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Adoption of BIM Technologies for Facilities Management Roles in Nigeria: An Empirical

Investigation
Dubem Ikediashi1 and Joseph Uyanga2
1
Lecturer, Dept. of Building, Faculty of Environmental Studies, Univ. of Uyo, Nigeria. E-mail:
dubemikediashi@uniuyo.edu.ng
2
Professor, Dept. of Urban and Regional Planning, Faculty of Environmental Studies, Univ. of
Uyo, Nigeria. E-mail: joeuyanga @yahoo.com

ABSTRACT
Building information modelling (BIM) has been established as an emerging area of research
based on the proposition that the BIM process of digitally generating, presenting and managing
building information throughout the lifecycle of a facility can improve efficiency and
effectiveness of its management. However, although research has identified several BIM for
facilities management (FM) technologies, it is argued that the facilities manager is only
beginning to explore the full benefits and challenges of BIM for FM, while most of the standards
and software are in early stages of development. Within the context of emerging economies like
Nigeria, research efforts in the past have mainly focused on BIM at the design and construction
stages ignoring the very crucial operational stage, while most of them have relied on anecdotal
evidence to draw conclusion. The aim of this paper is to assess the current state of adoption of
BIM for FM roles in Nigeria with a view towards generating a proper understanding of the
current state of use and its effectiveness in FM service delivery. The specific objectives are to (1)
examine the level of use and effectiveness of BIM for FM applications in the Nigerian FM
industry; and (2) explore impact of these applications on FM service delivery. Findings reveal
among others, that (1) BIM for FM technologies especially CAFM and CMMS are the most
effective tool for asset management, energy and safety management, and inventory management,
while (2) the use of BIM for FM applications had significant influence on lifecycle cost
reduction and timely delivery of service. The study concludes with a reflection on the
implications of research findings both from theoretical and practical points of view.

INTRODUCTION
The construction industry is one of the most active sectors propelling the Nigerian economy.
It is so vital to the nation’s economic development that it produces nearly 70% of the country’s
fixed capital formation and accounts for 1.4% of the nation’s gross domestic product (GDP)
(World Bank 2013). Over the past two decades, there has been growing concern that the global
constriction industry is fraught with complexities, uncertainties, and ambiguous traditional
practices that has impeded knowledge sharing resulting in duplication of processes
(Khosrowshahi and Arayici 2012) while fragmentation and calcified processes have inhibited
needed widespread change in the industry (Aranda-Mena et al. 2009). In response, governments
around the world have devised regulatory strategies to bring about the needed efficiency and
flexibility by mandating the use of building information modelling (BIM) as a platform to
address the declining productivity (Kaseem et al. 2015). In the UK for instance, a key priority is
the mandatory use of data and management information to determine expected cost, drive out
waste, improve efficiency and allow the government to function as an intelligent client (Williams
2013). In effect, it mandated the adoption of BIM level 2 (federated models held in separate

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discipline “BIM” tools with attached data) on all centrally procured projects from 2016,
including the handover from the design and construction stage to operation and asset
management stage (soft landings) (Kaseem et al. 2015).
BIM is a generic term used to describe the process of digitally generating, representing and
managing buildings and information related to them using advanced 3D Computer Aided Design
(CAD). Information generated include geometry, space relationships, geographic information,
quantities and properties of building components while the digital tool enables projects to be
designed and built several times virtually, thereby rehearsing and optimising an asset’s lifecycle,
eliminating errors, waste and inefficiency (Philip 2012; Williams 2013). Although many are of
the view that BIM has brought in revolution into the construction industry, it can be argued that
BIM data captured during the project lifecycle can improve the effectiveness and efficiency of
facilities management (FM) functions. The is because the largest prize for BIM lies in the
operational phase of the project lifecycle (BIMTG 2013; Kaseem et al. 2015) while estimates
show that the lifecycle cost is five to seven times the initial investment costs and three times the
construction costs (BIMTG 2013). Therefore, collaboration between design, construction and
FM is not only necessary but pre-requisite for BIM to succeed.
The unstructured and late delivery of data and information to FM phase of buildings is a
recognised issue among researchers and industry practitioners (Patacas et al. 2015). Although
recent studies in the literature (Becerik-Geber et al. 2012; Parsanezhad and Dimyadi 2014;
Kaseem et al. 2015) have all identified the general BIM for FM technologies such as Computer-
based FM (CAFM), Construction Operations Building information exchange (COBie), and
Industry Foundation Classes (IFC), one contends that facilities managers are only beginning to
explore BIM for FM, while most of the standards and software are in early stages of
development. It is even more worrisome in Nigeria where FM is only beginning to pick up
momentum. Efforts in the past have mainly focused on BIM at the design and construction stages
in the Nigerian construction industry (Kuroshi and Omorogbe 2010; Alufohai 2012; Abubakar et
al. 2014) while most of them have relied on anecdotal evidence to draw conclusion. The need for
the study therefore stems from the fact that previous studies have not explored the use of BIM
for FM functions within the context of an emerging economy like Nigeria.
Given the background above, the research in this paper aims to assess the current state of
adoption of BIM for FM roles in Nigeria with a view towards generating a proper understanding
of the current state of use and its effectiveness in FM service delivery. The specific objectives are to
(1) examine the level of use of BIM for FM applications; and (2) explore impact of these applications
on FM service delivery within the context of the Nigerian FM industry. It is envisaged that the
outcome of the study will provide a proper understanding of the current state of use and effectiveness
of BIM for FM in Nigeria and establish any relationship between use of BIM applications and
FM service delivery thereby instilling confidence in the industry.

