.18 1.00 0.801 𝑓𝑚𝑎𝑚1 1 1
5 Increase in accountability 3.63 0.36 0.751 𝑓𝑚𝑎𝑚2 15 2
6 Financial disclosure/Disclosure 3.58 0.30 0.826 𝑓𝑚𝑎𝑚3 18 3
7 Professional associations 3.39 0.09 0.855 𝑓𝑚𝑎𝑚4 25 4
8 Good leadership 3.32 0.00 0.933 𝑓𝑚𝑎𝑚5 26 5
Compliance Measures 𝒇𝒄𝒐𝒎 11.16 0.116
9 Compliance to fairness and 3.84 0.61 0.754 𝑓𝑐𝑜𝑚1 7 1
transparent procedures
10 Contractual compliance 3.79 0.55 0.811 𝑓𝑐𝑜𝑚2 8 2
11 Procedural compliance 3.53 0.24 0.762 𝑓𝑐𝑜𝑚3 21 3
Promotional Measures 𝒇𝒑𝒓𝒎 21.82 0.227
12 Education 3.76 0.52 0.852 𝑓𝑝𝑟𝑚1 10 1
13 Training and development 3.74 0.48 0.685 𝑓𝑝𝑟𝑚2 11 2
initiatives
14 Raising awareness 3.74 0.48 0.828 𝑓𝑝𝑟𝑚3 12 3
15 Information technology 3.61 0.33 0.823 𝑓𝑝𝑟𝑚4 16 4
16 Access to information 3.55 0.27 0.860 𝑓𝑝𝑟𝑚5 20 5
17 Enhance communication 3.42 0.12 0.858 𝑓𝑝𝑟𝑚6 24 6
Probing Measures 𝒇𝒑𝒃𝒎 19.05 0.199
18 Rigorous supervision among 3.92 0.70 0.673 𝑓𝑝𝑏𝑚1 3 1
others
19 Rigorous technical auditing 3.92 0.70 0.850 𝑓𝑝𝑏𝑚2 3 2
system
20 Contract monitoring 3.87 0.64 0.704 𝑓𝑝𝑏𝑚3 5 3
21 Efficient reporting system 3.68 0.42 0.702 𝑓𝑝𝑏𝑚4 13 4
(independent hotline)
22 Whistle-blowing mechanism 3.66 0.39 0.669 𝑓𝑝𝑏𝑚5 14 5
Reactive Measures 𝒇𝒓𝒆𝒎 14.64 0.153
23 Harsh punishment 4.11 0.91 0.606 𝑓𝑟𝑒𝑚1 2 2
24 Dismissal from employment 3.61 0.33 0.856 𝑓𝑟𝑒𝑚2 17 3
25 Effective investigation, court 3.50 0.21 0.923 𝑓𝑟𝑒𝑚3 22 4
proceedings, departmental
disciplinary action

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 Chapter 8 – Global Perspectives

26 Debarment/promoting fair 3.42 0.12 0.826 𝑓𝑟𝑒𝑚4 23 5

debarment procedures
95.92 1.000
MV-Mean values; NV- Normalized values; SD-Standard Deviation; Sig-Significance; RO-Overall
Rank; CR-Construct Rank; TM-Total Mean; WVC-Weighting of VC

8.5.3.6 MF assessment of the constructs and the variables

Using the gathered evaluations retrieved from the expert survey, the variable ‘Training and development

initiatives’ obtained the following scores 0% as ‘very low’; 3% as ‘low’; 32% as ‘moderate’; 55% as ‘high’

and 11% as ‘very high’ and was assessed through equation 1 as:
0.00 0.03 0.32 0.55 0.11
𝑀𝐹𝑓𝑖𝑛 = 𝑣𝑒𝑟𝑦 𝑙𝑜𝑤 + 𝑙𝑜𝑤 + 𝑚𝑜𝑑𝑒𝑟𝑎𝑡𝑒 + ℎ𝑖𝑔ℎ + 𝑣𝑒𝑟𝑦 ℎ𝑖𝑔ℎ . The MF is therefore expressed through equation 2

as (0.00, 0.03, 0.32, 0.55, 0.11). The MFs for the other variables are computed in a like manner and are

presented in Table 8.13. The generated MFs for the variables serve as the foundations for evaluating their

respective constructs. However, prior to the estimations of the MFs at the construct level is the evaluation

of the respective weights of the variables. The estimation of the weights is thus conducted in the next section.

8.5.3.7 Weights Estimations

The ACM variables and constructs weighted functions are computed from the mean values generated from

the experts’ survey. For instance, from Table 8.12, given the total mean of ‘promotional measures’ as 19.05.

Therefore, the weighted function of the variable ‘efficient reporting system’ (i.e., 𝑓𝑝𝑏𝑚4 ) can be calculated

3.68 3.68
through equation (4) as: 𝑦𝑝𝑏𝑚4 = = = 0.193. The remaining variables for this
3.92+3.92+3.87+3.68+3.66 19.05

construct, as well as all the other constructs, are calculated following the same procedure. The results for

all the weighted variables are presented in Table 8.13. Moreover, the individual weighted functions of a

specific construct must satisfy the condition stated in equation (4) (𝑖. 𝑒. , ∑5𝑖=1 𝑦𝑖 = 1). Thus, using the same

construct (i.e., probing measures as an example), the result of weighted function values is estimated to be,

as shown below:

∑5𝑖=1 𝑦𝑖 = 0.206 + 0.206 + 0.203 + 0.193 + 0.192 = 1.

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The weighted functions of the constructs are also calculated using the same technique. However, instead of

the variable mean values, the values for the constructs are normalized to obtain the respective weightings

for each construct. Therefore, using the total means of the constructs (i.e., 95.92) and the individual means

for the construct (𝑖. 𝑒. , 𝑓𝑟𝑔𝑚 = 11.15, 𝑓𝑚𝑎𝑚 = 18.10, 𝑓𝑐𝑜𝑚 = 11.16, 𝑓𝑝𝑟𝑚 = 21.82, 𝑓𝑝𝑏𝑚 =

19.05, 𝑓𝑟𝑒𝑚 = 14.64) in Table 8.14, the weightings for the constructs are calculated below:

11.15 11.15
𝑓𝑟𝑔𝑚 = = = 0.116
11.15 + 18.10 + 11.16 + 21.82 + 19.05 + 14.64 95.92

18.10 18.10
𝑓𝑚𝑎𝑚 = = = 0.189
11.15 + 18.10 + 11.16 + 21.82 + 19.05 + 14.64 95.92

11.16 11.16
𝑓𝑐𝑜𝑚 = = = 0.116
11.15 + 18.10 + 11.16 + 21.82 + 19.05 + 14.64 95.92

21.82 21.82
𝑓𝑝𝑟𝑚 = = = 0.227
11.15 + 18.10 + 11.16 + 21.82 + 19.05 + 14.64 95.92

19.05 19.05
𝑓𝑝𝑏𝑚 = = = 0.199
11.15 + 18.10 + 11.16 + 21.82 + 19.05 + 14.64 95.92

14.64 14.64
𝑓𝑟𝑒𝑚 = = = 0.153
11.15 + 18.10 + 11.16 + 21.82 + 19.05 + 14.64 95.92

Analogous to the estimations of the weighted functions of the variables, the normalized weightings of the

constructs must sum up to 1 (𝑖. 𝑒. , ∑5𝑖=1 𝑦𝑖 = 0.116 + 0.189 + 0.116 + 0.227 + 0.199 + 0.153 = 1). The

estimated values are moreover presented through equation 5 as:

𝑦𝑖 = (0.116, 0.189, 0.116, 0.227, 0.199, 0.153).

Table 8.13: Membership Functions (MFs) at ACM Variables and Constructs Levels
No Variables Mean Weight MF for Level 3 MF for Level 2
ings
Regulatory 0.02, 0.04, 0.26, 0.58, 0.11
Measures (𝒇𝒓𝒈𝒎 )
1 𝑓𝑟𝑔𝑚1 3.84 0.344 0.00, 0.05, 0.18, 0.63, 0.13
2 𝑓𝑟𝑔𝑚2 3.76 0.337 0.03, 0.03, 0.21, 0.63, 0.11
3 𝑓𝑟𝑔𝑚3 3.55 0.318 0.03, 0.03, 0.39, 0.47, 0.08

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Managerial 0.01, 0.06, 0.35, 0.40, 0.17

Measures (𝒇𝒎𝒂𝒎 )
4 𝑓𝑚𝑎𝑚1 4.18 0.231 0.00, 0.03, 0.16, 0.42, 0.39
5 𝑓𝑚𝑎𝑚2 3.63 0.201 0.00, 0.05, 0.37, 0.47, 0.11
6 𝑓𝑚𝑎𝑚3 3.58 0.198 0.03, 0.03, 0.39, 0.45, 0.11
7 𝑓𝑚𝑎𝑚4 3.39 0.187 0.03, 0.08, 0.45, 0.37, 0.08
8 𝑓𝑚𝑎𝑚5 3.32 0.183 0.03, 0.13, 0.45, 0.29, 0.11

Compliance 0.01, 0.03, 0.35, 0.47, 0.15

Measures(𝒇𝒄𝒐𝒎 )
9 𝑓𝑐𝑜𝑚1 3.84 0.344 0.00, 0.03, 0.29, 0.50, 0.18
10 𝑓𝑐𝑜𝑚2 3.79 0.340 0.03, 0.00, 0.29, 0.53, 0.16
11 𝑓𝑐𝑜𝑚3 3.53 0.316 0.00, 0.05, 0.47, 0.37, 0.11

Promotional 0.02, 0.05, 0.29, 0.53, 0.10

Measures(𝒇𝒑𝒓𝒎 )
12 𝑓𝑝𝑟𝑚1 3.76 0.172 0.03, 0.03, 0.26, 0.53, 0.16
13 𝑓𝑝𝑟𝑚2 3.74 0.171 0.00, 0.03, 0.32, 0.55, 0.11
14 𝑓𝑝𝑟𝑚3 3.74 0.171 0.03, 0.03, 0.26, 0.55, 0.13
15 𝑓𝑝𝑟𝑚4 3.61 0.165 0.03, 0.05, 0.29, 0.55, 0.08
16 𝑓𝑝𝑟𝑚5 3.55 0.163 0.03, 0.05, 0.37, 0.45, 0.11
17 𝑓𝑝𝑟𝑚6 3.42 0.157 0.03, 0.13, 0.26, 0.55, 0.03
Probing 0.01, 0.02, 0.24, 0.59, 0.13
Measures(𝒇𝒑𝒃𝒎 )
18 𝑓𝑝𝑏𝑚1 3.92 0.206 0.00, 0.03, 0.18, 0.63, 0.16
19 𝑓𝑝𝑏𝑚2 3.92 0.206 0.03, 0.03, 0.16, 0.58, 0.21
20 𝑓𝑝𝑏𝑚3 3.87 0.203 0.03, 0.00, 0.16, 0.71, 0.11
21 𝑓𝑝𝑏𝑚4 3.68 0.193 0.00, 0.03, 0.37, 0.50, 0.11
22 𝑓𝑝𝑏𝑚5 3.66 0.192 0.00, 0.03, 0.37, 0.53, 0.08
Reactive 0.02, 0.06, 0.26, 0.53, 0.12
Measures(𝒇𝒓𝒆𝒎 )
23 𝑓𝑟𝑒𝑚1 4.11 0.281 0.00, 0.00, 0.13, 0.63, 0.24
24 𝑓𝑟𝑒𝑚2 3.61 0.247 0.03, 0.08, 0.24, 0.58, 0.08
25 𝑓𝑟𝑒𝑚3 3.50 0.239 0.03, 0.13, 0.24, 0.53, 0.08
26 𝑓𝑟𝑒𝑚4 3.42 0.234 0.03, 0.05, 0.47, 0.37, 0.08

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8.5.3.8 Multi-level and multi-criteria FSE model Development

As stated earlier, the FSE technique encapsulates three levels (i.e., from level three to level one). To

determine the effectiveness of a particular ACM variable, the membership function (or the fuzzy

relational matrix) is first computed based on the responses obtained from the experts as established

previously. This is succeeded by the derivation of the MFs at the construct level. Thus, the equations 6

and 7 are employed to generate the MFs at both levels. For instance, the MFs of the variables within

the managerial/administrative construct (𝑖. 𝑒. , 𝑓𝑚𝑎𝑚1 ) can be presented as:

𝑀𝐹𝑓𝑚𝑎𝑚1
0.00 0.03 0.16 0.42 0.39
𝑀𝐹𝑓𝑚𝑎𝑚2 0.00 0.05 0.37 0.47 0.11
| |
𝑅𝑚𝑎𝑚 = 𝑀𝐹𝑓𝑚𝑎𝑚3 =||0.03 0.03 0.39 0.45 0.11|| The MF (fuzzy matrix) generated at this point
|𝑀𝐹 | 0.03 0.08 0.45 0.37 0.08
𝑓𝑚𝑎𝑚4
𝑀𝐹𝑓𝑚𝑎𝑚5 0.03 0.13 0.45 0.29 0.11

is further normalized through the weighted functions of the variables within their respective construct

(𝑓𝑚𝑎𝑚 ) to generate the evaluation matrix. This is computed using the equation as presented below:

𝑀𝐹𝑓𝑚𝑎𝑚1
𝑀𝐹
| 𝑓𝑚𝑎𝑚2 |
𝑃𝑖 = 𝑌𝑖 ●𝑅𝑖 , = (𝑝𝑖𝑛 , 𝑝𝑖𝑛 , 𝑝𝑖𝑛 , … 𝑝𝑖𝑛 ) ≈ (𝑦𝑚𝑎𝑚1 , 𝑦𝑚𝑎𝑚2 , 𝑦𝑚𝑎𝑚3 , 𝑦𝑚𝑎𝑚4 , 𝑦𝑚𝑎𝑚5 ) 𝑥 𝑀𝐹𝑓𝑚𝑎𝑚3
|𝑀𝐹 |
𝑓𝑚𝑎𝑚4
𝑀𝐹𝑓𝑚𝑎𝑚5

0.00 0.03 0.16 0.42 0.39

0.00 0.05 0.37 0.47 0.11
𝑃𝑖 = (0.231, 0.201, 0.198, 0.187, 0.183) 𝑥 ||0.03 0.03 0.39 0.45 0.11||. Therefore,
0.03 0.08 0.45 0.37 0.08
0.03 0.13 0.45 0.29 0.11

𝑃𝑖 = (0.01, 0.06, 0.35, 0.40, 0.17). The fuzzy evaluation matrix for the remaining constructs are

generated following the same technique. Therefore, having established the variables of the ACM, the

effectiveness of the constructs can be determined using equation (10) (𝑖. 𝑒. , ∑5𝑖=1 𝑃̅ × 𝐺 𝑡 ) 1 ≤ 𝑂𝐸𝐼 ≤

5 as demonstrated below:

∑ 𝑃𝑚𝑎𝑚 × 𝐺 𝑡 = (0.01, 0.06, 0.35, 0.40, 0.17) × (1,2,3,4,5)

𝑖=1

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𝐸𝐼𝑚𝑎𝑚 = [(0.01 × 1) + (0.06 × 2) + (0.35 × 3) + (0.40 × 4) + (0.17 × 5)] = 3.65 (effective)

Where EI represents the effectiveness index (EI) for the construct. The remaining constructs are thus,

computed using the same formula as presented below:

𝐸𝐼𝑟𝑔𝑚 = [(0.02 × 1) + (0.04 × 2) + (0.26 × 3) + (0.58 × 4) + (0.11 × 5)] = 3.72 (effective)

𝐸𝐼𝑐𝑜𝑚 = [(0.01 × 1) + (0.03 × 2) + (0.35 × 3) + (0.47 × 4) + (0.15 × 5)] = 3.72 (effective)

𝐸𝐼𝑝𝑟𝑚 = [(0.02 × 1) + (0.05 × 2) + (0.29 × 3) + (0.53 × 4) + (0.10 × 5)] = 3.64 (effective)

𝐸𝐼𝑝𝑏𝑚 = [(0.01 × 1) + (0.02 × 2) + (0.24 × 3) + (0.59 × 4) + (0.13 × 5)] = 3.81 (effective)

𝐸𝐼𝑟𝑒𝑚 = [(0.02 × 1) + (0.06 × 2) + (0.26 × 3) + (0.53 × 4) + (0.12 × 5)] = 3.68 (effective)

8.5.3.9 Assessment of the Overall Effectiveness Index (OEI)

Following the formula indicated in the equation (9) (𝑖. 𝑒. , 𝑃̅ = 𝑌̅●𝑅̅ ), the fuzzy matrix obtained at this

level [𝑖. 𝑒. , 𝑃𝑖 (𝑖 = 𝑓𝑟𝑔𝑚 , 𝑓𝑚𝑎𝑚 , 𝑓𝑐𝑜𝑚 , 𝑓𝑝𝑟𝑚 , 𝑓𝑝𝑏𝑚 , 𝑓𝑟𝑒𝑚 )] regarding the constructs of the ACM are

further normalized through the weighted functions to compute for the ultimate fuzzy evaluation matrix

of the overall effectiveness index of the anti-corruption measures. The individual MFs of the constructs

forming the fuzzy matrix are presented in Table 8.14 (fourth column).

Table 8.14: Membership Functions (MFs) at ACM Level 2 and 1

No ACM Constructs Weighting MF for Level 2 MF for Level 1

1 Regulatory Measures 0.116 0.02,0.04, 0.26, 0.58, 0.11 0.02, 0.04, 0.29, 0.52, 0.13
2 Managerial Measures 0.189 0.01, 0.06, 0.35, 0.40, 0.17
3 Compliance Measures 0.116 0.01, 0.03, 0.35, 0.47, 0.15
4 Promotional Measures 0.227 0.02, 0.05, 0.29, 0.53, 0.10
5 Probing Measures 0.199 0.01, 0.02, 0.24, 0.59, 0.13
6 Reactive Measures 0.153 0.02, 0.06, 0.26, 0.53, 0.12

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𝑃𝑓𝑟𝑔𝑚
0.02 0.04 0.26 0.58 0.11
|𝑃𝑓𝑚𝑎𝑚 | 0.01 0.06 0.35 0.40 0.17
𝑃𝑓𝑐𝑜𝑚 |0.01 0.03 0.35 0.47 0.15|
𝑅̅(𝑜𝑒𝑖) = 𝑃 =
𝑓𝑝𝑟𝑚 |0.02 0.05 0.29 0.53 0.10|
| 𝑃𝑓 | 0.01 0.02 0.24 0.59 0.13
𝑝𝑏𝑚
𝑃 0.02 0.06 0.26 0.53 0.12
𝑓𝑟𝑒𝑚

Moreover, given the weighted functions of the constructs as 𝑌̅ = (0.116, 0.189, 0.116, 0.227, 0.199,

0.153), the overall ACM effectiveness of the final evaluation matrix is computed through equation (9)

as presented below:

0.116 0.02 0.04 0.26 0.58 0.11

0.189 0.01 0.06 0.35 0.40 0.17
|0.116| |0.01 0.03 0.35 0.47 0.15|
𝑃̅(𝑜𝑒𝑖) = 𝑌̅(𝑜𝑒𝑖) ●𝑅̅(𝑜𝑒𝑖) ≈ × =
|0.227| |0.02 0.05 0.29 0.53 0.10|
0.199 0.01 0.02 0.24 0.59 0.13
0.153 0.02 0.06 0.26 0.53 0.12

(0.02, 0.04, 0.29, 0.52, 0.13)

Lastly, the overall effectiveness index of ACM employed to extirpate the proliferation of corrupt

practices in both the procurement and management of infrastructure works in the context of HK are

presented below:

𝐴𝐶𝑀𝑜𝑒𝑖 = [(0.02 × 1) + (0.04 × 2) + (0.29 × 3) + (0.52 × 4) + (0.13 × 5)] = 3.70 (effective).

8.5.4 Discussions

Thee individual variables formed the basis to estimate the effectiveness index (EI) for the constructs,

which are as well computer to arrive at the overall effectiveness index. Per the results from the survey,

the overall effectiveness index generated from the fuzzy synthetic evaluation technique was 3.70, which

indicates that anti-corruption measures stipulated to guide the procurement, execution, management,

and realization of infrastructure projects are generally effective. The succeeding sections detail the

performance of the individual anti-corruption measures and their contributions towards the respective

constructs. The constructs are presented in order of their thematic underpinnings guided by the ICAC’s

three-pronged approach. They are prevention, education, and enforcement (ICAC, 2018). Fig. 8.8,

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therefore, presents a summary of the thematic representations of the ACM constructs based on the

ICAC model.

Figure 8.8: Thematic representation of ACM constructs

8.5.4.1 Overview of Hong Kong’s Anti-Corruption Institution

The Independent Commission Against Corruption (ICAC) of HK is the institution responsible for

enforcing and ensuring the effectiveness of anti-corruption measures in Hong Kong (ICAC 2018; Gong

et al. 2015). The institution is made up of 3 effective divisions is with unique responsibilities. They are:

1) the operations department which constitutes the investigative branch of the institution (that is,

responsible for conducting investigations right from when cases are received to the closing of cases);

2) the corruption prevention department, responsible for examining the actions and procedures of public

institutions and government departments to safeguard any activity that may be susceptible to the

incidence of corruption and lastly 3) the community relations department responsible for educating the

general public against the incidence and the woes of corrupt practices. With the functionality of the

departments carefully delineated, the efficacy of the three-pronged approach encompassed within the

three respective departments (that is, law enforcement, prevention, and education) is always on the

ascendancy. The section of the study explicates the results of the anti-corruption constructs based on

the thematic underpinnings of the three-pronged approach by the three departments of ICAC.

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8.5.4.2 Corruption Prevention

The constructs captured under this theme encapsulates regulatory measures (RGM), managerial

measures, and compliance measures. RGM was identified to be the second leading construct with an

effectiveness index of 3.72. Also, all the individual variables were revealed to be effective, per the

responses of the experts. The individual measures that make up the RGM construct are: comprehensive

rules and regulations with an EI of 3.84, development of strong political and ethical will to enforce

existing anti-corruption laws and policies (Powell 2006; Shakantu 2006) with a mean value of 3.76,

and the development and enforcement of ethical codes to guide the procurement execution and

management of infrastructure projects (Tabish and Jha 2012; Sohail and Cavil 2006) with a mean value

of 3.55.

Per the definition of regulatory measures which connotes statutory measures (i.e., acts, decrees and

laws), as well as regulation, it is stipulated to guide public institutions in order to limit the proliferation

of corrupt acts as well as public parties and project parties from getting involved in corrupt acts (Owusu

et al. 2018). The RGM construct is technically and thematically observed to be skewed towards the

stipulations of the corruption prevention department CPD (ICAC 2018). According to Owusu et al.

(2019), preventive measures, which are as well regarded as proactive measures enforced to prevent

corrupt acts from happening typically in the procurement and management of infrastructure projects,

should be structured to prevent the incidents of corruption. Also, it is needed to create an atmosphere

of a corrupt-free environment that encourages the right thing to be done even when exposed to

corruption.

Managerial Measures The next preventive construct that succeeds both the regulatory and Compliance

measures is the managerial construct. As the heading implies, the managerial measures are defined to

be proactive administrative measures stipulated to effectively guide in the modus operandi of the

internal structures of public departments or private sector towards the prevention and extirpation of

corrupt practices (Owusu et al. 2018). Per the analysis conducted, the construct was ranked fourth with

an overall effectiveness index of 3.65. However, unlike the preceding constructs discussed, the

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managerial construct encapsulates five variables of which three are regarded effective, and the

remaining two identified to be moderately effective. The first three effective measures are transparency

mechanism with Eileen index of 4.18, increase in institutional accountability with a main index of 3.63,

and ensuring the disclosure of vital information that a house is transparency, such as financial disclosure

with a mean index of 3.58. Among these variables, transparency mechanism was not only realized as

the leading variable within this construct but also among the total twenty-six anti-corruption measures

analyzed. The Assurance of transparency in public projects as well as within the public department has

been recognized as one of the key strongholds of any society or institution that is less prone to the

incidences of corrupt practices (Boyd and Padilla 2009; Ling et al. 2014).

For instance, according to the study of Kenny (2012), the incessant exposure of contractual and

implementation details was identified to be part of the key means of enhancing project transparency.

Similar to the transparency mechanism, the remaining two effective measures (i.e., increase in

accountability as well as the disclosure of relevant information such as financial standings and all

relevant tender information to potential bidders among others) are geared towards creating an

atmosphere of transparency, thus limiting the manifestation and proliferation of corrupt acts (Bowen et

al. 2012; Tabish and Jha 2011). Even though good leadership and professional associations were

identified to be moderately effective, other managerial structures stipulated to limit the incidence of

corrupt practices may include strengthening of professional bodies and creating a system of checks and

balances. That is, creating an environment where the works of each department in the public sector

domain or the private institutions could be checked during the expending and executing of their

respective departmental duties (Zou 2006; Brown and Loosemore 2015).

Compliance Measures Compliance measures, on the other hand, are stipulated to either encourage the

adherence to contractual requirements and regulations binding a project. As a preventive tool, the aim

of compliance measures seeks to obtain either full adherence or concordance as well as limit the attitude

of non-compliance, less compliance, or even partial compliance (Worthy et al. 2017). Also, with an

effectiveness index of 3.72, similar to that of regulatory measures, the variables captured under these

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constructs were identified to be effective. They include stipulations such as compliance to fairness and

transparent procedures, with a mean value of 3.84, compliance to contractual requirements with a mean

value of 3.79, and the compliance to procedural stipulations being the least but effective variable with

a mean value of 3.53. According to Owusu et al. (2018), other measures captured under this construct

include compliance to code of conduct as well as professional standards which are protected with other

reactive measures discuss later in this section (Powell 2006; Sohail and Cavill 2008; de Jong et al.

2009). According to TI (2018), one of the primary factors that differentiate corrupt cities and societies

from less corrupt societies hangs on the drive of parties to adhere to stipulations laws and regulations.

For instance, according to Le et al. (2014), flawed regulation system contributes heavily to the causal

instigators of corruption in the Chinese infrastructure projects. This evolves as a result of non-adherence

to their stipulated laws and regulations. Similar cases are reported in developing countries, including

India (Tabish and Jha 2012) Zambia (Sichombo et al. 2009) and Ghana (Ameyaw et al. 2017) among

other developing countries.

Contrastingly, in developed cities such as HK, the respondents are of the view that HK has attained an

appreciable level of cleanliness regarding the level of corruption in the city as a result of effective

compliance measures. Owusu et al. (2018) reported that it is one thing to develop and enforce ACMs,

and it is another thing to ensure concordance from the side of the parties to which the laws and

regulations affect. The needed input from both scholars and industrial practitioners would be to

strategize effective means of creating working environments that ensure full compliance.

8.5.4.3 Education

Promotional Measures (PRM) was the lone construct captured under this theme. The PRM construct

was the least ranked construct among the six constructs under investigation. Promotional measures are

classified as publicity mechanisms employed to propagate and extend the knowledge and information

on corruption (that is, their occurrence, consequences, and resolute measures) to a specific class of

people or the general public (Owusu et al. 2018). In effect, they are stipulated to inform the recipient

of the information, especially in the public domain about proactive measures (I.e., managerial,

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compliance and probing measures) and their effect on work processes as well as their influence on the

public institutions. With an overall construct EI of 3.64, the promotional construct was as well identified

to be effective within the context of Hong Kong procurement processes. There are six variables

captured under this construct, which makes it the construct with most measures. The variables captured

under the promotional measures construct were: 1) education, which was ranked first with an MI of

3.76, training and development initiatives as well as raising awareness each with equal MI of 3.74, the

use of information technology not only to enhance transparency through e-government and e-

procurement but also to publicize information on corruption and encourage whistleblowing mechanism

as it is one of the platforms for submitting complaints (Stansbury 2009; Søreide 2002; Ameyaw et al.

2017; Neupane 2014).

The use of Information technology was ranked fourth under this contract with an EI of 3.61 and the

remaining two, which are access to information and enhance communication coming fifth and sixth

position with respective me indexes of 3.55 and 3.42. Therefore, among all the six measures, the only

variable that needs effort in addressing to make it more effective is the communication enhancement.

Whether between departments of public sectors, parties associated with a project or publicizing

stipulated proactive and reactive measures to the general public. For instance, in HK, the Department

of community relations of the ICAC that's responsible for executing promotional measures, especially

in the form of public education, raising awareness and conducting periodic training to keep the

information on corruption well spread.

According to the institution, the department is responsible for encouraging the adoption of an "ethics

for all" attitude to relay tailor-made and context-oriented proactive educational programs for different

target groups to advance the integration of personal contact and media publicity among other effective

strategies. As opined in the previous section about the importance of reactive measures, equal attention

is needed to advance the course of promotional measures. Moreover, per the study of Owusu et al.

(2019), the development and enforcement of anti-corruption frameworks without careful consideration

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on how to adequately publicize, educate, raise awareness and conduct periodic training to keep

informants up to date may limit the enforced measures from experiencing their full potency.

8.5.4.4 Enforcement

Two constructs were captured under this theme. They are: 1) probing measures and 2) reactive

measures. To probe simply means to search into, examine, or investigate (Cambridge Dictionary 2018).

The probing construct, also termed as the investigative construct are stipulated to ensure effective

investigations and also monitor the processes involved in infrastructure procurement to deter project

parties from engaging in corrupt acts (Suen et al. 2007; Ameyaw et al. 2017). This construct was

however, identified to be the most effective category amount the six constructs with an EI of 3.81. In

descending order of effectiveness, the measures captured under this contract include conducting regular

supervision and technical auditing from time to time with equal mean indexes of 3.92 (Zhang et al.

2016; Søreide 2002); monitoring of contract (Sohail and Cavil 2006; Kenny 2012), setting up an

efficient reporting system and whistleblowing mechanisms with your respective mean indexes of 3.87,

2.68, and 3.66.

As the most effective anti-corruption construct, the modus operandi of the probing techniques

determines how successful a suspected corruption case may turn out (Wai 2006). The ICAC of Hong

Kong has indicated the importance of the investigation processes. Thus, it follows a very stringent

procedure every reported case goes through right from when the case is reported through to its closure.

According to Wai (2006), even though similar importance is placed on all three-pronged measures (i.e.,

deterrence prevention and education), greater emphasis is placed on 'deterrence' that is, the main

activity of the operations department. The evidence is seen in the devotion of over 70% of ICACs

resources channeled to the operations department. This perhaps demonstrates how the respondents see

the variables within the probing constructs to be the most effective measures, among others.

Reactive Measures was revealed to be the fifth most relevant anti-corruption construct with an overall

construct EI of 3.68, indicating the effectiveness of the construct. Unlike proactive measures, reactive

measures are control mechanisms stipulated to render Justice to offenders all corrupt parties and deter

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them from subsequent involvement in a corrupt act (Owusu et al. 2018). Therefore, at any given

moment where proactive measures are infringed upon, there is the need to apply reactive measures to

ensure an incessant atmosphere of a corrupt-free environment. The construct encapsulate measures

which are; 1) offering harsh punishment to culprits (with an MI of 4.11 being the most effective variable

under this construct and the second most effective among the overall 26 measures); 2) dismissal from

unemployment in other disciplinary action (with an MI of 3.61) which may not be regarded as a harsh

punishment such as life imprisonment depending on the case at hand and the act of promoting

debarment procedures (Stansbury 2009; Ameyaw et al. 2017).

A typical instance of rendering a debarment procedure may occur in the case of the procurement

process, where certain builders are exempted from submitting tenders due to previous cases of

involvement in corrupt acts. Debarment procedures are effective reactive tools that are set to deter

parties from corrupt at knowing that there is a higher consequence of being exempted from future

opportunities (Williams 2007). Again, per the departmental obligations of the ICAC, the operations

department is solely responsible for rendering reactive measures and charges mentioned earlier.

According to the study of Owusu et al. (2018), no matter how active and effective proactive and

promotional measures are, the absence of stringent and effective reactive measures has the capacity to

reader institutions and processes to the susceptibility of corrupt acts. Therefore, similar to the relevance

of both promotional and managerial measures, the importance of this construct demonstrates the

interconnectedness of the constructs developed. Thus, one construct cannot fully stand without

engaging the full potency another. Lastly, reactive measures are known to send a strong deterring

message if rendered to corrupt public officials.

8.5.5 Concluding remarks

This section of the study examined the effectiveness of anti-corruption measures in the developed

contest using the FSE technique. The purposive sampling approach was adopted to arrive at 38 experts

involved in the procurement and management processes of infrastructure projects. The experts were

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requested to evaluate the effectiveness of 26 unique anti-corruption measures categorized under the

constructs namely probing measures, regulatory measures, compliance measures, managerial measures,

reactive measures, and promotional measures (Owusu et al. 2018).

Per the results obtained from the application of the FSE technique, the overall effectiveness Index of

anti-corruption measures generated was 3.70, which indicates that anti-corruption measures guiding the

procurement, execution, and management of infrastructure works in the developed regions (particularly

in HK) are generally effective. Moreover, all the six constructs captured in this section were as well

identified to be effective with their respective mean values ranging from 3.81 (i.e., probing measures,

being the highest ranked variable) to 3.64 (promotional measures obtaining the lowest index even

though noted as effective). Regarding the effectiveness of the individual variables, the top five measures

that were identified to be effective were transparency mechanism, harsh punishment, rigorous

supervision, and technical auditing and, monitoring contractual performance.

Moreover, the six categories were further structured under the three-pronged approach developed by

HK to tackle corruption as well as the three departments responsible for executing the respective tasks

based on the thematic underpinnings of the constructs. This three-pronged approach has been identified

not only in scholarly works but also in international reports as one of the most successful anti-corruption

models in the world presently. They are deterrence, prevention, and education. Therefore, whereas

probing and reactive measures were identified to be functions associated with the operations department

(deterrence), promotional areas were identified to be related functions of the community relations

department (education). Lastly, the remaining three constructs, namely, regulatory, compliance, and

administrative measures, were captured under the functions of the corruption prevention department

(prevention). As a successful model, it is noted that even though these departments stem from one unit,

(that is, the ICAC) they are however structured in the format where the functions are executed

'department-wise' and to their full effect to enhance transparency and limit the proliferation of corrupt

acts. Moreover, as an exemplary model, the departmentalization of the six constructs captured in this

section of the study may inform other corrupt institutions and countries on how to strategically enforce

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the variables captured under the constructs by the required specialties (i.e., by their respective division

of labor).

8.6 Chapter Summary

Following the empirical examination of the negative constructs this chapter conducted a comparative

examination of the constructs of corruption, particularly focusing on the effectiveness of anti-corruption

measures and the negative factors that hamper the effectiveness of anti-corruption measures. This

comparative analysis was concluded to determine the contextual disparities between the developed and

developing contexts given the general notion that anti-corruption stipulations in the developed context

are more effective as compared to that of the developing countries. Thus, this chapter first tested the

validity of the established supposition and also tested for the effectiveness of the individual variables

against the negative constructs of corruption. After realizing that most of the variables were either

neutrally effective or less effective, a common theme that emerged from further exploration

encapsulated the barriers (i.e., factors) that hampered the effectiveness of anti-corruption. As a result,

the variables captured under this construct were examined to ascertain their individual criticalities and

their relational impacts on the effectiveness of anti-corruption measures. Following the examination of

all the variables in relation to the procurement process, a further assessment of the effectiveness of the

anti-corruption measures was conducted, specifically using Hong Kong as an exemplary case model.

All the constructs were examined within the context of Hong Kong and were identified to be effective

justifying the selection of HK as an exemplary context for other countries can learn from.

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CHAPTER 9 – DEVELOPING THE DYNAMIC FRAMEWORK 15

9.1 Introduction
This section examines the impacts of the negative constructs of corruption on the procurement process

of infrastructure projects. In all cases, the criticalities of the variables encapsulated within the negative

constructs were examined in relation to their impacts on the procurement process. Eleven activities

within the procurement process were revealed to have been significantly impacted by overarching

variables of the negative constructs. However, only seven activities were noted in the case of the forms.

The results reveal the dynamic nature of the variables that instigates corruption within the procurement

process. Thus, given the dynamic nature of the variables captured under the negative constructs coupled

with the high complexities of the procurement process, this study further examined these two critical

issues regarding corruption within the procurement process.

This section contributes to the scholarship on understanding the dynamism of the constructs of

corruption and their impacts on the complex process of infrastructure procurement. Moreover, the

developed dynamic model contributes significantly not only to facilitate the decision-making process

regarding policies but also offers an in-depth understanding on the relational interactions of the

constructs of corruption and how they can be mitigated, and the established anti-corruption measures

enforced. Practically, it provides valuable information on how to dynamically mitigate or extirpate the

criticalities associated with the negative constructs of corruption and improve the efficacy of anti-

corruption measures.

15
This chapter is fully or partially published in the following journal article: Owusu, E.K., Chan A.P.C. (2020).
Extirpating Corruption in Urban Infrastructure Procurement: The Dynamic Criticalities and the Way Forward.
Cities (Manuscript ID: JCIT_2019_1839
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9.1.1 SD Model development - A ‘corrupt free’ procurement SD model

System Dynamics was first introduced by Forrester in 1958 using computer simulation and feedback

control theory to facilitate the quantitative analysis or simulations of complex structures or systems.

System Dynamics has been widely used as a multidisciplinary simulation tool in project management,

business, decision sciences, and construction management domains, among others. It is often employed

to analyze the Dynamics and complexities associated with projects (Khan et al. 2016). However, its

applicability to analyze corruption in projects has been recommended but rarely conducted or used. As

a standardized simulation tool, the SD is noted to facilitate the management of complex processes that

rely on feedback, communication, and the receipt of information (Ding et al. 2016).

Thus, the modeling process is highly dependable on the interactions among the variables captured in

the process. SD examines the holistic perspective of a system focusing on the given elements, construct

or the measurement items of that particular system at a time. Thus, it enables the examination of the

relational attributes between the components of a system and their behavior over time. Moreover, in

research, SD has been adapted to examine different topics ranging from productivity rework,

construction demolition, safety culture, and forensic project management, among others (Li et al. 2014).

The SD methodology is used in this study to examine the complexities of the procurement process and

the dynamism of the indicators of corruption. Thus, the application of the SD methodology in this study

is intended to facilitate the understanding of how the procurement process responds to the interactions

and the changes or the dynamic behavior of the negative constructs of corruption. Moreover, it is

employed to explicate the behavior of the procurement system under suggested propositions of the anti-

corruption strategies stipulated to mitigate corrupt practices within the procurement process. The SD
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modeling approach, therefore, helps to evaluate the relational feedback and the consequences of new

structures and new policies (Wang et al. 2018). Given the SD’s ability to evaluate the complexities

associated with the procurement process and the dynamism of the variables of the constructs, it was

considered the most suitable approach in conjunction with the network analysis approach to fulfill the

aim and the objectives underpinning this study. Aside from the network assessment of the impacts of

the negative constructs of corruption on the procurement process, this study develops an SD model to

facilitate the decision-making process on how the incidences and effects of corruption can be mitigated

and extirpated at the various stages of the procurement process.

At the same time, the model is intended to facilitate the enhancement of the effectiveness of anti-

corruption measures. The developed model can, therefore, reflect the quantitative demonstration of the

feedback between the activities noted under the procurement process and the measurement items

captured under the negative constructs of corrupt practices. While the SD methodology has wide

contexts of application, it is employed in this study to examine the behavior of the procurement system

under the influence of the dynamics of the negative constructs of corruption as well as that of the ACMs.

Figure 9.1: Theoretical relationships among the constructs Conceptual Framework

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9.1.2 Causal Loop Diagram (CLD) and conceptual model formulation

Corruption extirpation in this study is measured in two directions. They are: 1) reducing the incidence

and the impacts of the significant negative constructs of corruption practices and 2) increase the

effectiveness of the extant ACMs stipulated to check corruption within the procurement process. Thus,

the development of both the initial models are intended to reveal the significant variables captured under

1) the causal factors of corruption; 2) the irregularities or risk indicators of corruption; 3) the

effectiveness of anti-corruption measures and 4) the barriers that hamper the efficacy of anti-corruption

measures. Thus, apart from the construct of the ACM, the remaining constructs highlight the negative

constructs of corruption. As a result, two distinct constructs are discussed. Thus, the two loops

considered here are 1) the positive indicator (+) where the constructs of corruption are noted to

contribute or add to the incidence and accumulated impact of corruption and 2) the negative indicator

(-) where the variables of anti-corruption measures are noted to repeal the impacts and effects of

corruption. Simply put, the ACM construct, and its underlying variables contribute negatively to the

accumulated impact of corruption.

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 Chapter 9 – Developing the Dynamic Framework
<administrative
measures>
<compliance measures>
-
psychosocial-specific
causes
biased tender +
solicitation
<contract monitoring -
- + organizational
+ irregularities>
statutory specific specific causes
cause unfair tender <regulatory
+ evaluation + + project specific + +
- measures>
dishonest contract causes
award + + selecting an
+
<administrative unqualified contractor -
- + <biased tender falsified contract
measures> inaccurate final illegal approval of
solicitation> amendment necessary licenses and
+ audit + <contract monitoring
administrative specific ++ - permits
+ + + + irregularities>procedural
irregularities corruption + irregularities +
+ unjust progres + -
- + +
return of forged s payments - + + + +
loosed
- examination of compliance
performance bond deliveries
<regulatory or legal - - irregularities
-
- contract monitoring specific causes>
- - compliance
+ irregularities <regulatory or legal
measures
fictitious or probing measures specific causes>
regulatory or legal +
regulatory exaggerated claims -
specific causes -
measures -
- reactive measures +
- +
promotional
- measures + fear and insecurtiy
- - (barriers)
social political
barriers
-
+ administrative
administrative
<unfair tender barriers -
psycosocial + + measures
evaluation>
barriers
<corruption>

Figure 9.2: Causal Loop Diagram (CLD) of the constructs of corruption and the procurement process activities

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 Chapter 9 – Developing the Dynamic Framework
The positive loop commences with the contextual risk indicators of corruption. As highlighted earlier,

these risk indicators are not necessarily primary instigators of the causal factors of corruption but rather

they are context-specific threats that pose the potency of contributing to the causal factors of corruption

with time (Le et al. 2014a; Owusu et al. 2019). Thus, if left unchecked, they may contribute to the

factors that cause corruption in the given context. For instance, one of the critical contextual risk

indicators identified in this study was the likelihood of procurement board members not adhering to the

stipulations of the procurement act. Given the definition of the risk indicators and the causal factors of

corruption, not following the established act may not necessarily be induced by or underpinned by the

possibility of the board members corrupting the process. The action may be influenced by other factors

other than corruption. Thus, given the scenario above, the risk indicator mentioned may not directly

contribute to the incidence of corruption. However, depending on the criticality and the time frame

allowed for this risk to thrive without immediate application of the necessary corrective measures, this

risk indicator may create enough room for any related causal factor of corruption to be incubated and

lead to or allow corruption to occur with time.

Thus, in the design of the causal loop diagram, the first-hand construct of consideration are the

contextual risk indicators, which influence the incidence and criticalities of the causal factors of

corruption. The first relationship established is that of the risk indicators leading to the causal factors

of corruption (Le et al. 2014; Owusu et al. 2019). The causal factors (otherwise known as the causes of

corruption) are considered as the main instigators or direct propellers of corruption in the given context

(Zhang et al. 2016; Zou 2006). As a result, while the risk indicators are considered to have a direct

positive influence on the causal factors, the causal factors, in turn, contribute to the main incidence of

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corruption within the different activities of the procurement process. However, as the causal factors

continue to contribute to the accumulated level of corruption in a given context, there are anti-corruption

strategies proposed or established to mitigate both the causal factors and the accumulated level of

corruption (Shan et al. 2015; Smith 2009; Ameyaw et al. 2017). The ACMs are, therefore, considered

to have a negative influence on the causal factors of corruption, the accumulated level and impact of

corruption and the risk indicators of corruption within the procurement process (Le et al. 2014a). The

influence of the ACMs on the negative constructs of corruption is therefore represented with the

negative notation sign (-).

Moreover, while the ACMs are designed to mitigate the overall level of corruption in a given context,

extant literature revealed that some, if not most, of these ACMs struggle to achieve their full potency,

especially in the developing context. Owusu and Chan (2018) investigated this supposition and

identified 17 established factors reported to hamper the efficacy of anti-corruption measures. The level

of corruption in a given context is, therefore, not limited to only the causal factors and the risk indicators

but also the barriers that hamper the efficacy of ACMs. As a result, the barriers are classified or

considered as negative influencing variables (-) towards the ACMs in the CLD while they contribute

(+) to the overall level of corruption (Owusu and Chan 2018). Lastly, it must be emphasized that the

part of the CLD labeled corruption in Fig. 4 represent corruption in the procurement process. The

variables of the respective constructs are also indicated and represented by the respective rotational

notations depending on their contribution to the incidence or extirpation of corruption within the

procurement process.

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9.1.3 Stock-flow diagram (SLD)

Based on the CLD, the key significant measurement items or constructs that influence corruption within

the procurement process are identified. The CLD was developed and converted to a stock-flow diagram

with the help of an SD simulation software called Vensim. The stock-flow diagram is presented in Fig.

5. Yan et al. (2012) pointed out that to ensure the appropriate quantitative analysis to be conducted,

their respective index for each of the measurement items should be stipulated. The solicited data from

the experts were examined to ascertain the model's equations and parameters validity.

Before running the simulation, a series of tests were performed to check the validity of the model (Ding

et al. 2016; Senge 1990). The validity test is performed to ensure that the certainty and veracity of the

model typifies a true reflection or scenario of the real world (Richardson and Pugh 1981). The series of

tests performed to review and highlight the validity of the models are 1) the boundary adequacy test; 2)

parameter verification test; 3) dimension consistency test; 4) extreme condition test and 5) structure

verification test. All these tests were performed and successfully passed. An example of two of the tests

(i.e., structure verification test and the dimension consistency test) are explicated as follows.

The structure verification test measures the consistency of the model structure to the pertinent

descriptive knowledge proposed or developed a model system (Ding 2016; Marzouk and Azab 2014).

In response, all the variables, constructs, and information on the composition and the relational

attributes captured in the CLD or founded on a germane and comprehensive review of extant and

previous literature as well as the analysis of the data retrieved from the expert survey. Thus, the structure

of the model is family and logically rooted in the actual instances of the reported cases of corruption.

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Also, regarding the dimension consistency test, the software employed for this SD model development

and analysis (i.e., Vensim) contains an integrated measurement function which automatically examines

and verifies the recorded dimensions after the measurement units of all the variables have been defined.

The developed model has, therefore, been verified for its dimension consistency with the help of the

software.

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 Chapter 9 – Developing the Dynamic Framework

effective investigation, court procedural- compliance administrative-

proceedings, departmental irregularities professional
harsh punishment disciplinary action irregularities specific
dismissal from malfeasauce acts
or penalty contract monitoring bribery acts
employment debarment/promoting fair effects of risks to irregularities
debarment procedures corruption fraudulent acts
collusive acts
increasing accumulated favoritism acts
effects of reactive measures impacts of
compliance to fairness reactive impact of total amount of
taken for corruption measures
and transparent increase of risks risk corruption extortionary acts
reduction
procedures increasing rate of
the impact of statutory-specific
effects of compliance reactive rigorous technical corruption psychosocial-specific
accumulated causes
measures taken for impact of measures auditing system rigorous supervision causes
corruption reduction reactive the impact of
measures the impact of causes to organizational-specific
comtractual among others corruption
the impact of barriers whistle-blowing risk to causes
compliance the impact rate of
to anti-corruption barriers to anti-cor mechanism contract corruption monthly
the impact of measures
procedural ruption measures monitoring increase of
compliance measures causes
compliance accumulated
reduction of corruption increase of
effects of probing efficient reporting corruption the impact of causes
corruption
increasing measures taken for system accumulated of corruption
impacts of corruption reduction the impacts of impact of causes
compliance accumulated regulatory or
impacts of anti-corruption of corruption legal-specific
measures the impact of the impact changes of impacts of anti-corruption
measures measures project-specific causes
anti-corruption of probing anti-corruption measures
measures accumulated the impact rate of causes
accumulated measures impact of the impact of barriers
probing anti-corruption measures
impact of measures increasing impacts of to corruption
compliance socio-political
measures <monthly> the impact of probing measures barriers
regulatory measures the impact of
accumulated
the impact of accumulated promotional measures barriers to
impact of anti-corruption
administrative measures regulatory the impact rate of
increasing impacts of measures accumulated measures administrative
impact of barriers to corruption
regulatory measures barriers
promotional increasing impacts of
measures
accumulated promotional measures
impact of increasing barriers impacts of barriers to
administrative effects of regulatory
conduct anti-corruption
measures increasing impacts of measures taken for
effects of promotional measures psychosocial
administrative measures corruption reduction
measures taken for barriers
effects of administrative ethical code
corruption reduction access to
measures taken for comprehensive rules
corruption reduction and regulations development of strong political and information fear and insecurity
ethical willing to enfore existing raising awareness
transparency anti-corruption policies and laws training and
good leadership mechanism information enhance development initiatives
professional financial disclosure
associations education teconology communication
increase in
accountability

Figure 9.3: Stock flow diagram

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 Chapter 9 – Dynamic Framework Development

Following the simulation, a proposition of adjusting the significant variables under each context was

established to develop the best-case scenario of how the impact of corruption can be reduced, and the

individual anti-corruption measures enhanced. Unlike the negative variables that scored between the

range of 3.5 and 4.5 (i.e., critical), all the variables under the ACMs scored between the range of 2.5

and 3.5. This demonstrated that the overall effectiveness of the ACM construct was neutral. As a result,

the accumulated impact on the measures was relatively lower as compared to the criticality of the

variables under the negative constructs. This reemphasizes on the high criticality of corruption within

the developing context coupled with limited or neutral effectiveness of anti-corruption measures.

Moreover, similar to the proposed simulation run for the negative constructs where the criticality of the

significant variables was reduced by one (i.e., critical variables), the effectiveness indexes of the

significant ACMs were, in turn, increased by one. Given this scenario, if a significant variable scored

2.8 in its actual score, the proposed score was set to 3.8 (i.e., moving the variable from a neutral level

to a relatively effective level. These propositions were established to test whether the proposed

scenarios established under each context would have a significant positive outlook towards the

extirpation on accumulated corruption in the procurement process as well as the enhancement of the

efficacy of ACMs.

This proposition was made with the aim that when the needed efforts are expended on the critical

variables and constructs to the point where the significant negative variables can be reduced (i.e., either

from critical to neutral or from neutral to less critical), there will be a significant corresponding change

in the accumulated corruption. Similarly, if similar efforts are expended on the ACMs to result in a +1

of the significant ACMs (i.e., from either less effective to neutral or from neutral to effective), a

significant analogous output in the accumulated effectiveness of the ACMs would occur. The outcome

for the proposition made is intended to strengthen the notion or the proposition that the efforts towards

the mitigation and extirpation of corruption in infrastructure procurement should be strategic and

timely. Instead of paying attention to all the variables and other related constructs at the same time, a

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more focused effort can be expended on the few critical constructs and the most significant variables

in both cases (i.e., negative constructs of corruption and ACMs). This supposition can be grounded or

deduced from the simulation results obtained in this study, as the results indicated the innermost degrees

of difference in both the constructs. Whiles Fig. 6 presents the actual and the predicted output of the

accumulated corruption over a given timeframe, Fig. 7 also presents both the actual and the predicted

output of the accumulated ACMs.

Figure 9.4: Simulation results of actual and predictive accumulated corruption

Figures 6 and 7 show the accumulated impact of corruption and that of anti-corruption measures within

an estimated timeframe of 3 years or 36 months. The proposed or estimated boundary conditions are

established to highlight the degree of the criticality of the negative constructs of corruption as well as

the effectiveness of the anti-corruption measures as the month progresses from 0 to 36. It must be

emphasized that the accumulated impact of corruption highlights the overall effect of the constructs of

corruption. They include the total estimated criticalities of the forms of corruption, the causal factors

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of corruption, risk indicators or procurement irregularities, and the barriers that hamper the efficacy of

ACMs. As presented earlier, each of the constructs is made up of their respective underlying variables.

Given the actual simulated results, which indicated an accumulated corruption impact of over 22 degree

of criticality index, a proposition was made to reduce the critical variables by 1. The measurement

scales attributed to the measurement items were stipulated in a given range of 1 to 5, where 1

represented not critical, 5 = very critical, and the neutral point set at 3. For instance, using the construct

of the causal factors of corruption as an example, two out of the five established factors were identified

to be critical. They are Psychosocial-Specific Causes (PSSC) with a criticality index of 3.61 and

Statutory-Specific Causes (SCC) also with a criticality index of 3.58. Per the stipulated adjustable

requirement, the actual indexes of these two measurement items were reduced by 1 each. Thus, the

prosed CI for PSSC was adjusted to 2.61, and that of SCC was adjusted to 2.58.

The other three constructs remained unchanged since the emphasis was only on the critical and

significant measurement items. Similar adjustments were made to all the significant measurement items

of the remaining negative constructs. As a result, the actual situation of the accumulated corruption

within the context under study revealed an index of over 22.5 (red cumulative curve). On the other

hand, the proposed adjustment resulted in a significant drop-down of the accumulated impact of

corruption by over a difference of 15 to 7.5. The implication here is that a slight adjustment to any of

the significant constructs will result in a significant increase in the overall impact of the ACM.

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Figure 9.5: Simulation results of actual and predictive accumulated impacts of ACMs

Moreover, as established earlier, this study does not only focus on the mitigation of the accumulated

impacts of corruption but also the enhancement of the effectiveness of the ACMs. Thus, similar to the

propositions made to adjust the significant measurement items of the negative constructs, an adjustment

was made to the significant measurement items within the ACM construct in the context under study.

Given the same conditions for the simulation process of the negative constructs, a significant increase

in the accumulated effectiveness of the ACMs was noted. Whiles the red cumulative curve represents

the actual simulated effectiveness of the ACMs construct; the blue cumulative curve represents the

predictive outcome proposed simulated results. It can be established that the comparative dispositions

of the actual simulated results on both the accumulated corruption and the ACMs constructs show a

significantly disparate finding (i.e., the criticalities of the accumulated corruption impacts way beyond

that of the ACMs construct). This is unsurprising as most countries in the developing context, such as

Ghana are noted to have high criticality indexes of corruption coupled with either neutrally effective or

low effectiveness of existing ACMs (Transparency International 2019; Ameyaw et al. 2017).

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In essence, the implications of the results reveal that corruption in infrastructure procurement can be

mitigated or extirpated with time and strategic focus. That is, given that critical attention is expended

to the implementation and the application of the most significant ACMs, and the mitigation of the most

significant negative constructs prevalent in the procurement process. Thus, aside from the initial

propositions made, this study further contends that it may not be helpful to focus on all the underlying

constructs of corruption (i.e., both the negative constructs and the ACMs) in a corrupt-prone context,

all at once. Instead, critical considerations be given to the significant constructs captured under both

constructs at a given time. Once improvements are recorded, then it will be needful to consider other

less significant constructs. For instance, it is valid to propose in the context under study that out of the

5 constructs capture under the causal factors of corruption greater amount of efforts can be geared

towards PSSC and SSC. Similarly, regarding the irregularities, more attention can be diverted towards

administrative-specific and compliance irregularities. Similar efforts are required to be expended on

the other constructs to ensure a strategic fight against the incidences and effects of corruption in a given

context.

9.2 Anti-Corruption Framework: Ex-ante and Ex-post Classification

According to the study of Kaufmann (1997), whereas ex-post measures refer to curative measures, ex-

ante measures referred to as preventive measures. Owusu et al. (2019) categorize the measures into

three main constructs, namely proactive (or preventive) measures, promotional measures, and reactive

measures. Thus, per the descriptions of the classifications, ex-post measures are synonymous to reactive

measures, whereas ex-ante measures align with proactive and promotional measures. Other constructs

captured under the proactive measures include; administrative measures, regulatory measures, and

compliance measures.

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Figure 9.6: Anti-corruption constructs application within the procurement process

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From the findings, it was determined that none of the activities captured throughout the pre-contract

stage of infrastructure-related works to the post-contract stage is free from corruption. Simply put, when

it comes to the lifecycle of infrastructure projects, there are no specific boundaries within which the

extent and impacts of corrupt practices are limited. Thus, from the planning stage, which involves

critical decisions such as the size and the definition of the project's requirements to the post-contract

stage, corruption can show up at any time and within any of the stages. The extent to which corruption

is endemic at any of the stages underpins the stipulation of ACMs in both ex-ante and ex-post processes.

Figure 7 presents the applicability of the ACM constructs within the contexts of ex-ante and ex-post

processes. Anti-corruption frameworks or tools are argued to be ineffective or likely to be ineffective

if the framework does not encapsulate all the developed constructs captured under both ex-ante and ex-

post timelines. Over-reliance or excessive focus on ex-post measures at the expense of ex-ante will not

only cripple the framework but can create systemic loopholes that facilitate corrupt acts (Kaufmann

1997; Owusu and Chan 2019). However, an appropriate combination and application of measures

stipulated within the processes of ex-ante and ex-post is identified to be relatively effective.

9.3 Chapter Summary

The section sought to investigate two significant objectives on the subject of corruption in infrastructure

project procurement. Following the identification of the impacted activities, the study continued to

investigate how these impacts could be mitigated in the short-term or extirpated in the long-term run.

As a result, the SD approach was adopted to simulate the dynamic interactions between the negative

constructs of corruption, the procurement process, and the strategies established to mitigate corruption.

Using a proposed boundary condition for the application of the simulated results, the CLD (which

highlighted the suggested relational attributions of all the constructs) was initially developed. This was

done to facilitate the development of the stock-flow diagram and further analysis of the retrieved data.

All the relevant model validity and reliability tests were performed to authenticate the pre and post-

simulation results. The data used was solicited from 62 experts involved in the procurement process of

infrastructure works. The initial results revealed a gradual acceleration of the accumulated corruption
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impact derived from the collective impacts of the negative constructs of corruption. An analogous trend

was identified with the ACM constructs. However, the accumulated impact of the ACM construct was

revealed to be relatively lower even though it demonstrated a possible increase in its effectiveness over

time. A supposition was made envision a more realistic and best-case scenario for reducing the impact

of the accumulated corruption and increasing the effectiveness of the anti-corruption measures. That is,

the variables that were identified to be significant were adjusted and simulated. The simulated results

demonstrated revealed a drastic decline in the accumulated corruption impact as well as enhanced

accumulated effectiveness of the ACMs over the 36-month used for the simulation. While the results

provide a piece of very resourceful and valuable information on how to tackle corruption within the

procurement process of infrastructure works in the developing contest, the approaches used in this study

can be replicated in other contexts to demonstrate how corruption in different settings can be tackled.

Given that the analysis conducted in this study remains the first to examine and report on the dynamics

of corruption in infrastructure-related works, this study extends the body of knowledge on the subject

matter. Consequently, the developed models are intended to facilitate the decision-making process to

reduce or extirpate the impact and the effect of corruption within the procurement process and, at the

same time, increase the effectiveness of anti-corruption measures within the process. Thus, it offers

practical information to anti-corruption activists, project managers, procurement officers, supply chain

managers and researchers on a proposed mechanism for reducing the impact and the criticality of the

negative constructs of corruption and enhancing the anti-corruption measures and also reinforcing the

weak and corrupt-prone activities within the procurement process.

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9.4 Validation of Variables Constructs and Models

Research validation (RV) is regarded as the ultimate and one of the most significant stages of a research

study process (Hu et al. 2016). RV is mostly conducted to evaluate the acceptability and the credibility

of the research outputs and the models developed (Yang et al. 2010; Ameyaw et al. 2014). According

to Yeung (2007), the RV measures the suitability, reliability, practicality, objectivity, and the

appropriateness of the developed frameworks or systems). More specifically, RVs are performed to

examine the degree to which the generated outputs and the developed models fulfill or satisfy the needs

of the user or the consumer of the outputs and the models (Gupta 1991, Osei-Kyei and Chan 2015).

However, according to Sargent (1991), there are no specific criteria or stipulated procedures for

identifying specific RV techniques or tools for carrying out the RV process. This has been viewed as

one of the key challenges in RV. Thus, Law (2007) advocated that RV always relies on a study's specific

propose.

Owing to the definition postulated by Lucko and Rojas 2010), RV is concerned with or attributed to

doing the right thing, different from research verification, which is concerned with or attributed to doing

things right. RV, therefore, aims to ensure that all the individual procedures associated with the study's

methodology strictly/ rigorously conform to the most stringent quality standards to produce quality,

reliable and credible output acceptable by its final consumers. As such, the relevant measurement items

that RV considers are the accuracy, precision, adequacy, and the usability of a framework or a system.

While Yang et al. (2010) highlighted and explicated two approaches of RV (i.e., qualitative and

quantitative), Lucko and Rojas (2010) mentioned and explained six different forms of RV in CEM

research. They are criterion validity, construct validity, content validity, face validity, internal validity,

and external validity. In explicating the two approaches (i.e., qualitative and quantitative), Ameyaw

(2015) pointed out that the qualitative approach adopts a non- statistical technique such as opinion-

based data. Moreover, the quantitative approach adopts an objective and numerical - based data to test

for hypothesized correlations among measurement items. This study, however, adopted the qualitative

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method of validation since all the identified constructs and their underlying measurement items are

considered to be abstract items that are relatively difficult to quantitatively evaluate. Thus, conducting

an expert survey to gather opinion-based data was noted to be more appropriate as compared to the

other evaluation criteria. Experts from both Academia and the industry were invited to take part in the

survey. This was done via a face-to-face approach. The RV period lasted for eight consecutive weeks.

The backgrounds of the experts are presented below. Each section of the questionnaire was made up of

both open-ended and close-ended questions. All the developed close-ended questions were assessed

based on a five-point Likert scale. The biodata of the experts involved in the RV is presented in Table

9.1.

Table 9.1: Respondents’ Data

I/EV Sector Institution Position Years of

Experience

A. Public Millennium Development Senior Procurement Specialist 40 years

Authority

B. Public Kwame Nkrumah University Senior Lecturer, 35 years

of Science and Technology,
GhIS Fellow, Lead Director for
Ghana.
MSc. Procurement Program

C. Public Ghana Institute of Surveyors President 33 years

(GhIS)

D. Public Public Procurement Director, Compliance and 30 years

Authority Monitoring Evaluation

E. Public* Kwame Nkrumah University Head, Department of Building 25 years

of Science and Technology Technology

F. Private Moderntech Construction Technical Director 20 years

Ltd.

G. Public* KNUST Procurement Office Chief procurement officer 20 years

H. Private Construction Cost Consult Managing Director/Senior 15 years

Quantity Surveyor

I. Private Procurement and Project Procurement Manager 12 years

Management Consultancy
(PPMC) Ltd.

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J. Private* Deliren Construction Ltd. Chief Quantity Surveyor 11 years

K. Public Architectural and Deputy Quantity Surveyor 10 years

Engineering Services (AESL)

L. Public Architectural and Deputy Quantity Surveyor 10 years

Engineering Services (AESL)

Note: I/EV stands for Interviewee/ Expert validator; GhIS represents Ghana Institute of Surveyors

In all, a total of 12 experts were involved in the survey. With the minimum years of experience being

ten years, all the experts involved were identified to occupy senior position in their respective

institutions and sectors. Other criteria for selecting the experts were as follows: 1) involved in the

supply chain of infrastructure procurement and delivery in the Ghanaian context and 2) involved in the

contractual arrangements of projects and either witnessed or understands the dynamism of corruption

in infrastructure projects.

9.4.1 Validation Results

Six sets of questionnaires were developed and explored (via an expert survey) to highlight the

credibility and the outputs of the results generated (both as an individual or stand-alone constructs) and

towards the developments of the models. Thus, all the constructs and their relational attributions to the

developed models were examined. They include the forms of corruption and their associated causal

factors, the contextual risk indicators, extant anti-corruption measures, and the barriers that hamper the

efficacy of the measures. Lastly, the RV regarding susceptibility patterns of the procurement process

was conducted (Table 9.1). Thus, each of the six constructs highlighted represents a set of

questionnaires. The questions asked in relation to the constructs to determine their RV are presented in

Table 9.2.

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Table 9.2: Validation Results

No Constructs and their respective underlying measurement items Mean

Procurement Irregularities
P1 Are the 18 procurement irregularities established, critical in the Ghanaian
4.36
infrastructure procurement?
P2 Do the 18 procurement irregularities obscure the normal process of infrastructure
4.18
procurement in Ghana?
P3 Can the 18 procurement irregularities established, contribute or create room for
4.54
corruption to occur?
P4 Can the impact of their criticalities have adverse effects on the general economy? 4.55
P5 Are the probability and severity rankings of the identified irregularities
4.00
reasonable?

Forms of Corruption
F1 Are the 27 forms of corruption prevalent in the process of infrastructure
4.54
procurement in Ghana?
F2 Can the 27 forms established contribute to the forms of corruption in the
4.46
procurement sector?
F3 Are the 27 forms of corruption established, critical in the Ghanaian infrastructure
4.36
procurement?
F4 Do the impacts of their criticalities have adverse effects on the procurement sector
4.54
and the general economy?
F5 Are the rankings of the identified forms reasonable? 4.27

Causes of Corruption
C1 Are the 38 causes of corruption established, critical in the Ghanaian infrastructure
4.46
procurement towards the incidence of corruption?
C2 Do the 38 causes of corruption obscure the normal process of infrastructure
4.55
procurement in Ghana?
C3 Can the 38 causes of corruption established contribute or create room for
4.54
corruption to occur?
C4 Are the rankings of the identified causes reasonable? 4.46

Anti-Corruption Measures
A1 Are the 26 anti-corruption measures established, important towards the eradication
4.18
of corruption in the Ghanaian infrastructure procurement?
A2 Are all 26 anti-corruption measures moderately effective in the procurement
3.91
process as rated by the respondents?
A3 Can the 26 anti-corruption measures established contribute or create transparency
4.27
and accountability in the procurement process?
A4 Can the impact of their effectiveness contribute to the good image of the public
4.45
procurement sector and the general economy?
A5 Are the rankings of the identified measures reasonable? 4.00

Barriers Against the Efficacy of Anti-Corruption Measures

B1 Are the 17 barriers established, critical in the Ghanaian infrastructure
4.50
procurement?
B2 Do the 17 barriers impede the effective application of and enforcement of anti-
4.27
corruption measures in the procurement process in Ghana?
B3 Can the 17 barriers established contribute or create room for corruption to occur? 4.09
B4 Can the impact of their criticalities have adverse effects on the general economy? 4.40
B5 Are the rankings of the identified barriers reasonable? 4.20
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The questions presented in Table 9.2 are developed to support or justify the individual measurement

items and their respective constructs in the development of the fuzzy model, the PLS-SEM model, and

the System Dynamics model. As such, the questions were posed to determine the following sub-

questions: Construct validity measures the degree to which the measurement items within a specific

construct measure or address the theoretical domains of the actual construct it claims to measure

(Ameyaw 2015). Thus, in this study, a typical question, posited to measure this RV is demonstrated as:

Are the measurement items and their respective constructs appropriate for the development of the

models? In all cases, the experts demonstrated that the measurement items within their respective

constructs adequately measure the actual construct they claim to measure. For instance, taking the forms

of corruption as an example, do the underlying constructs such as bribery acts, collusive acts,

discriminatory acts among the other forms adequately measure the construct of the forms of corruption.

These questions (on the model) in harmony with the underlying contracts and the measurement items

were posed to determine five out of the six mentioned types of RV. The five are 1) Content validity, 2)

face validity, 3) external validity, 4) internal validity and 5) construct validity.

In explicating the individual types of validity, Lucko and Rojas (2010) pointed out that the first type,

which is the content validity, represents a non - statistical technique that examines the fair

representation of the output to reality. Simply put, does the study's content fairly reflect or represents

the actual case in real life. At this stage, the key focus is the degree to which all the underlying

measurement items with their respective constructs can facilitate or contribute towards the

enhancement of the established ACMs and the curtailment accumulated corruption on the procurement

process provided that they are strategically enforced with continual attention (Ameyaw and 2015;

Babbie 1990). A typical question posed to evaluate this type of RV is: Can the respective measurement

items with their established constructs and the developed models contribute or create room for

corruption to occur? (P3). In all cases, the experts revealed or highlighted the validity of the

measurement items in terms of the content with the score of each question obtaining an MS of more

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than 4.00, Which means very good (Fig. 9.6). Similar to content validity, face validity is a subjective

non-statistical technique that gathers subjective data from experts to evaluate a study's validity. Face

validity measures the level of agreement between the generated output of the study and the experts'

consent of the results in tandem with practice. Thus, in a nutshell, the face validity reveals whether the

expert's assessment on a given list of measurement items agrees with what happens in real practice.

Examples of the questions posed to address this type of RV are as follows: Are the 18 procurement

irregularities established, critical in the Ghanaian infrastructure procurement? – Are the developed

models effecitive to be employed or facilitate decision making? (P2). Again, the results generated

among all the constructs were revealed to be greater than 3.5, which indicates good (Fig.9.6).

Next, internal validity measures the appropriateness of a study and also the extent to which the

generated outputs are free from errors. Thus, this particular type of RV examines the logic of the

procedures adopted to arrive at the final output (Lucko and Rojas 2010). Questions regarding the

internal validity included: 1) are the models developed easy to understand? 2) Is the model outputs

logical? 3) are the steps adapted to arrive at the final model, logical to the extent that other practitioners

or experts can replicate it? (P4). With the MS identified to be greater than 4.0, the results reflect the

appropriateness of the study or the confirmation of the logic to arrive at the established outputs.

Lastly, external validity shows how a research study's output can be generalized for prediction or

forecast purposes (Ameyaw 2015; Leedy and Ormrod 2001). Thus, since this type of RV interrogates

whether the results generated from a study can be generalized to the general population, one of the key

measuring items for estimating the index for this indicator is to ensure that the respondents selected for

the RV will yield representativeness (Osei-Kyei 2017). In this study, the questions posed on the

reasonability of the lists' rankings are developed to test the external validity of the established

measurement items and their respective constructs towards the development of the models. Another

typical question is as follows – Is the overall output of the model suitable to contribute to the efficacy

of anti-corruption measures and lead to a decline in the overall impact of corrupt practice in the

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procurement process? (P5 in Fig. 9.6). The acceptable limits of the mean score used to measure all the

types of R V in all the cases were given to be 3.5 to 5, which represents very good to excellent. Figure

9.2 typically reveals how all the measurement items used to measure the different forms or types of the

RV fall within the acceptable stipulated range.

P1
5

4.5

Procurement Irregularities
4
P5 P2 Forms of Corruption
3.5

Causes of Corruption
3

Anti-Corruption Measures

Barriers Against the Efficacy

of Anti-Corruption Measures

P4 P3

Figure 9.6: Graphical representations of the constructs contributions towards the models’ validity

9.5 Chapter Summary

This chapter presented the dynamic framework highlighting the interactions of the various constructs

of corruption and their accumulated impact on the procurement process. Thus, while the expert survey

revealed the accumulated impacts of the current criticalities of the corruption constructs on the

procurement process, a proposition of slight adjustments to the significant constructs captured were

made to determine the responsive changes to the adjustments made. The model revealed and confirmed

that efforts taken to produce either a fair or the slight changes to the significant constructs could cause

a very significant increase in the effectiveness of the anti-corruption measure and a significant decline

to the accumulated impacts of corruption on the procurement process over a fairly appreciable amount

of time. The results reflect the ideology underpinning the Pareto's principle. (i.e., 80/20 rule). That is,

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efforts taken to implement the 20% slight adjustments on the constructs can reflect /cause a significant

80% output in the changes needed.

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CHAPTER 10 – CONCLUSIONS AND RECOMMENDATIONS

10.1 Introduction

This chapter concludes this research. While the topic of corruption is noted to be an unending

phenomenon, this research targeted to contribute to corruption-related studies within the domains of

project management and construction management. Thus, while the significance of each section and

chapter of this research had been explicitly indicated at the respective sections and chapters, this chapter

presents the overall contribution of this research to the related scholarships. The practical implications

for the industry are further detailed out in the chapter. Lastly, the research limitations, in addition to the

recommendations for future research, are presented in this chapter. The next section of this chapter

presents the review of the aim and accompanying objectives of this research.

10.2 Review of the Research aim and objectives and their significance

The aim is to explore the dynamism of corruption in public project procurement in the developing and

the developed contexts, however, placing more emphasis on the developing context and to develop a

soft computing model to predict and evaluate the corruption within the procurement process and

propose an overarching dynamic framework potent and resilient enough to extirpate and resist

respectively, the negative constructs of corruption within the procurement process.

1. Examine the forms of corrupt practices and their respective causes that auger the practices of

corruption in public infrastructure procurement;

2. Examine the procurement irregularities in the developing context;

3. Establish the stages in procurement and their susceptibility to corruption with respective

strategic measures to curb its incidence;

4. Investigate the effectiveness and the barriers to effectiveness of the anti-corruption measures;

5. Develop a dynamic overarching model to mitigate corrupt practices in public procurement.

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The main aim, including the individual objective, was achieved using appropriate methods and

techniques explained in Chapter 2. The methods include but not limited to, expert surveys and

interviews, literature reviews, and document (A-G reports and ICAC reports) analysis. The succeeding

sections present the major findings and conclusions for every objective. This study is one of the first

empirical studies to comprehensively examine all the constructs of corruption within the procurement

process. This study contributes significantly not only to the body of knowledge the corruption-related

studies but also a practical contribution towards the effective development of focused anti-corruption

measures. Particularly, the findings of each of the stipulated objectives offer very useful and practical

implications towards the extirpation of corruption in the developing world, especially in Ghana.

Objective 1: Examine the forms of corrupt practices and their respective causes that auger the

practices of corruption in public infrastructure procurement

A comprehensive review was conducted to identify the prevailing forms of corrupt practices and their

associated causal factors in infrastructure projects. In all, twenty-eight forms were identified. However,

twenty-seven were noted as applicable in the Ghana context. Over forty-four factors on causes of

corruption were as well identified in a review study conducted to identify the prevailing causal factors

behind the criticality of the forms. First, the identified forms were clustered under five categorical

constructs, namely; bribery acts, fraudulent acts, collusive acts, discriminatory acts, and extortionary

acts. An additional construct labeled unclassified acts. Per the review, the most discussed constructs in

descending order were fraudulent acts, bribery, and discriminatory acts. An empirical analysis

regarding the forms was conducted to 1) identify the criticalities of the individual forms of corruption

in infrastructure projects. 2) assess the impact of the forms of corruption on the procurement process

of infrastructure works and the criticality of the constructs at the various stages and activities captured

under the procurement process.

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The findings revealed that bribery acts' construct and professional malfeasance acts (initially labeled as

the unclassified construct) and collusive acts were noted as the leading constructs of CFs in

infrastructure projects. Results regarding their criticalities within the procurement stages and their

respective activities were conducted in a comparatively. Thus, a contextual comparative analysis was

conducted between the results of the developing context and that of the developed. For instance, from

the developing context, bribery and collusive acts dominated the critical activities such as PCS4, PCS6

CTS2 and CTS3. Others, similar results, were identified in the developed context as well but at different

stages PCS2, PCS3, CTS1, and PCP3. The construct known as unclassified acts was named after the

empirical survey and analysis based on the definitions and attributes of the underlying variables.

The second section of this objective dealt with the causal factors of corruption. Sub exploration included

their criticality in infrastructure projects and of their overall impact on the individual stages and

activities of the procurement process. As mentioned, forty-four causal factors were identified via a

comprehensive literature review. Among these factors, some of the most discussed included poor

professional, ethical standards, overdose relationships, and negative working conditions. Similar to the

forms, the causal factors were captured under five categorical constructs, namely, regulatory or legal-

specific causes (RSC), statutory-specific causes (SSC), psychosocial-specific causes (PSSC),

organizational-specific courses (OSC) and project-specific causes (PSC). Among the forty-four

variables, 38 variables were noted as applicable to the context of Ghana. The most critical causal factors

under their respective constructs were personal greed (under PSSC), inadequate sanctions (under OSC),

lack of coordination among government departments (under SSC), flawed regulation system binder

(RSC) as the lack of rigorous supervision (under PSC). In addition to other constructs, the causal factors

were revealed to have significant critical impacts on the activities such as CTS3, CTS4, CTS5, and

other important activities at the post-contract stage including PCP1 through to PCP5.

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In sum, the objective revealed the critical forms of corrupt practices and their associated causal factors

in the procurement process. The results retrieved from this objective does not only facilitate the

development and the enforcement of appropriate ACMS but also to facilitate deeper investigations into

these affected stages and activities on how to develop reinforcing mechanisms to reinforce the entire

process against corruption.

Objective 2: Examine the procurement irregularities in the developing context

This objective was established to examine the criticalities of procurement irregularities and evaluate

the credibility and reliability of the identified suppositions. In realizing this objective, three sub-

objectives were established set. They are: 1) systematically review the relevant documents to identify

the prevailing procurement irregularities or risk indicators identified in infrastructure procurement in

the context of developing countries, particularly Ghana; 2) evaluate the criticality of the identified risk

indicators; and lastly 3) test the hypothesis on the corruption attribution to the identified irregularities.

Due to the context-specific nature of this objective, the primary documents that revealed the

procurement irregularities in the context of Ghana were the periodic reports issued by the auditor

general of the Republic of Ghana. The Fuzzy Synthetic Evaluation (FSE) technique, which is regarded

as one of the leading soft computing tools for assessing risk, is employed to evaluate the criticality of

the irregularities. Moreover, other auxiliary rigorous tools such as factor analyses, normalization, and

descriptive tools are employed to factorize the identified irregularities and to test the established

hypothesis. The results reveal that the sourcing of proforma invoices from the same supplier as well as

compliance Irregularities was revealed to be the most critical variable and construct respective.

Moreover, out of the four constructs developed, even though three were identified to be critical and

one, moderately critical. The results confirm two hypothesized constructs, which are administrative-

specific irregularities and compliance irregularities, to significantly contribute to risking the

infrastructure works to the incidence of corruption.

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Lastly, the impact of these variables within this construct, in addition to the other negative constructs

were examined. As mentioned, eleven out of the twenty-one activities were identified to be highly

impacted by the variables. The results obtained from this objective did not only focus on the

identification and the examinations of the criticalities of the procurement irregularities but also their

associated impacts. Theoretically, the relevance of this objective is attributed to its knowledge

contribution by examining the criticality of procurement irregularities and testing the hypothetical

stance of their contribution to the incidence of corruption. Practically, this study is intended to

contribute immensely to both procurement planning and policy-making process regarding the measures

to put in place to prevent or extirpate the likelihood of any of the risks’ incidence. As such, the

information in this study is relevant to project parties, policymakers, and anti-corruption activists within

the domain of the developing context.

Objective 3: Establish the stages in procurement and their susceptibility to corruption with respective

strategic measures to curb its incidence

This objective was set to establish the stages (and the respective activities) in procurement and their

susceptibility to corruption with respective strategic measures to curb its incidence. First, a

contemporary review was conducted to identify the procurement systems in existence. However, this

section focused on the traditional procurement system since most of the activities under this system are

captured at the various stages of the other systems. Twenty-one activities were identified under the

procurement process, captured under four major stages or constructs. The stages are the pre-contract

stage, contract stage, contract administration stage, and the post-contract stage. As mentioned, the

objective of the study was to ascertain the susceptibility levels of the procurement stages and activities

to corruption and also the overall impact of the constructs of corruption on the process. The other sub-

objective therefore focused on the evaluation of the criticalities of the various constructs of corruption

forms. Not only was this assessment conducted in the developing context, but also the developed

context. This enabled a comparative analysis to be conducted. While the result indicated that the

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procurement process in the developing context is vulnerable to the incidence of corrupt practices, the

case of the developed context is sharply disparate. Moreover, the comparative analysis revealed the

activities that resulted in the sharp disparities and how the developing context can learn from the

developed to neutralize the susceptible stages from their current form to a more stable, reinforced, and

resilient activities and stages within the procurement process. Particularly in the case of Ghana, not

only were the activities examined to identify their susceptibility patterns, but also, the results generated

facilitated the development of a fuzzy model for determining and predicting the vulnerability levels in

both existing and proposed projects. This is a linear model, simple to understand, adapt, and replicate

in other contexts. This objective focuses on the exploration of the irregularities identified within the

procurement process.

Moreover, while the measurement and predictability of corruption are reported to be difficult due to its

clandestine nature, this section also attempted to develop a measurement model for evaluating the

proneness of the procurement process of construction projects to corruption. The model is developed

using a soft computing approach (i.e., the Fuzzy Synthetic Evaluation technique) to assess the levels of

vulnerability with respect to the stages of corruption and their corresponding activities within the

procurement process of construction projects. A review of related literature produced a 21-activity list

encapsulated within the four stages of the procurement process. Procurement and construction

practitioners evaluated the list through an expert survey. The analysis of the survey results revealed an

overall project vulnerability index, which suggests that construction projects executed in developing

countries are relatively susceptible to corrupt practices. The main stages of the process that were

identified to be vulnerable were the contract stage (CTS) and the post-contract phase (PCP).

This section of the study contributes to the body of knowledge on the ways of measuring the various

indicators of corruption in infrastructure procurement and is, arguably, the first to employ soft

computing techniques (i.e., the FSE approach) to estimate the susceptibility patterns of the various

stages of the procurement process as well as develop an easy to adopt-and-use, yet standardized

approach to facilitate similar estimations in future works. Practically, even though a rigorous technique
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is employed, the model is developed in a manner that is easily understandable and can be adopted by

practitioners such as policymakers and auditors for detecting and/or measuring the vulnerability

indexes of various procurement activities and their respective stages of the procurement process to the

incidence of corruption. The model can as well form the basis for researchers to develop more

comprehensive tools that extend beyond the boundaries of the procurement process for predicting,

measuring and offering effective measures for corrupt practices right from the definition of project’s

requirements through to project execution to contract close-out. Thus, contributing to a more deepened

understanding of the various means of measuring corruption in the domain of project procurement and

management. Lastly, the developed model provides useful insights that can inform project parties and

anti-corruption activists in their efforts to implement necessary actions aimed at curbing the incidence

of corrupt practices in construction projects in developing countries.

Objective 4: Investigate the effectiveness and the barriers to effectiveness of the anti-corruption

measures

This objective reviewed the anti-corruption measures (ACMs) developed to mitigate the pervasiveness

of corruption in construction project management (CPM). Using a two-stage methodological process

to identify the relevant publications needed, 39 unique ACMs were identified in 38 selected

publications. The leading ACMs identified are ethical codes, transparency mechanisms, training, and

development initiatives. A conceptual framework constituting six thematic constructs was developed

to facilitate easy identification of ACMs and the categorization of future developments of ACMs. They

are regulatory, managerial, probing, compliance, promotional, and reactive measures. The findings

contribute an in-depth understanding of ACMs in CPM and are useful for further empirical research.

Following the retrieval and the categorization of the variables into their respective constructs, two

surveys were conducted. First, a global expert survey was conducted with 65 experts from around the

world involved in infrastructure project procurement and management using the purposive sampling

technique. The analysis was conducted on a contextual comparative basis, thus, comparing the views

of experts from the developed countries against the experts from the developing countries. The leading
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barriers identified by the respondents from the developing context were the absence of political will by

government officers and statutory professional councils to fight corruption and personal attitudes,

which include the lack of will to become involved in fighting corruption. The respondents from the

developed world revealed that non-familiarity with ethical codes, the fear of being caught reporting,

and personal attitude were the leading barriers. The Mann-Whitney U test was used to analyze the

statistical difference regarding the barriers’ criticality between the two contexts. This study contributes

to a deepened understanding of corruption by examining the criticalities of barriers to the effectiveness

of ACMs, which have not received the needed attention in the past. The study also reveals that the

prevalence of corruption in infrastructure projects is not attributed to the causes and vulnerabilities

only; it is also attributed to the identified barriers. This study informs policymakers, anti-corruption

institutions, and academic and industrial researchers about the barriers that are likely to be encountered

in enforcing and applying the stipulated ACMs. It is also intended to contribute to the strategic

development of a more holistic approach to annulling corrupt practices in project procurement and

execution.

Secondly, the section employed the fuzzy synthetic evaluation (FSE) technique to assess responses

retrieved from experts involved in the procurement and execution of infrastructure-related projects

using the purposive sampling technique to reach the experts in Ghana. Even though none of the

variables nor constructs was identified to be effective, the probing measures’ construct was identified

to be the highest-ranked construct, followed by managerial measures. Moreover, all of the remaining

constructs with their variables were revealed to be moderately effective. The rationale behind this

explorative study is to ascertain how effective the existing anti-corruption measures stipulated to check,

thwart and extirpate corrupt practices in infrastructure project procurement and management perform

in developing countries and to reveal the ineffective measures that need reinforcement in order to make

them resilient. This section of the research theoretically contributes to the body of knowledge on

corruption in infrastructure-related studies and adds to the deepened understanding of the subject

matter. Practically, this objective revealed useful information for project parties, policymakers, anti-

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corruption institutions and researchers towards the reinforcement of the existing measures for the

expurgation of corrupt practices in infrastructure projects’ procurement, execution, and management.

Objective 5: Develop a dynamic overarching model to mitigate corrupt practices in public

procurement

The last objective encompasses all the first four objectives to establish the overarching framework for

the study. It encapsulates the dynamics defining the vulnerabilities of the activities and the stages within

the procurement process, the criticalities of the causal factors, the procurement irregularities or risk

indicators, the effectiveness of the anti-corruption measures, and the criticalities of the barriers that

hamper the efficacy of the anti-corruption measures. Three comprehensive models are developed in

this section. The first two models serve as the foundational models for the final third and final model.

The established the relational impacts of the criticalities of the negative constructs on the procurement

process. The second model examined the significant correlations of the barriers against the

effectiveness of ACMs on the respective constructs of the ACM. Finally, the third model dynamically

examines all the constructs within the first two models to propose a final framework for reducing the

criticalities of the negative constructs and, at the same time, enhancing the efficacy of the anti-

corruption measures.

The first model examined the relational effects of the constructs of corruption on the procurement

activities and stages. In general, eleven out of twenty-one stages were noted to be highly impacted by

the constructs. Among the eleven impacted one activity was identified under the pre-contract stage,

three out of five activities of the construct stage, two out of four at the contract administration stage,

and five out of six activities at the post-contract stage. Thus, none of the stages was exempted from the

criticalities of the constructs of corruption. Per the analysis, the only activity that was identified to be

significantly impacted by the corruption constructs was PCS6 (that is, the receipt of leaders). While

PCS4 (obtaining necessary approvals) and PCS5 (soliciting tenders) were noted as the most susceptible

activities to corrupt practices, the network analysis revealed PCS6 (even though not as vulnerable as
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PCS4 and PCS5) as the most significant in terms of the constructs' criticalities at the pre-contract stage.

Moving on to the next stage (that is, the contact-stage), the three most impacted activities based on the

normalized values were CTS3 (the selection of a contractor), CTS4 (awarding of contact), and CTS5

(the preparation and signing of contract). Stage three (also known as the contract administration stage)

also recorded similar results as compared to the previous stage.

Two out of four activities were identified to be impacted by the collective force of all the variables

captured under the negative constructs of corruption. The two activities are CAS1 (issuing of contract

amendments) and CAS4 (administering progress payment). CAS4 was. However, the only activity

noted to be highly vulnerable to the incidence of corrupt practices (Owusu et at. 2019). At the final

stage, five of the activities were identified to be crucial regarding their criticalities to the impacts of the

construct of corruption. Thus, the activities noted were: 1) completing final audits, checking proofs of

delivery (project deliveries), and returning of performance bond as closing out the contract. The only

activity identified to be less critical regarding the impacts of the negative constructs is the confirmation

of the accuracy and completeness of file documentations. Similar findings were noted under the

vulnerability assessment stage. Thus, aside from the first five activities identified to be vulnerable to

corruption, the final activity within this stage (that is, PCP6) was the only activity noted to be less

vulnerable to corrupt practices. This section of the objectives revealed one of the most significant

findings of the study. That is, to reveal the activities within the procurement process heavily impacted

by the negative constructs of corruption. The information revealed by this model is significantly useful

for not only decision making regarding the criticalities of forms to extirpate but also the highly impacted

activities within the procurement process that needs attention and reinforcement against the criticalities

of the negative constructs.

The second model examined two main sub-objectives. They were: 1) the effectiveness of anti-

corruption measures (ACMs) in project planning, procurement and management, and 2) the barriers

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that hinder the effectiveness of the ACMs. It investigates the correlational impacts of noted barriers on

the efficacy of ACMs in the procurement and management of public projects in the developing world

using Ghana as the case study. Similar to the previous objectives, an expert survey was conducted with

the same 62 professionals involved in project procurement and management. The data were analyzed

using descriptive statistics, factor analysis, and partial least squares structural equation modeling (PLS-

SEM). Moreover, 24 relational iterations were established and examined among the identified

constructs (i.e., four barriers and six ACM constructs), and they formed the study’s hypotheses. The

PLS-SEM was used to test the hypotheses. The results showed that the lack of knowledge and

understanding of one’s right in a contractual environment and political and structural barriers were the

most critical variable and construct, respectively. The PLS-SEM also revealed seven out of the twenty-

four statistical relationships tested were revealed to be significant.

The socio-political barriers’ construct, which happened to be the most critical construct, was revealed

to have strong impacts on administrative, compliance, and promotional anti-corruption measures. The

findings justify why most projects in this part of the world are plagued with political corruption and, in

turn, lead to high cost and time overruns. It also shows the need to extirpate socio-political barriers to

enhance the effectiveness of the established anti-corruption measures as well as limit the prevalence of

corruption in project management. This study is arguably the first to examine the impacts of barriers

on the effectiveness of anti-corruption measures in public projects in the developing context. The

findings can facilitate the development of stringent anti-corruption measures that are more resilient to

barriers. Theoretically, this study contributes to the body of knowledge regarding corruption-related

studies in project management. Practically, it can inform relevant parties, such as project managers,

contract administrators, project stakeholders, policymakers, and anti-corruption advocates, about the

significant barriers that obstruct the effectiveness of anti-corruption measures and the need to extirpate

them. Thus, contributing to the holistic development of anti-corruption measures aimed at expurgating

corrupt practices during the planning, procurement, and management of public projects.

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 Chapter 10 – Conclusions and Recommendations

Lastly, the final model examined the dynamic nature of the constructs of corrupt practices in relation

to the complex procurement process. As established in the fifth objective, which happened to be an

overarching objective among the others, this section of the study sought to develop and propose a

dynamic model to reduce the impact of the accumulated corruption within the respective activities of

the procurement process. Moreover, the model, on the other hand, is intended to guide the decision-

making process on how to strengthen the potency of anti-corruption measures. Thus, it was anticipated

that all the constructs on corruption in this study would be collectively examined. Given the dynamic

nature of corrupt practices (c.f. Jain 2001; Shan et al. 2017; Chan and Owusu 2017), previous methods

often adopt linear approaches that fail to examine the dynamism and complexities regarding corruption.

Thus, the final objective employed the system dynamics (SD) approach to examine the dynamic

behavior of all the constructs of corruption within the various activities of the procurement process.

Most significantly, the dynamic interactions among all the measurement items captured in the model

would be revealed. The proposed dynamic model is presented to facilitate decision making on how to

efficiently improve the efficacy of the established anti-corruption measures and reduce the impact and

influence of corrupt practices within the procurement process. Lastly, some of the key findings to each

of the objectives are presented in Table 10.1.

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Table 10.1: Review of objectives’ key findings

No Objectives Key Findings

1 Examine the forms of 1. The results demonstrated sharp disparities between the developed and the developing contexts on all the
corruption and their constructs examined. Thus, while the negative constructs were revealed to be relatively critical in the
respective causes that developing contexts, the opposite was the case for the developed context.
instigate or propel
2. Most discussed causes of corruption in literature, Psychosocial-Specific, Organizational-Specific, and
corruption in
infrastructure procurement regulatory specific-causes while the most critical causes of corruption were identified as follows:
(IP). inadequate sanctions and flawed regulation system at the variable level.
3. Wide disparities in forms between developed and developing countries. Out of the 27 forms examined,
only three forms did not show significant statistical disparities between the two contexts. Thus, other
than money laundering, deception, and professional negligence, all the remaining forms, from bribery to
conflict of interest, demonstrated wide disparities in terms of their criticalities between the two contexts.

2 Examine the procurement 1. The most critical procurement irregularities prevalent in the Ghanaian IP were noted to be: Compliance
irregularities in the irregularities (construct level) and payments for uncompleted works (variable level).
developing context
2. Irregularities contributes significantly to the overall prevalence of corruption in the developing context
3. Development of anti-corruption frameworks should specifically contain measures to curb the criticalities and
the impacts of the irregularities

3 Investigate the 1. ACMs more effective in the developed contexts as compared to the developing sectors
effectiveness and the
2. Most effective ACM construct that is revealed to enhance the overall effectiveness of an ACM
barriers to effectiveness of
framework is probing measures
the anti-corruption
measures 3. Socio-political barriers were revealed to be the primary factors that impedes the effectiveness of the
ACMs.
4. The effectiveness of the ACMs can be improved by stepping up some of the key ACM constructs such
as probing measures such as probing and promotional measures.

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 Chapter 10 – Conclusions and Recommendations

4 Examine the IP stages' 1. The IP procurement process was revealed to possess varying degrees of susceptibility patterns to
susceptibilities to corruption.
corruption, associated
2. Most dominant forms across the stages include collusive and bribery acts at the contract stages in both
forms, and respective
contexts
strategic measures
3. Most impacted procurement stages in the case of Ghana were contract stage and post-contract stage.
4. The contract stage was revealed to be the most vulnerable in the developing context. The developed
context, as well as HK, showed relatively neutral levels of susceptibilities in all the cases.

5 Develop a dynamic model 1. No specific model or framework designed to extirpate corruption other than the PPA ACT 2003, which
to mitigate corrupt is void of adequate measures.
practices in the IP process
2. SD model shows that the overall impact of corruption can be effectively dealt with by mitigating some
of the key negative constructs (e.g., socio-political construct).
3. Effectively strategize ex-ante and ex-post ACMs across the respective stages of the procurement process

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 Chapter 10 – Conclusions and Recommendations

10.3 Limitations of the study and recommendations for future research

Research limitations may be argued to be inevitable, especially because the processes and outcomes of

research works are mostly unpredictable. Similar to other studies, this research encountered a few

limitations, which are presented below and the recommendations for future studies proposed. The first

limitation is attributed to the type of data uses in this study. While the expert survey is argued to be

suitable for this study or most preferred data collection technique (Trapnell 2015), it is also widely

criticized for its opinion or subjective driven nature. This approach is argued to possess some inherent

flaws as it often criticized to be subjective. The subjective nature of the data may be addressed in a

future study by making use of real corruption case data (if any) and probably, big data to draw justifiable

conclusions and assumptions. Recently, the use of big data, coupled with the adoption of rigorous

analytical tools, is becoming more common. Future works can, therefore, take advantage of this positive

trend after weighing the pros and cons of the applicability, especially in dealing with sensitive topics

like corruption. Also, given the upsurge of big data analytics on almost every topic, conclusive

deductions can be drawn with justifiable connotations on the dynamics of corruption in specific

projects, and how these practices can be mitigated, and transparency improved via big data analytics.

The second limitation concerns the non-generalization of the study's results. While the main surveys

conducted in this study mainly come from Ghana (developing countries) and Hong Kong (developed

country), it must be emphasized that using or referring to the outputs generated in this study must be

duly acknowledged. Corruption has long been reported to be a complex subject and is defined

differently in different contexts (Owusu et al. 2017; Jain 2001). Therefore, generalizing the results of

this study beyond Ghana may be somewhat unrealistic. While this study can offer a solid foundation

for similar studies in other developing contexts, more general surveys that are evenly distributed across

different contexts can be conducted, if possible, to be able to draw general deductions or conclusions

from the survey.

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 Chapter 10 – Conclusions and Recommendations

Admittedly, the construction process is a highly complex one; however, only the procurement section

was examined in this study. Therefore, whereas germane and practical conclusions may be drawn to

make significant contributions towards the justification of the adoption of the model developed in this

paper in different contexts, it must be noted that the results obtained, and the model developed cannot

be generalized to represent the entire construction process. Further studies should consider examining

the other stages of the construction process other than the procurement, which has been reported in this

study. Moreover, another primary limitation of this study is attributed to the overgeneralization or the

applicability of the results to different contexts. Simply put, since the study primarily highlights the

case of the Ghanaian context, the adoption of the linear model for estimating the vulnerability indexes

of other countries should be conducted with caution as explicated above. Also, per the theory behind

the measurement tools for estimating corruption index, Trapnell (2015) revealed two foundational

constructs that can be considered to establish more rigorous and explicit results. They are the estimation

of corrupt practices and the estimation of anti-corruption measures. This study only focused on the

measurement of corruption (i.e., the susceptibility of the procurement stages to the incidence of corrupt

practices) and not on anti-corruption measures. Therefore, it is recommended that future studies explore

the measurement indexes for anti-corruption measures since such a study will contribute to the holistic

measurement or estimation and determination of a firm’s or a state’s condition regarding corruption.

Regarding the international surveys conducted in this study, the limitation has to do with the unevenness

of the respondents’ distribution across the representing countries. Although discussions are made on

both developed and developing countries, it must be emphasized that the conclusions do not represent

the general views of the overall experts from the developed or the developing world because most of

the respondents in this study happen to come from Hong Kong and Ghana, respectively. Therefore, any

reference to the results should be relayed, conveyed, or used with caution (that is, the specified

limitation encountered in this study). The skewness of the data toward these two specific regions is

attributed to the fact that the authors are currently conducting a research study using these two contexts

as the scopes for the ongoing research. Although the research is still ongoing, the views of other experts,

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 Chapter 10 – Conclusions and Recommendations

particularly from the top global organizations and academics involved in the procurement and

management of construction and other infrastructure-related projects, were sought after and solicited

to determine whether there will be a level of consistency in the views of all the experts involved

regardless of their nationality.

Moreover, the findings on the international survey cannot be attributed to one specific country but

rather serve as a point of reference in considering areas to tackle in each context regarding the constructs

explored at the international level (e.g., explorations on the barriers against the efficacy of ACMs). It

is therefore recommended that further detailed research be conducted in a more focused direction (i.e.,

institution or country-specific). This is because the barriers that affect a given context may be very

much disparate from another context, even in the same region. Some items may be more critical than

others, and even other barriers specific to one context may be identified to exceed the 17 barriers

identified in this study. This is one of the many reasons more detailed studies in specific contexts are

needed, but this study can be referred to as a reference point.

It may also be argued that a larger sample from more wide-ranging counties could have generated more

significant results. Not disputing this proposition, it is justified that the sample size is adequate and

appropriate for further analysis, given the initial results generated by the necessary tests, which stipulate

the results to be reliable and appropriate. Moreover, due to the sensitive nature of the topic, and the

realization that the theme was focused on a wider perspective, experts were reluctant to share the

situations from their specific countries, and only those who responded were recorded for the analysis.

However, the authors believe and recommend that researchers who aim to conduct similar research in

a given or specific context should solicit more data to eliminate any discrepancies concerning the

reliability of the data and yield more significant results.

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 Chapter 10 – Conclusions and Recommendations

10.4 Chapter Summary

This chapter presented the summaries of the main aim of the study with the five interrelated objectives

developed to realize the aim of the study. The conclusions of all the objectives were presented with

their respective significance to the scholarship of corruption-related studies in

infrastructure/construction project management. Moreover, the contributions to industry practice and

practitioners have been duly stipulated. Finally, the major limitations encountered regarding the project

have been presented with recommendations for future research.

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APPENDICES

367
 SECTION B
Q1a. Proneness of procurement stages to corruption. How vulnerable are the following stages of
procurement and construction to corruption? 1= Not vulnerable to 5=Extremely vulnerable. Please,
also indicate the most extreme (only one) associated form to each process. 1= Bribery Acts; 2=
Fraudulent Acts; 3= Collusive Acts; 4= Extortionary Acts and 5= Discriminatory Acts

No Procurement Process Level of Vulnerability Form associated

1 Pre- Define requirements ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
Contra
2 ct
Procurement process planning and strategy development ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
3 stage Pre-tender survey ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
4 Obtaining necessary approvals ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
5 Soliciting tenders ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
6 Receipt of tenders ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
7 Contra Pre-tender meeting (Establishing Evaluation Criteria, ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
ct Evaluation Plan, Evaluation Criteria)
Stage
8 Tender evaluation (review to approve or reject bids) ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
9 Select contractor ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
10 Award contract/Purchase order ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
11 Preparation and Signing of Contract ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
12 Contra Issuing contract amendments ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
ct
13 admini
Monitor Progress ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
14 stratio Follow up delivery ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
15 n stage Administer Progress payments ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
16 Post File final action Contractor agreement to final claim ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
17 contr Issue final contract amendment ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
18 act Complete of financial audits ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
19 phase Check for proof of delivery ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
20 Return of performance bonds and close-out ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
21 Ensure completeness and accuracy of file documentation ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5

No Construction Process Level of Vulnerability Form associated

1 Conception ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
2 Project selection stage ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
3 Planning stage ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
4 Inspection stage ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
5 Design Stage ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
6 Pre-qualification and tender ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
7 Contact signing stage ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
8 Project execution ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
9 Service Delivery ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
10 Project Maintenance ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
11 Dispute resolution ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5

No. Parties involved in procurement and construction processes Level of Vulnerability Level of Corruption
1 Public participants (Clients, regulatory authorities, etc.) ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
2 Private participants (clients, financiers, etc.) ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
3 Contractors and subcontractors ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
4 Design consultant (Architects, Quantity Surveyors, etc.) ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
5 Suppliers ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
6 Legal advisors ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
7 Other ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5

370
2. General Forms of corruption in Infrastructure Procurement. How critical are the incidences of
the following forms of corruption to infrastructure procurement? 1= Not Critical; 2=Less Critical;
3=Neutral; 4= Critical; 5=Very Critical. Please, kindly indicate with respect to their categories.

No. Corruption Acts Corruption Form Level of Criticality

Low High
1 Bribery Acts Bribery ☐1; ☐2; ☐3; ☐4; ☐5

2 Kickbacks ☐1; ☐2; ☐3; ☐4; ☐5

3 Facilitation Payments ☐1; ☐2; ☐3; ☐4; ☐5

4 Influence Peddling ☐1; ☐2; ☐3; ☐4; ☐5

5 Lobbying ☐1; ☐2; ☐3; ☐4; ☐5

6 Solicitation ☐1; ☐2; ☐3; ☐4; ☐5

7 Fraudulent Acts Fraud ☐1; ☐2; ☐3; ☐4; ☐5

8 Collusion ☐1; ☐2; ☐3; ☐4; ☐5

9 Front/Shell companies ☐1; ☐2; ☐3; ☐4; ☐5

10 Dishonesty ☐1; ☐2; ☐3; ☐4; ☐5

11 Ghosting ☐1; ☐2; ☐3; ☐4; ☐5

12 Money Laundering ☐1; ☐2; ☐3; ☐4; ☐5

13 Deception ☐1; ☐2; ☐3; ☐4; ☐5

14 Collusive Acts Bid rigging ☐1; ☐2; ☐3; ☐4; ☐5

15 Price fixing ☐1; ☐2; ☐3; ☐4; ☐5

16 Cartels ☐1; ☐2; ☐3; ☐4; ☐5

17 Extortionary Acts Extortion ☐1; ☐2; ☐3; ☐4; ☐5

18 Client abuse/’clientelism’ ☐1; ☐2; ☐3; ☐4; ☐5

19 Intimidations and threats ☐1; ☐2; ☐3; ☐4; ☐5

20 Coercion ☐1; ☐2; ☐3; ☐4; ☐5

21 Blackmail ☐1; ☐2; ☐3; ☐4; ☐5

22 Discriminatory Nepotism ☐1; ☐2; ☐3; ☐4; ☐5

23 Acts Favoritism ☐1; ☐2; ☐3; ☐4; ☐5

24 Patronage ☐1; ☐2; ☐3; ☐4; ☐5

25 Guanxi ☐1; ☐2; ☐3; ☐4; ☐5

26 Unclassified Acts Embezzlement ☐1; ☐2; ☐3; ☐4; ☐5

27 Conflict of interest ☐1; ☐2; ☐3; ☐4; ☐5

28 Professional negligence ☐1; ☐2; ☐3; ☐4; ☐5

371
Q3. The effectiveness of Anti-Corruption Measures. How effective are the following measures to
the application of infrastructure procurement? 1= Not Effective; 2=Less Effective; 3=Neutral; 4=
Effective; 5=Very Effective

No. Anti-Corruption Measures (ACM) Level of Effectiveness

Low High
1 Ethical code ☐1; ☐2; ☐3; ☐4; ☐5

2 Transparency mechanism ☐1; ☐2; ☐3; ☐4; ☐5

3 Training and development initiatives ☐1; ☐2; ☐3; ☐4; ☐5

4 Raising awareness ☐1; ☐2; ☐3; ☐4; ☐5

5 Rigorous technical auditing system ☐1; ☐2; ☐3; ☐4; ☐5

6 Contract monitoring ☐1; ☐2; ☐3; ☐4; ☐5

7 Comprehensive rules and regulations ☐1; ☐2; ☐3; ☐4; ☐5

8 Harsh punishment or penalty ☐1; ☐2; ☐3; ☐4; ☐5

9 Whistle-blowing mechanism ☐1; ☐2; ☐3; ☐4; ☐5

10 Compliance to fairness and transparent procedures ☐1; ☐2; ☐3; ☐4; ☐5

11 Education ☐1; ☐2; ☐3; ☐4; ☐5

12 Increase in accountability ☐1; ☐2; ☐3; ☐4; ☐5

13 Access to information ☐1; ☐2; ☐3; ☐4; ☐5

14 Financial disclosure / Disclosure ☐1; ☐2; ☐3; ☐4; ☐5

15 Contractual compliance ☐1; ☐2; ☐3; ☐4; ☐5

16 Good Leadership ☐1; ☐2; ☐3; ☐4; ☐5

17 Professional associations ☐1; ☐2; ☐3; ☐4; ☐5

18 Debarment/ Promoting fair debarment procedures. ☐1; ☐2; ☐3; ☐4; ☐5

19 Procedural compliance ☐1; ☐2; ☐3; ☐4; ☐5

20 Rigorous supervision among others ☐1; ☐2; ☐3; ☐4; ☐5

21 Effective investigation, court proceedings, departmental ☐1; ☐2; ☐3; ☐4; ☐5

disciplinary action
22 Development of strong political and ethical will to enforce ☐1; ☐2; ☐3; ☐4; ☐5
existing anti-corruption policies and laws
23 Enhance communication ☐1; ☐2; ☐3; ☐4; ☐5

24 Dismissal from employment or other disciplinary action] ☐1; ☐2; ☐3; ☐4; ☐5

25 Efficient reporting system (Independent hotline) ☐1; ☐2; ☐3; ☐4; ☐5

26 Information technology ☐1; ☐2; ☐3; ☐4; ☐5

372
Q4. Barriers to the effective application of Anti-Corruption Measures (ACM) in Infrastructure
Procurement. How risky are the following barriers to effective implementation and application of
anti-corruption measures in infrastructure procurement? Use 1=Not Critical; 2=Less Critical; 3=
Neutral; 4= Critical; 5=Highly Critical.

No. Barriers to effective application of ACM Level of

Criticality
1 Political and structural barriers ☐1; ☐2; ☐3; ☐4; ☐5

2 Fear of insecurity which includes fear of losing job ☐1; ☐2; ☐3; ☐4; ☐5

3 Fear of losing life ☐1; ☐2; ☐3; ☐4; ☐5

4 Social misrepresentation ☐1; ☐2; ☐3; ☐4; ☐5

5 Fear of being marginalized ☐1; ☐2; ☐3; ☐4; ☐5

6 Fear of being caught reporting ☐1; ☐2; ☐3; ☐4; ☐5

7 Social or occupational stigma and rejection ☐1; ☐2; ☐3; ☐4; ☐5

8 Bureaucratic process of reporting corrupt cases ☐1; ☐2; ☐3; ☐4; ☐5

9 Lack of independence ☐1; ☐2; ☐3; ☐4; ☐5

10 Fear of victimization ☐1; ☐2; ☐3; ☐4; ☐5

11 Inappropriate internal institutional coordination / inter agency ☐1; ☐2; ☐3; ☐4; ☐5
relations
12 Perception of no better end result, distrust in system ☐1; ☐2; ☐3; ☐4; ☐5

13 Lack of political will, A lack of political will by government ☐1; ☐2; ☐3; ☐4; ☐5
officials and statutory professional councils to fight corruption is
seen as an exacerbating factor
14 Lack of understanding and knowledge of their rights within a ☐1; ☐2; ☐3; ☐4; ☐5
contractual environment, difficulty in providing concrete
evidence
15 Inappropriate staffing ☐1; ☐2; ☐3; ☐4; ☐5

16 Lack of knowledge or non-familiarity with ethical codes/ ☐1; ☐2; ☐3; ☐4; ☐5
organizational codes of ethics
17 Personal attitude, for example, lack of will to become involved in ☐1; ☐2; ☐3; ☐4; ☐5
fighting corruption
18 Other ☐1; ☐2; ☐3; ☐4; ☐5

373
Q5. Causes of corruption in Infrastructure Procurement. How critical are the following causes to
the procurement of infrastructure? Use 1=Not Critical; 2=Less Critical; 3= Neutral; 4= Critical;
5=Highly Critical.

No Causes Criticality
1 Over close relationships ☐1; ☐2; ☐3; ☐4; ☐5
2 Poor professional ethical standard ☐1; ☐2; ☐3; ☐4; ☐5
3 Lack of a positive industrial climate ☐1; ☐2; ☐3; ☐4; ☐5
4 Negative role models ☐1; ☐2; ☐3; ☐4; ☐5
5 Inadequate sanctions ☐1; ☐2; ☐3; ☐4; ☐5
6 Lack of rigorous supervision ☐1; ☐2; ☐3; ☐4; ☐5
7 Personal greed ☐1; ☐2; ☐3; ☐4; ☐5
8 Flawed regulation system ☐1; ☐2; ☐3; ☐4; ☐5
9 Deficiencies in rules and laws ☐1; ☐2; ☐3; ☐4; ☐5
10 Great project complexity ☐1; ☐2; ☐3; ☐4; ☐5
11 Multifarious licenses or permits ☐1; ☐2; ☐3; ☐4; ☐5
12 Low wage level ☐1; ☐2; ☐3; ☐4; ☐5
13 The nature of infrastructure projects ☐1; ☐2; ☐3; ☐4; ☐5
14 Over competition in tendering process ☐1; ☐2; ☐3; ☐4; ☐5
15 Inappropriate political interference ☐1; ☐2; ☐3; ☐4; ☐5
16 Lack of pro-active steps by funders to limit corruption on projects ☐1; ☐2; ☐3; ☐4; ☐5
17 Absence of effective and responsible administrative systems ☐1; ☐2; ☐3; ☐4; ☐5
18 Insufficient legal punishments and penalties ☐1; ☐2; ☐3; ☐4; ☐5
19 Fierce competition ☐1; ☐2; ☐3; ☐4; ☐5
20 Weak procurement / contractual structures ☐1; ☐2; ☐3; ☐4; ☐5
21 Absence of control mechanism ☐1; ☐2; ☐3; ☐4; ☐5
22 Transition of governments or economies ☐1; ☐2; ☐3; ☐4; ☐5
23 The nature of corruption being a secret activity ☐1; ☐2; ☐3; ☐4; ☐5
24 Complex contractual structure ☐1; ☐2; ☐3; ☐4; ☐5
25 Appointment of a local representative who acts on behalf of the firm to ☐1; ☐2; ☐3; ☐4; ☐5
obtain contracts
26 Economic survival ☐1; ☐2; ☐3; ☐4; ☐5
27 Delaying the payment of workers’ salaries ☐1; ☐2; ☐3; ☐4; ☐5
28 Lack of legal awareness ☐1; ☐2; ☐3; ☐4; ☐5
29 Lack of coordination among Government departments ☐1; ☐2; ☐3; ☐4; ☐5
30 Poor documentation of records ☐1; ☐2; ☐3; ☐4; ☐5
31 Insufficient transparency in the selection criteria for tenderers ☐1; ☐2; ☐3; ☐4; ☐5
32 Deregulation in the public construction ☐1; ☐2; ☐3; ☐4; ☐5
33 Complexities of institutional roles and functions ☐1; ☐2; ☐3; ☐4; ☐5
34 Asymmetric information amongst project parties ☐1; ☐2; ☐3; ☐4; ☐5
35 Lack of standardized execution in construction projects ☐1; ☐2; ☐3; ☐4; ☐5
36 Negative encouragement ☐1; ☐2; ☐3; ☐4; ☐5
37 (The influence of guanxi) ☐1; ☐2; ☐3; ☐4; ☐5
38 Absence of project anti-corruption systems ☐1; ☐2; ☐3; ☐4; ☐5
39 Subjecting workers to job insecurity, especially in government and public ☐1; ☐2; ☐3; ☐4; ☐5
enterprises
40 Feeble semblance of public interest ☐1; ☐2; ☐3; ☐4; ☐5
41 Monopoly ☐1; ☐2; ☐3; ☐4; ☐5
42 Inefficiency ☐1; ☐2; ☐3; ☐4; ☐5
44 Lack of frequency of projects ☐1; ☐2; ☐3; ☐4; ☐5

374
 SECTION C
Q1. Procurement and Contractual Irregularities in the Ghanaian Public Sector. How probable are the listed
irregularities likely to happen and should they occur in infrastructure procurement, how severe are their
impact on the procurement process? Use 1=Not Probable; 2=Less Probable; 3= Neutral; 4= Probable;
5=Highly Probable; at the probability section and 1=Not Severe; 2= Less Severe; 3= Neutral; 4=
Severe; 5= Very Severe at the Severity Section.

No Procurement Irregularities/Vulnerabilities Probability Severity

1 Institutions not following correctly the ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
Public Procurement Act in terms of
obtaining minimum quotations, exceeding
authorized threshold limits and
unauthorized sole sourcing of suppliers.
2 Lack of adequate supervisory control ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
over procurement transactions and
management
3 Payments for uncompleted works ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
4 Non-application of sanctions ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
5 Poor supervision of subordinate officers ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
6 Disregard for Public Procurement Act ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
regulations
7 Procurements not taken on ledger charge ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
8 The procurement of goods and services ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
by management without adequate
recourse to procurements committees of
the various public institutions, which
diverges from the provided regulations.
9 Variations to contract ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
10 Outstanding mobilization advances owing ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
to non-observance of stipulated
regulations
11 Fragmentary procurement ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
12 Little evidence of value for moneys spent ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
13 Sourcing of proforma invoices from the ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
same supplier (Single sourcing)
14 Overpayment of purchases ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
15 Lack of proper co-ordination among key ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
departments of the Company and
apparent internal control weaknesses
reconciliation on Association
16 Lack of consistent monitoring and review ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
of procurement activities
17 Lack of whole-of-government and ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5
corporate procurement planning for
significant purchases
18 Lack of audit trails or verification data ☐1; ☐2; ☐3; ☐4; ☐5 ☐1; ☐2; ☐3; ☐4; ☐5

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375
Definition of key terms
(Please, if necessary, refer to the following definitions when answering the questions in section C)

Forms Description
F1 Bribery Acts
Bribery Bribery refers to a corrupt act which may involve giving, promising, soliciting, accepting or
offering a benefit to lure or entice someone to act unethically or illegally.
Kickbacks Kickbacks refer to illegal acts where a secret payment is demanded by an individual in a
coercive position from another party in search of an advantageous or a biased decision.
Facilitation Facilitation Payments are regarded as small bribes which can also be termed as ‘grease’ or
Payments ‘speed’ payments normally made to expedite or secure an action to which the briber already has
authorized or other rights to.
Influence Influence Peddling is described as the use of one’s status or influence on behalf of another
Peddling person for a special advantage in return for financial favors or other benefits.
Lobbying Lobbying refers to any corrupt act which is undertaken to influence the decisions and policies of
an institution to favor an outcome or a course.
Solicitation Solicitation is the act of enticing, ordering, influencing or asking another party to indulge in the
act of bribery or other corrupt behaviors.
F2 Fraudulent Acts
Fraud This takes place when a party deceives another fellow with the aim of gaining an illegal or unfair
advantage (contract award, financial, political).
Collusion Collusion is regarded as an undisclosed arrangement that exists among the parties involved,
either in the private or public sector or both who meet to conspire to commit deceitful or
fraudulent acts with the intention of gaining illegitimate rewards such as financial gains.
Front/Shell Front/ Shell companies refer limited liability companies or corporations which have no corporal
companies existence in terms of jurisdiction; no commercial activities neither are they made up of any real
employees.
Dishonesty Dishonesty can be described as an act of lying, stealing or cheating with the primary aim of
acquiring, converting or disposing of either tangible or intangible property to obtain an upper
hand or a benefit.
Ghosting Ghosting refers to an entity (either an individual or a unit) made-up for the purposes of
fraudulent act or deception.
Money Money Laundering refers to the act of concealing the ownership, source or the end point of
Laundering money obtained in an unlawful of a dishonest manner and secretly placing it in legitimate
ventures or projects to make them look lawful.
Deception Deception refers to the act of presenting wrong information with the aim of misleading another
person concerning a situation that in itself is true.
F3 Collusive Acts
Bid rigging Bid rigging refers to a collusive act where consenting participants settle on the results of a bid
process beforehand.
Price fixing Price fixing is a collusive act analogous to big rigging. With this act, a sect of competitors or
tenderers colludes to either manipulate or fix prices rather than observe an open market
competition.
Cartels Cartel, also regarded as a form of the collusive act and similar to bid rigging, transpires when
two or more firms arrange or enter into an agreement to limit the flow of materials or as fix the
prices of goods they control in a specific industry.
F4 Extortionary Acts
Extortion Extortion refers to the direct or indirect act of using one’s power, knowledge or status to
coercively threaten others in the form of demanding unmerited benefits, compensations or
benefits.

376
Client Client Abuse / ‘clientelism’ refers to a biased arrangement of exchanging goods, favors or
Abuse/cliente resources on a manipulative affiliation between a powerful party and a punier client.
lism’
Intimidations Intimidations and threats are regarded as a form of extortion where an individual intentionally
and threats induces a sense of subjection, inferiority or fear into another person or group of individuals with
the aim of frightening them to make them do what the Intimidator wants.
Coercion Coercion is regarded as a direct or indirect act of committing harm, prejudice or threats to
negatively influence the actions of another person always often to favor the coercer.
Blackmail Blackmail can be described as a condition or an act when a party threatens another party if the
latter party does not render some sort of privilege.
F5 Discriminatory Acts
Nepotism Nepotism refers to an act where an individual in a position grants a favor to either a relative or a
friend without suitable regard to qualification.
Favouritism Favoritism refers to the act of offering a special treatment to either an individual or a group of
persons, and it often takes the form of awarding contract, honoring, hiring, benefits, etc. even
though the person may not necessarily be qualified for the position or the contract offered.
Patronage Patronage is regarded as a form of favoritism where an individual is offered a job, award contract
or other benefits regardless his/her entitlement or qualifications and it is normally due to either
the individual’s connections or affiliations.
Guanxi Guanxi is a Chinese term for nepotism although not all Guanxi may be termed unlawful. In some
cases, it turns to favor the parties that have good connections in a local domain, but it becomes
unlawful when the favor is granted to a party or group of persons not deserving the favor.
F6 Unclassified Acts
Embezzlemen Embezzlement refers to an act where an individual misappropriates, traffics or uses either goods
t or funds of an organization or an institution entrusted in his/her care for personal benefits.
Conflict of Conflict of Interest in the construction industry refers to the situation where a professional of the
interest industry is challenged with a choice of deciding between the demands and duties required by
profession and their respective personal interests.
Professional Professional Negligence was insinuated as a corrupt conduct in the construction industry which
negligence occurs when a professional fails to provide a responsibility of care which a normal careful and
prudent professional would offer given the same conditions.
Reference: Chan and Owusu 2017

377
 Appendix B

SELECTED JOURNAL PAPERS ON FORMS OF CORRUPTION

Selected papers on Corruption Forms

No. Journal Year Authors Citation
1 BRI 2004 Dorée, A. G. 107
2 JCEM 2014 Le, Y., Shan, M., Chan, A. P., & Hu, Y. 13
3 JCEM 2012 Meduri, S. S., & Annamalai, T. R. 14
4 JCEM 2012 Ho, C. M. 10
5 JCEM 2000 Wang, S. Q., Tiong, R. L., Ting, S. K., & Ashley, D. 147
6 JCEM 2006 Waara, F., & Bröchner, J. 94
7 JCEM 2008 Sohail, M., & Cavill, S. 57
8 JCEM 2009 Tsai, J. S., & Chi, C. S. 36
9 CME 2011 Tabish, S. Z. S., & Jha, K. N. 25
10 CME 1997 Adams, O. 71
11 CME 2012 Bowen, P. A., Edwards, P. J., & Cattell, K. 23
12 CME 2012 Ling, F. Y. Y., & Tran, P. Q. 19
13 CME 2007 Bowen, P., Akintoye, A., Pearl, R., & Edwards, P. J. 54
14 CME 2011 Tabish, S. Z. S., & Jha, K. N. 37
15 CME 2012 Tabish, S. Z. S., & Jha, K. N. 12
16 ECAM 2016 Loosemore, M., & Lim, B. T. H. -
17 ECAM 2016 Willar, D., Trigunarsyah, B., & Coffey, V. 1
18 ECAM 2015 Brown, J., & Loosemore, M. 2
19 ECAM 2014 Wibowo, A., & Wilhelm Alfen, H. 6
20 ECAM 2013 Weisheng, L., MM Liu, A., Hongdi, W., & Zhongbing, W. 14
21 ECAM 2004 Liu, A. M., Fellows, R., & Ng, J. 38
22 ECAM 2011 Ke, Y., Wang, S., Chan, A. P., & Cheung, E. 38
23 ECAM 2007 Man-Fong Ho, C. 24
24 IJPM 2009 Sichombo, B., Muya, M., Shakantu, W., & Kaliba, C. 21
25 IJPM 2010 Corvellec, H., & Macheridis, N. 21
26 IJPM 2013 Hwang, B. G., Zhao, X., & Gay, M. J. S. 67
27 IJPM 2015 Zeng, S. X., Ma, H. Y., Lin, H., Zeng, R. C., & Tam, V. 7
28 IJPM 1995 Zhi, H. 333
29 IJPM 1987 Stuckenbruck, L. C., & Zomorrodian, A. 33
30 JME 2012 Olawale, Y., & Sun, M. 11
31 JME 2005 Xu, T., Smith, N. J., & Bower, D. A. 32
32 JME 2014 Le, Y., Shan, M., Chan, A. P., & Hu, Y. 10
33 JME 2016 Zhang, B., Le, Y., Xia, B., & Skitmore, M. -
34 LME 2009 Stansbury, C. 3
35 LME 2009 Hartley, R. 6
36 LME 2009 Smith, J. H. 2
37 LME 2009 de Jong, M., Henry, W. P., & Stansbury, N. 20
38 PICE-CE 2012 Kenny, C. 2
39 SP* 2016 Transparency International -

378
 Appendix C

SELECTED JOURNAL PAPERS ON CAUSES OF CORRUPTION

Appendix E: Selected Papers with associated journals (Causes of Corruption)

No. Journal Year Authors Citation
1 JCEM 2005 Zhang, X 116
2 JCEM 2009 Iyer, K. C., & Sagheer, M. 85
3 JCEM 2014 Le, Y., Shan, M., Chan, A. P., & Hu, Y. 13
4 CME 2012 Ling, F. Y. Y., & Tran, P. Q. 21
5 CME 2004 Yow Thim, L. A. M., & Zonggui, C. 46
6 ECAM 2015 Brown, J., & Loosemore, M. 2
7 IJPM 2014 Ning, Y. 10
8 IJPM 2014 Ling, F. Y. Y., Ong, S. Y., Ke, Y., Wang, S., & Zou, P. 22
9 IJPM 1987 Stuckenbruck, L. C., & Zomorrodian, A. 33
10 CME 2008 Sohail, M., & Cavill, S. 61
11 CME 2012 Bowen, P. A., Edwards, P. J., & Cattell, K. 26
12 CME 2011 Tabish, S. Z. S., & Jha, K. N. 28
13 BRI 2000 Bologna, R., & Del Nord, R. 20
14 BRI 2004 Dorée, A. G. 107
15 JME 2003 Chan, A. P., Chan, D. W., & Ho, K. S. 131
16 JME 2016 Zhang, B., Le, Y., Xia, B., & Skitmore, M. -
17 JME 2014 Le, Y., Shan, M., Chan, A. P., & Hu, Y. 11
18 IMF* 1998 Tanzi, V. 2061
19 ECAM 2004 Liu, A. M., Fellows, R., & Ng, J. 38
20 CME 2008 Moodley, K., Smith, N., & Preece, C. N. 50
21 CME 2000 Zarkada-Fraser, A., & Skitmore, M. 68
22 PIEEP 2007 Alutu, O. E. 12
23 PIEEP 1993 Porter, J. C. 1
24 PIEEP 2016 Shan, M., Chan, A. P., Le, Y., Hu, Y., & Xia, B. -
25 PIEEP 1983 Damit, A. P. -
26 PIEEP 2008 King, W. S., Duan, L., Chen, W. F., & Pan, C. L. 9
27 PIEEP 2009 Fan, L. C., & Fox, P. W. 21
28 PIEEP 2015 Shan, M., Chan, A. P., Le, Y., Xia, B., & Hu, Y. 7
29 LME 2009 Boyd, J. M., & Padilla, J. D. 4
30 LME 2009 Hartley, R. 7
31 LME 2009 de Jong, M., Henry, W. P., & Stansbury, N. 21
32 LME 2009 Krishnan, C. 10
33 LME 2009 Stansbury, N. 1
34 IJPM 2016 Locatelli, G., Mariani, G., Sainati, T., & Greco, M. -

379
 Appendix D

SELECTED JOURNAL PAPERS ON ANTI-CORRUPTION MEASURES

Appendix F
No. Journal Year Authors Citation
1 JME 2014 Le, Y., Shan, M., Chan, A., and Hu, Y. 10
2 JCEM 2014 Le, Y., Shan, M., Chan, A. P., & Hu, Y. 12
3 JME 2016 Zhang, B., Le, Y., Xia, B., & Skitmore, M 0
4 CME 2012 Bowen, P. A., Edwards, P. J., & Cattell, K. 23
5 CME 2012 Tabish, S. Z. S., & Jha, K. N. 12
6 CME 2011 Tabish, S. Z. S., & Jha, K. N. 25
7 CME 2008 Sohail, M., & Cavill, S. 59
8 JCEM 2012 Valdes-Vasquez, R., & Klotz, L. E. 56
9 JCEM 2012 Ho, C. M. 9
10 JCEM 1998 Shen, L., & Song, W. 56
11 LME 2009 Hartley, R. 6
12 LME 2009 Krishnan, C. 10
13 LME 2009 Boyd, J. M., & Padilla, J. D. 4
14 PICE-CE 2006 Sohail, M., and Cavill, S. 5
15 PICE-CE 2012 Kenny, C. 2
16 IJPM 2009 Sichombo, B., Muya, M., Shakantu, W., & Kaliba, C. 21
17 JME 2011 Rebeiz, K. S. 27
18 PICE-CE 2012 Hawkins, J., & McKittrick, B. 3
19 LME 2009 de Jong, M., Henry, W. P., & Stansbury, N. 19
20 LME 2009 Stansbury, C. 3
21 LME 2009 Stansbury, N. 1
22 CME 2007 Bowen, P., Akintoye, A., Pearl, R., & Edwards, P. J. 54
23 JCDC 2006 Zou, P. X 27
(SP)*
24 SP 1998 Tanzi, V. 1991
25 SP 2002 Søreide, T. 25
26 IJPM 2007 Suen, H., Cheung, S. O., & Mondejar, R. 53
27 LME 2009 Tashjian L 0
28 IJPM 2014 Ling, F. Y. Y., Ong, S. Y., Ke, Y., Wang, S., & Zou, P. 20
29 ECAM 2015 Brown, J., & Loosemore, M. 2
30 PIEEP 1993 Porter, J. C. 1
31 PIEEP 2007 Alutu, O. E. 12
32 PIEEP 2008 King, W. S., Duan, L., Chen, W. F., & Pan, C. L. 9
33 CE 2006 Powell, S. 5
34 CE 2006 Shakantu, W. 30

380
 Appendix E

SELECTED JOURNAL PAPERS ON HONG KONG

Appendix: Selected papers with their corresponding journals

No Year Journal Authors Citation

1995 IJPA Shafiqul Huque, A. 3
1995 CJWB Lee, M. Q. 14
1997 JFC Bishop, Mike 2
1999 TOC Lo, T. W. 1
1999 JCC Moran, J. 9
1999 BEQ Snell, R. S. 45
1999 JBE Snell, R. S., Chak, A. M. K., & Chu, J. W. H. 44
2000 PJM Snell, R. S., & Herndon Jr, N. C 40
2001 JCCM Lo, J. M. 11
2001 JCE Mo, P. H. 840
2003 WSP Kim, T. 11
2004 GER Li, S. 1
2007 PAD Marquette, H. 12
2008 RPAM Cheung, A. B. 8
2008 JBE Donleavy, G. D., Lam, K. C. J., & Ho, S. S. 18
2008 CLSC Lo, T. W., & Ngan, P. 2
2009 JFC Young, S. N. 8
2010 APR De Speville, B. 16
2010 JBE Ho, C., & Redfern, K. A. 55
2010 AJC Jiao, A. Y. 5
2010 SAPM Wong, W. -
2011 CUP Donald, D. C. -
2012 PPM Luk, S. C. Y. 11
2012 OUP Raj Kumar, C. -
2012 LSC Scott, I., & Leung, J. Y 19
2013 JHG Chu, C. 2
2013 SIR Gong, T., & Wang, S 22
2013 APJM Mao, Y., Wong, C. S., & Peng, K. Z 5
2013 RPP Quah, J. S. 4
2013 PPAM Scott, I. 3
2013 JCC Scott, I. 14
2013 CI Yep, R. 5
2014 JCCA Lin, M. W., & Yu, C. 9
2015 IPMJ Gong, T., Wang, S., & Ren, J. 3
2015 AJPS Holmes, L. -
2015 CPE Ip, E. C. -
2015 CUP Jones, C. A. G. -
2015 JFC Michael, B. -
2015 SB Scott, I. -
2015 AE Weng, W. W., Woo, C. K., Cheng, Y. S., Ho, T., & Horowitz, 2
I.
2016 JDS Hira, A 2
2016 CCR Lee, M. H., & Lio, M. C. -
2016 CLSC Li, L. 1
2016 AG Warf, B. -

381
 Appendix F

Table 2: Information on selected papers

No Journal/Pu Year Authors Type of study No. of respondents Study context Methodology
. blisher

1 JME, 2017 Ameyaw, E. E., Pärn, E., Empirical 35 Ghana Descriptive (Mean
ASCE Chan, A. P., Owusu-Manu, Scores and Frequency),
D. G., Edwards, D. J., & purposive
Darko, A.

2 CME, 2011 Tabish, S. Z. S., & Jha, K. N Empirical 6 India Delphi approach
Descriptive (Mean
Taylor and Scores and Frequency),
Francis purposive

3 IJPM, 2017 Locatelli, G., Mariani, G., Review study - Italy Case analysis
Elsevier Sainati, T., & Greco, M.

4 SEE, 2017 Owusu, E. K., Chan, A. P., & Review study - International Content and thematic
Springer Shan, M. analysis.

5 JCEM, 2017 Chan, A. P., & Owusu, E. K. - International Content and thematic
ASCE analysis.

6 CME, 2007 Bowen, P., Edwards, P., & Empirical 107 out of 193 South Africa Frequency with
Cattell, K. study through a stratified respective percentages
Taylor and random sampling and descriptive
Francis

7 JCDC 2006 Zou, P. X. Empirical 14 China Qualitative analysis,

focus-group workshops
and face-to-face
interviews

8 JME, 2014 Le, Y., Shan, M., Chan, A. Review study - International Document/content
ASCE P., & Hu, Y. analysis.

9 JPIEEP, 1992 Porter, J. C. Review study - International Document/content

ASCE analysis

10 CME, 2012 Bowen, P. A., Edwards, P. J., Empirical 493 out of 11,608 South Qualitative: Thematic
& Cattell, K. (2012) study (Random African analysis
Taylor and Sampling)
Francis

11 JCEM, 2009 Iyer, K. C., & Sagheer, M. Empirical 4 India Interpretative

ASCE (2009 Study
Structural Modeling
analysis after purposive
sampling.

12 LME, 2009 Stansbury, N. (2009). Review study - The United Review

ASCE Kingdom

13 IJMPB, 2010 Osei-Tutu, E., Badu, E., & Review Study - Ghana Case with
Emerald Owusu-Manu, D. (2010). Document/content
analysis

14 SEE, 2015 Shan, M., Chan, A. P., Le, Empirical 188 China Factor analysis and
Springer Y., & Hu, Y. (2015a) Study partial

Least squares-structural
equation modeling

382
15 SEE, 2017 Shan, M., Le, Y., Yiu, K. T., Empirical 188 China Factor analysis and
Springer Chan, A. P., & Hu, Y. Study partial
(2017).
Least squares-structural
equation modeling

16 JCEM, 2008 Sohail, M., & Cavill, S. Review Study - International Reports review
ASCE (2008). Document/content
analysis

17 LME, 2009 Krishnan, C. (2009). Review Study - International Case reports

ASCE

18 AA, Wiley 2013 Tidey, S. (2013) Review Study - Indonesia Document/content

analysis

19 JPIEEP, 2009 Alutu, O. E. (2007). Empirical 200 out of 760 Nigeria Frequency with
ASCE study (Random respective percentages
Sampling) and descriptive

Notes: Full references are found in the referencing list. Abbreviations are listed as follows: JME - Journal of Management in Engineering; ASCE -
American Society of Civil Engineers; CME - Construction Engineering and Management; IJPM - International Journal of project management;
SEE - Science and engineering ethics; JCEM - Journal of construction engineering and management; JCDC - Journal of construction in
Developing Countries; JPIEEP - Journal of Professional Issues in Engineering Education and Practice; LME - Leadership and Management in
Engineering; IJMPB - International Journal of Managing Projects in Business; AA - American Anthropologist.

383
 Appendix G

SELECTED REPORTS ON GHANA PUBLIC AUDIT

The Public Accounts of Ghana Ministries, Departments and Other Agencies (MDAs)

GHANA

Reports References

1. Ghana Audit Service, GAS (2005a). Report of the Auditor-General on the Public Accounts of Ghana
Ministries, Departments and other Agencies (MDAs) for the Financial Year Ended 31 December
2005 (For 2005 and 2004), available at: www.ghaudit.org/gas/site/reports/download_report/475,
(accessed 2 December 2016)
2. Ghana Audit Service, GAS (2005b). Report 0f the Auditor-General on the Public Accounts of Ghana –
Public Boards, Corporations and other Statutory Institutions for the Period Ended 31 December
2005, available at: www.ghaudit.org/gas/site/reports/download_report/436, (accessed 4 December
2016)
3. Ghana Audit Service, GAS (2006a). Report of the Auditor-General on the Public Accounts of Ghana
Ministries, Departments and other Agencies (MDAs) for the Financial Year Ended 31 December
2006, available at: www.ghaudit.org/gas/site/reports/download_report/437, (accessed 9 December
2016)
4. Ghana Audit Service, GAS (2006b). Report 0f the Auditor-General on the Public Accounts of Ghana –
Public Boards, Corporations and other Statutory Institutions for the Period Ended 31 December
2006, available at: www.ghaudit.org/gas/site/reports/download_report/28, (accessed 9 December
2016)
5. Ghana Audit Service, GAS (2007a). Report of the Auditor-General on the Public Accounts of Ghana
Ministries, Departments and other Agencies (MDAs) for the Financial Year Ended 31 December
2007, available at: www.ghaudit.org/gas/site/reports/download_report/439, (accessed 10 December
2016)
6. Ghana Audit Service, GAS (2007b). Report 0f the Auditor-General on the Public Accounts of Ghana –
Public Boards, Corporations and other Statutory Institutions for the Period Ended 31 December
2007, available at: www.ghaudit.org/gas/site/reports/download_report/23, (accessed 10 December
2016)
7. Ghana Audit Service, GAS (2008a). Report of the Auditor-General on the Public Accounts of Ghana
Ministries, Departments and other Agencies (MDAs) for the Financial Year Ended 31 December
2008, available at: www.ghaudit.org/gas/site/reports/download_report/431, (accessed 12 December
2016)
8. Ghana Audit Service, GAS (2008b). Report 0f the Auditor-General on the Public Accounts of Ghana –
Public Boards, Corporations and other Statutory Institutions for the Period Ended 31 December
2008, available at: www.ghaudit.org/gas/site/reports/download_report/21, (accessed 12 December
2016)
9. Ghana Audit Service, GAS (2011a). Report of the Auditor-General on the Public Accounts of Ghana
Ministries, Departments and other Agencies (MDAs) for the Financial Year Ended 31 December
2011 (For 2011 and 2010), available at: www.ghaudit.org/gas/site/reports/download_report/473,
(accessed 12 December 2016)
10. Ghana Audit Service, GAS (2011b). Report 0f the Auditor-General on the Public Accounts of Ghana –
Public Boards, Corporations and other Statutory Institutions for the Period Ended 31 December
20011, available at: www.ghaudit.org/gas/site/reports/download_report/451, (accessed 13
December 2016)
11. Ghana Audit Service, GAS (2013). Report of the Auditor-General on the Public Accounts of Ghana
Ministries, Departments and other Agencies (MDAs) for the Financial Year Ended 31 December
2013, (For 2013 and 2012) year of release 2014, available at:
www.ghaudit.org/gas/site/reports/download_report/503, (accessed 14 December 2016)
12. Ghana Audit Service, GAS (2014). Report of the Auditor-General on the Public Accounts of Ghana
Ministries, Departments and other Agencies (MDAs) for the Financial Year Ended 31 December
2014, Year Of Release 2016 available at: www.ghaudit.org/gas/site/reports/download_report/518,
(accessed 15 December 2016)

384
 Part A: Procurement Irregularities Factors in Public Infrastructure Procurement

Table 1: Established variables for Procurement Irregularities

Code Procurement Irregularities P-M S-M Sig. I Impact N-V Rank Criticality
PI-1 Payments for uncompleted works 3.85 3.84 14.78 3.84* 1.00 1 High
PI-2 Sourcing of proforma invoices from the 3.87 3.77 14.59 3.82* 0.96 2 High
same supplier (single sourcing)
PI-3 Lack of proper co-ordination among 3.73 3.68 13.73 3.70* 0.75 3 High
key departments of the company and
apparent internal control weaknesses
reconciliation on Association
PI-4 Institution not following correctly the 3.58 3.66 13.10 3.62* 0.61 4 High
public procurement Acts in terms of
obtaining minimum quotations,
exceeding authorization threshold limits
and unauthorized sole sourcing of
suppliers
PI-5 The procurement of goods and services 3.47 3.69 12.80 3.58* 0.54 5 High
by management without adequate
resources to procurements committee of
the various public institutions, which
diverges from the provided regulations
PI-6 Disregard for public procurement Acts 3.65 3.48 12.70 3.56* 0.51 6 High
regulations
PI-7 Lack of consistent monitoring and 3.66 3.45 12.63 3.55* 0.49 7 High
review of procurement activities
PI-8 Non-application of sanctions 3.61 3.48 12.56 3.54* 0.47 8 High
PI-9 Poor supervision of subordinate officers 3.56 3.48 12.39 3.52* 0.44 9 High
PI-10 Lack of whole-of-government and 3.50 3.48 12.18 3.49* 0.39 10 High
corporate procurement planning for
significant purchases
PI-11 Procurement not taken on ledger charge 3.63 3.31 12.02 3.47* 0.35 11 High
PI-12 Overpayment of purchases 3.58 3.35 11.99 3.46* 0.33 12 High
PI-13 Variations to contract 3.45 3.39 11.70 3.42 0.26 13 Moderate
PI-14 Little evidence of value for moneys 3.56 3.27 11.64 3.41 0.25 14 Moderate
spent
PI-15 Lack of audit trails or verification data 3.52 3.31 11.65 3.41 0.25 15 Moderate
PI-16 Lack of adequate supervisory control 3.39 3.44 11.66 3.41 0.25 16 Moderate
over procurement transactions and
management
PI-17 Fragmentary procurement 3.32 3.48 11.55 3.40 0.23 17 Moderate
PI-18 Outstanding Mobilization advances 3.18 3.37 10.72 3.27 0.00 18 Moderate
owing to non-observance of stipulated
regulations
5 - point scale; 1 = not critical and 5 = very
Risk significance index (Sig. I) = probability mean (P-M) × severity mean (S-M)
Risk impact = (risk significance index)0.5
N-V: Normalization (N) value = (actual mean-minimum mean)/(maximum mean-minimum mean)

386
Table 2: Variables for Contractual Irregularities
Code Contractual Irregularities P-Mean S-Mean Sig. I Impact N-V Rank Criticality
CI-1 Absence of transparency in the 3.64 3.64 13.25 3.64* 1.00 1 High
disbursement of funds and
award of contracts
CI-2 Delay in construction 3.51 3.67 12.88 3.59* 0.95 2 High
CI-3 Failure on the part of public 3.66 3.52 12.88 3.59* 0.95 2 High
enterprises to award contracts
to competent contractors
CI-4 Delayed execution of contract 3.56 3.61 12.85 3.58* 0.94 4 High
works
CI-5 Ineffective control over 3.56 3.41 12.14 3.48* 0.83 5 High
contracts
CI-6 Failure to exercise due 3.55 3.40 12.07 3.47* 0.82 6 High
diligence in the award of
contracts
CI-7 Unsettled mobilization fee due 3.58 3.34 11.96 3.46* 0.81 7 High
on abandoned
CI-8 Contract lapses include non- 3.52 3.41 12.00 3.46* 0.81 7 High
tendering of contracts and
items paid for but not supplied
CI-9 Contract management 3.47 3.29 11.42 3.38 0.72 9 Moderate
loopholes
CI-10 Payments for work not 3.27 3.31 10.82 3.29 0.63 10 Moderate
certified
CI-11 Outstanding refund of 3.32 3.26 10.82 3.29 0.63 10 Moderate
mobilization advances
CI-12 Unexecuted contracts 3.26 3.18 10.37 3.22 0.55 12 Moderate
CI-13 Non-specification of the mode 3.36 3.08 10.35 3.22 0.55 12 Moderate
of payment and deliveries in
contract agreements
CI-14 Inadequate supporting 3.19 3.18 10.14 3.18 0.51 14 Moderate
documents for contract
payments
CI-15 Failure to comply with 3.29 3.03 9.97 3.16 0.49 15 Moderate
tendering procedures
CI-16 Discrepancies of conditions of 2.98 3.36 10.01 3.16 0.49 15 Moderate
contract owing to disregards
for stipulated procedures
CI-17 Unapproved contracts 3.16 3.03 9.57 3.09 0.41 17 Moderate
CI-18 Noncompliance to public 3.11 3.10 9.64 3.10 0.43 18 Moderate
procurement Acts (2003)
CI-19 Overpayment of contract sum 3.13 3.03 9.48 3.08 0.40 19 Moderate
CI-20 Absence of the signing of 2.87 3.02 8.67 2.94 0.26 20 Moderate
contract agreements
CI-21 Failure to retain 10%contract 2.65 2.76 7.31 2.70 0.00 21 Moderate
retention funds
5 - point scale 1 = not critical and 5 = very

387
 VALIDATION QUESTIONNAIRE
Please, kindly respond to separate questions on both contractual and procurement irregularities as
presented in the following page sections.
Questionnaire for Part A: Irregularities in Public Infrastructure Procurement
1. Please, kindly choose the suitable score for each validation aspect/question to indicate the extent of
your satisfaction: 1 – Poor; 2 – Average; 3 – Good; 4 – Very good; 5 – Excellent.
No. Validation Questions (on Procurement Irregularities) Evaluation Scale
1 Are the 18 procurement irregularities established, critical in the ☐1; ☐2; ☐3; ☐4; ☐5
Ghanaian infrastructure procurement?
2 Do the 18 procurement irregularities obscure the normal process of ☐1; ☐2; ☐3; ☐4; ☐5
infrastructure procurement in Ghana?
3 Can the 18 procurement irregularities established contribute or create ☐1; ☐2; ☐3; ☐4; ☐5
room for corruption to occur?
4 Can the impact of their criticalities have adverse effects on the general ☐1; ☐2; ☐3; ☐4; ☐5
economy?
5 Are the probability and severity rankings of the identified irregularities ☐1; ☐2; ☐3; ☐4; ☐5
reasonable?

No. Validation Questions (on Contractual Irregularities) Evaluation Scale

1 Are the 21 contractual irregularities established, critical in the Ghanaian ☐1; ☐2; ☐3; ☐4; ☐5
infrastructure procurement?
2 Do the 21 contractual irregularities obscure the normal process of ☐1; ☐2; ☐3; ☐4; ☐5
infrastructure procurement in Ghana?
3 Can the 21 contractual irregularities established contribute or create ☐1; ☐2; ☐3; ☐4; ☐5
room for corruption to occur?
4 Can the impact of their criticalities have adverse effects on the general ☐1; ☐2; ☐3; ☐4; ☐5
economy?
5 Are the probability and severity rankings of the identified irregularities ☐1; ☐2; ☐3; ☐4; ☐5
reasonable?

2. Among the listed 18 procurement and 21 contractual irregularities, which 6 can of each construct can
contribute most to the obscurity of the procurement process and as well render the process vulnerable to
the incidence of corrupt practice?
Rank Procurement Irregularity ID (e.g., PIR2) Rank Contractual Irregularity ID (e.g., CIR2)
1 1
2 2
3 3
4 4
5 5
6 6

3. Other comment (general or specific)

388
 Part B: Forms and Causes of Corruption in Public Infrastructure Procurement
1. Please, kindly choose the suitable score for each validation aspect/question to indicate the extent of
your satisfaction: 1 – Poor; 2 – Average; 3 – Good; 4 – Very good; 5 – Excellent.

Table 3: Forms of Corruption in the Ghanaian Procurement Public Sector

Code Variables Mean N-Value Sig Rank Criticality
CF1 Bribery 4.02 1.00 0.000 1 High
CF2 Lobbying 3.81 0.76 0.000 2 High
CF3 Price fixing 3.81 0.76 0.000 3 High
CF4 Facilitation payments 3.79 0.74 0.000 4 High
CF5 Bid rigging 3.76 0.70 0.000 5 High
CF6 Conflict of interest 3.74 0.68 0.000 6 High
CF7 Kickbacks 3.74 0.68 0.000 7 High
CF8 Favoritism 3.68 0.61 0.000 8 High
CF9 Solicitation 3.66 0.59 0.000 9 High
CF10 Influence peddling 3.65 0.57 0.000 10 High
CF11 Front/shell companies 3.63 0.55 0.000 11 High
CF12 Embezzlement 3.61 0.53 0.000 12 High
CF13 Nepotism 3.58 0.49 0.000 13 High
CF14 Collusion 3.58 0.49 0.000 14 High
CF15 Fraud 3.53 0.44 0.003 15 High
CF16 Professional negligence 3.52 0.43 0.004 16 High
CF17 Ghosting 3.52 0.43 0.001 17 High
CF18 Dishonesty 3.44 0.33 0.007 18 Moderate
CF19 Patronage 3.44 0.33 0.007 19 Moderate
CF20 Deception 3.37 0.25 0.020 20 Moderate
CF21 Coercion 3.34 0.22 0.047 21 Moderate
CF22 Blackmail 3.29 0.16 0.086 22 Moderate
CF23 Money laundering 3.27 0.14 0.129 23 Moderate
CF24 Cartels 3.26 0.13 0.081 24 Moderate
CF25 Extortion 3.24 0.10 0.125 25 Moderate
CF26 Client abuse/clientelism 3.19 0.05 0.223 26 Moderate
CF27 Intimidations and threats 3.15 0.00 0.327 27 Moderate

389
Table 4: Causes of corruption variables
Code Variables Mean N-V Rank Criticality
CC 1 Personal greed 3.92 1.00 1 High
CC 2 Inadequate sanctions 3.77 0.83 2 High
CC 3 Flawed regulation system 3.74 0.80 3 High
CC 4 Lack of coordination among Government 0.77 4 High
3.71
departments
CC 5 Inappropriate political interference 3.71 0.77 5 High
CC 6 Over close relationship 3.71 0.77 6 High
CC 7 Lack of legal awareness 3.69 0.74 7 High
CC 8 Lack of rigorous supervision 3.69 0.74 8 High
CC 9 Negative role models 3.66 0.71 9 High
CC 10 Insufficient legal punishment and penalties 3.66 0.71 10 High
CC 11 Lack of a positive industrial climate 3.61 0.66 11 High
CC 12 Poor documentation of records 3.61 0.66 12 High
CC 13 Lack of pro-active steps by funders to limit 0.64 13 High
3.60
corruption on projects
CC 14 Poor professional ethical standard 3.60 0.64 14 High
CC 15 Delaying the payment of workers" salaries 3.56 0.60 15 High
CC 16 Asymmetric information amongst project parties 3.55 0.59 16 High
CC 17 Great project complexity 3.55 0.59 17 High
CC 18 Subjecting workers to Job insecurity, especially in 0.56 18 High
3.52
government and public enterprises
CC 19 Transition of government 3.52 0.56 19 High
CC 20 Over competition in tendering process 3.50 0.53 20 High
CC 21 Multifarious license or permits 3.50 0.53 21 High
CC 22 Insufficient transparency in the selection criteria 0.53 22 High
3.50
for tenders
CC 23 Low wage level 3.50 0.53 23 High
CC 24 Absence of project anti-corruption systems 3.48 0.51 24 High
CC 25 Appointment of a local representative who acts on 0.48 25 High
3.45
behalf of the firm to obtain contracts
CC 26 Absence of control mechanism 3.44 0.47 26 Moderate
CC 27 Economic survival 3.40 0.42 27 Moderate
CC 28 Lack of frequency of projects 3.30 0.31 28 Moderate
CC 29 Deficiencies in rule and laws 3.29 0.30 29 Moderate
CC 30 Complexities of institutional roles and functions 3.29 0.30 30 Moderate
CC 31 Deregulation in the public construction 3.27 0.28 31 Moderate
CC 32 Absence of effective and responsible 0.27 32 Moderate
3.26
administrative systems
CC 33 Fierce competition 3.24 0.24 33 Moderate
CC 34 Weak procurement/contractual structures 3.23 0.23 34 Moderate
CC 35 Feeble semblance of public interest 3.16 0.16 35 Moderate
CC 36 Complex contractual structure 3.15 0.14 36 Moderate
CC 37 The nature of infrastructure 3.14 0.13 37 Moderate
CC 38 The nature of corruption being a secret activity 3.02 0.00 38 Moderate

390
 VALIDATION QUESTIONNAIRE
Please, kindly respond to separate questions on both contractual and procurement irregularities as
presented in the following page sections.
Questionnaire for Part B: Forms and Causes of Corruption in Public Infrastructure Procurement
1. Please, kindly choose the suitable score for each validation aspect/question to indicate the extent of
your satisfaction: 1 – Poor; 2 – Average; 3 – Good; 4 – Very good; 5 – Excellent.
No. Validation Questions (on forms of corruption) Evaluation Scale
1 Are the 27 forms of corruption prevalent in the process of infrastructure ☐1; ☐2; ☐3; ☐4; ☐5
procurement in Ghana?
2 Can the 27 forms established contribute to the forms of corruption in ☐1; ☐2; ☐3; ☐4; ☐5
the procurement sector?
3 Are the 27 forms of corruption established, critical in the Ghanaian ☐1; ☐2; ☐3; ☐4; ☐5
infrastructure procurement?
4 Do the impact of their criticalities have adverse effects on the ☐1; ☐2; ☐3; ☐4; ☐5
procurement sector and the general economy?
5 Are the rankings of the identified forms reasonable? ☐1; ☐2; ☐3; ☐4; ☐5

No. Validation Questions (on Causes of corruption) Evaluation Scale

1 Are the 38 causes of corruption established, critical in the Ghanaian ☐1; ☐2; ☐3; ☐4; ☐5
infrastructure procurement towards the incidence of corruption?
2 Do the 38 causes of corruption obscure the normal process of ☐1; ☐2; ☐3; ☐4; ☐5
infrastructure procurement in Ghana?
3 Can the 38 causes of corruption established contribute or create room ☐1; ☐2; ☐3; ☐4; ☐5
for corruption to occur?
5 Are the rankings of the identified causes reasonable? ☐1; ☐2; ☐3; ☐4; ☐5

2. Among the listed 27 forms and the 38 causes, which 6 of each construct can have extreme negative
impacts on the procurement process and as well render the process vulnerable to the incidence of corrupt
practice?

Rank Forms ID (e.g., CF2) Rank Causal Factors ID (e.g., CC2)

1 1
2 2
3 3
4 4
5 5
6 6

3. Other comment (general or specific)

391
 Part C: Anticorruption Measures and the Barriers to Effective Application of Anticorruption
Measures in Public Infrastructure Procurement
1. Please, kindly choose the suitable score for each validation aspect/question to indicate the extent of
your satisfaction: 1 – Poor; 2 – Average; 3 – Good; 4 – Very good; 5 – Excellent.

Table 5: Anti-corruption measures

Code Variables Mean N-V Rank Effectiveness
AC1 Good leadership 3.31 1.00 1 Moderate
AC2 Contract monitoring 3.24 0.84 2 Moderate
AC3 Professional associations 3.24 0.84 3 Moderate
AC4 Whistle-blowing mechanism 3.24 0.84 4 Moderate
AC5 Procedural compliance 3.19 0.73 5 Moderate
AC6 Information technology 3.11 0.55 6 Moderate
AC7 Efficient reporting system (independent 3.11 0.55 7 Moderate
hotline)
AC8 Rigorous supervision among others 3.10 0.52 8 Moderate
AC9 Raising awareness 3.08 0.48 9 Moderate
AC10 Rigorous technical auditing system 3.07 0.45 10 Moderate
AC11 Dismissal from employment or other 3.03 0.36 11 Moderate
disciplinary action
AC12 Enhance communication 3.03 0.36 12 Moderate
AC13 Education 3.03 0.36 13 Moderate
AC14 Harsh punishment or penalty 3.02 0.34 14 Moderate
AC15 Contractual compliance 3.00 0.30 15 Moderate
AC16 Compliance to fairness and transparent 2.98 0.25 16 Moderate
procedures
AC17 Comprehensive rules and regulations 2.98 0.25 17 Moderate
AC18 Training and development initiatives 2.97 0.23 18 Moderate
AC19 Transparency mechanism 2.97 0.23 19 Moderate
AC20 Ethical code 2.97 0.23 20 Moderate
AC21 Debarment/promoting fair debarment 2.94 0.16 21 Moderate
procedures
AC22 Increase in accountability 2.94 0.16 22 Moderate
AC23 Effective investigation, court proceedings, 2.92 0.11 23 Moderate
departmental disciplinary action
AC24 Access to information 2.90 0.07 24 Moderate
AC25 Financial disclosure/Disclosure 2.90 0.07 25 Moderate
AC26 Development of strong political and ethical 2.87 0.00 26 Moderate
will to enforce existing anti-corruption
policies and laws.

392
Table 6: Barriers to effective application of anti-corruption measures
Code Variables P-Mean S-Mean Sig Impact N-V Rank Criticality
BAC1 Lack of knowledge and 3.82 3.90 14.90 3.86* 1.00 1 High
understand of their rights
within a contractual
environment, difficulty in
providing concrete evidence
BAC2 Political and structural 3.65 3.95 14.42 3.80* 0.88 2 High
barriers
BAC3 Fear of insecurity which 3.77 3.82 14.40 3.79* 0.86 3 High
includes fear of losing Job
BAC4 Bureaucratic process of 3.69 3.82 14.10 3.75* 0.78 4 High
reporting corrupt cases
BAC5 Fear of victimization 3.81 3.56 13.56 3.68* 0.65 5 High
BAC6 Perception of no better end 3.74 3.63 13.58 3.68* 0.65 5 High
result, distrust in system
BAC7 Lack of political will, A 3.73 3.63 13.54 3.68* 0.65 5 High
lack of political will by
government officials and
statutory professional
councils to fight corruption
is seen as an exacerbating
factor
BAC8 Personal attitude, for 3.73 3.63 13.54 3.68* 0.65 5 High
example, lack of will to
become involved in fighting
corruption
BAC9 Lack of knowledge or non- 3.69 3.56 13.14 3.62* 0.53 6 High
familiarity with ethical
codes organizational codes
of ethics
BAC10 Inappropriate staffing 3.60 3.63 13.07 3.61* 0.51 10 High
BAC11 Social or occupational 3.48 3.61 12.56 3.54* 0.37 11 High
stigma and rejection
BAC12 Lack of independence 3.52 3.56 12.53 3.54* 0.37 11 High
BAC13 Fear of being marginalized 3.61 3.37 12.17 3.49* 0.27 13 High
BAC14 Social misrepresentation 3.39 3.42 11.59 3.40 0.10 14 Moderate
BAC15 Fear of being caught 3.39 3.37 11.42 3.38 0.06 15 Moderate
reporting
BAC16 Inappropriate internal 3.21 3.52 11.30 3.36 0.02 16 Moderate
institution
coordination/inter agency
relations
BAC17 Fear of losing life 3.44 3.27 11.25 3.35 0.00 17 Moderate

393
 VALIDATION QUESTIONNAIRE
Please, kindly respond to separate questions on both contractual and procurement irregularities as
presented in the following page sections.
Questionnaire for Part C: Anticorruption Measures and the Barriers to Effective Application of
Anticorruption Measures in Public Infrastructure Procurement
1. Please, kindly choose the suitable score for each validation aspect/question to indicate the extent of
your satisfaction: 1 – Poor; 2 – Average; 3 – Good; 4 – Very good; 5 – Excellent.
No. Validation Questions (on anti-corruption measures) Evaluation Scale
1 Are the 26 anti-corruption measures established, important towards the ☐1; ☐2; ☐3; ☐4; ☐5
eradication of corruption in the Ghanaian infrastructure procurement?
2 Are all 26 anti-corruption measures moderately effective in the ☐1; ☐2; ☐3; ☐4; ☐5
procurement process as rated by the respondents?
3 Can the 26 anti-corruption measures established contribute or create ☐1; ☐2; ☐3; ☐4; ☐5
transparency and accountability in the procurement process?
4 Can the impact of their effectiveness contribute to the good image of ☐1; ☐2; ☐3; ☐4; ☐5
the public procurement sector and the general economy?
5 Are the rankings of the identified forms reasonable? ☐1; ☐2; ☐3; ☐4; ☐5

No. Validation Questions (on Barriers to effectiveness of ACM) Evaluation Scale

1 Are the 17 barriers established, critical in the Ghanaian ☐1; ☐2; ☐3; ☐4; ☐5
infrastructure procurement?
2 Do the 17 barriers impede the effective application of and ☐1; ☐2; ☐3; ☐4; ☐5
enforcement of anti-corruption measures in the procurement process
in Ghana?
3 Can the 17 barriers established contribute or create room for ☐1; ☐2; ☐3; ☐4; ☐5
corruption to occur?
4 Can the impact of their criticalities have adverse effects on the ☐1; ☐2; ☐3; ☐4; ☐5
general economy?
5 Are the rankings of the identified causes reasonable? ☐1; ☐2; ☐3; ☐4; ☐5

2. Among the listed 26 anti-corruption measures and the 17 barriers established, which 6 of each
construct can have extreme impacts (both positive and negative respectively) on the procurement
process and as well contribute to transparency (Anti-corruption measures) or render the process
vulnerable to the incidence of corrupt practice in the case of the barriers?

Rank Anticorruption Measures ID (e.g., Rank Barriers ID (e.g., BAC1)

AC2)
1 1
2 2
3 3
4 4
5 5
6 6

3. Other comment (general or specific)

394
 Part D: Susceptibility of the procurement activities and stages to corrupt practices

Table 7: Activities and their respective stages of the procurement process

Procurement Process (TSa) ID Mean N-Value Weighting Vulnerability
1 Pre- Define requirements PCS1 2.63 0.00 0.133 Moderate
2 Contract Procurement process planning and PCS2 3.05 0.27 0.155 Moderate
stage strategy development
3 Pre-tender survey PCS3 3.15 0.33 0.160 Moderate
4 Obtaining necessary approvals PCS4 3.52 0.56 0.178 High
5 Soliciting tenders PCS5 4.02 0.88 0.204 High
6 Receipt of tenders PCS6 3.35 0.46 0.170 Moderate
7 Contract Pre-tender meeting (Establishing CTS1 3.40 0.49 0.182 Moderate
Stage Evaluation Criteria, Evaluation
Plan, Evaluation Criteria)
8 Tender evaluation (review to CTS2 4.00 0.87 0.214 High
approve or reject bids)
9 Select contractor CTS3 4.21 1.00 0.225 High
10 Award contract/Purchase order CTS4 3.74 0.70 0.200 High
11 Preparation and Signing of Contract CTS5 3.35 0.46 0.179 Moderate
12 Contract Issuing contract amendments CAS1 3.13 0.32 0.238 Moderate
13 administra Monitor Progress CAS2 3.39 0.48 0.257 Moderate
14 tion stage Follow up delivery CAS3 2.97 0.22 0.226 Moderate
15 (CAS) Administer Progress payments CAS4 3.68 0.66 0.279 High
16 Post File final action Contractor PCP1 3.48 0.54 0.165 High
contract agreement to final claim
17 phase Issue final contract amendment PCP2 3.51 0.56 0.167 High
18 Complete of financial audits PCP3 3.48 0.54 0.165 High
19 Check for proof of delivery PCP4 3.76 0.72 0.178 High
20 Return of performance bonds and PCP5 3.45 0.52 0.164 High
close-out
21 Ensure completeness and accuracy PCP6 3.39 0.48 0.161 Moderate
of file documentation

Questionnaire for Part D: Susceptibility of the procurement activities and stages to corrupt
practices
1. Please, kindly choose the suitable score for each validation aspect/question to indicate the extent of
your satisfaction: 1 – Poor; 2 – Average; 3 – Good; 4 – Very good; 5 – Excellent.
No. Validation Questions (on Procurement Irregularities) Evaluation Scale
1 Are the 21 procurement activities established, vulnerable to corrupt ☐1; ☐2; ☐3; ☐4; ☐5
practices?
2 Can all the 21 procurement activities established be plagues with ☐1; ☐2; ☐3; ☐4; ☐5
corrupt activities?
3 Can the impact of their vulnerabilities have adverse effects on the ☐1; ☐2; ☐3; ☐4; ☐5
procurement sector and the general economy?
4 Are the rankings of the identified activities and stages reasonable? ☐1; ☐2; ☐3; ☐4; ☐5

2. Among the listed 21 procurement activities established which 6 of each construct can have extreme
susceptibility to corrupt practices?
Rank Procurement Activities ID (e.g., PCP2)
1
2
3
4

395
 5
6

3. Other comment (general or specific)

-The End-
Please, we are very grateful for your valuable contribution and time spent on validating our
questionnaire. Please, if you would want to receive the final feedback of the validation, kindly provide
your email address here: _______________________________________________

396
 References

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