LITERATURE REVIEW
What is BIM: The various definitions of BIM available in the literature have been shaped by
difference in authors’ perceptions, pedigree, and experience base encompassing technology,
process and human dimensions (Coates et al. 2010). Below are few of such definitions that put
this study into proper perspective.
Gu and London (2010) defines BIM as an IT enabled approach that involves applying and
maintaining an integral digital representative of all building information for different phases of a
project lifecycle. Vanlande et al. (2008) defined BIM as the process of generating, storing,

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managing and sharing building information in an interoperable and reusable way. BIM is a
digital representation of physical and functional characteristics of a facility creating a shared
knowledge resource for information about it forming a reliable basis for decisions during its
lifecycle from earliest conception to demolition.
While there are several other definitions in the literature, the three above clearly demonstrate
the relevance of BIM at the operational stage of a building’s lifecycle and underscores the place
of BIM in FM roles. Going by the popular definition of FM as an integrated approach to
operating, maintaining, improving and adapting an organisation’s building and infrastructure
assets in order to support its core objectives to end users, owners and facilities managers (Atkin
and Brooks 2009), it suffices to say that, to effectively manage and operate buildings-in-use and
infrastructure assets, facilities managers would require extensive BIM data and information
captured during the planning, design and construction stage of a project’s lifecycle.
BIM for FM applications and FM service delivery: BIM is said not to be only
transforming the way building projects are designed and constructed, but has also changed how
buildings-in-use and related services are operated and managed. In this context, BIM-enabled
information systems are aimed to seamlessly convey the information from design and
construction models and databases to actors within the FM sector (Parsanezhad and Dimyadi
2014). Such BIM applications are capable of interacting with other digital tools that are already
in use in the FM industry and include computer-aided-facilities management (CAFM),
computerised maintenance management system (CMMS), building management system (BMS),
document management system (MDS), building automation system (BAS) among many others
within the industry (Parsanezhad and Dimyadi 2014). In particular, CAFM systems are a
combination of Computer-Aided Design (CAD) and relational database software aimed for space
management i.e. administering room numbers, departments, usable heights, room areas etc.
According to Molnar (2006), CAFM can further be categorised into 5 distinct groups as:
Infrastructure CAFM that deals with buildings and facilities, space and asset
management, where object oriented data bases are linked to CAD space-plan drawings
for detailed information on space utilisation needs;
H&S and Environmental management that deals with energy management, emissions,
fire, emergency, environmental impact assessment (EIA), integrating building control
systems and meters across sites;
Maintenance, repairs and contract management that involves operation and maintenance
(O&M) history of all plants and equipment, lifecycle maintenance, planned preventive
maintenance (PPM), malfunctioning alert on plants and equipment;
Helpdesk, service desk, IT and security management deal with fault reporting and
resolution service, CCTV monitoring, motion detectors, alarms etc.;
Financial, budget and inventory management which involves management of cost
associated with capital and current assets including lifecycle costing, consumables, stock
tracking, measurement and forecasting at strategic levels.
Although other FM applications such as CMMS, BMS, MDS, and BAS are useful in
articulating the concept of building information gathering and processing, CAFM has been the
most preferred among researchers and practising facilities managers due to improved processing
and efficiency, data quality and cost savings.
One of the key objectives of BIM is to provide opportunities for integrating FM phase with
downstream project delivery phases of design and construction. This is because information and
data emanating from different sources are created and manipulated several times during the

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asset’s life cycle, are not synchronised between systems, resulting in error-prone processes
(Becerik-Gerber et al. 2012). To address these, many platforms are being developed to foster
open standards and interoperability across the information supply chain in the construction
industry. According to Patacas et al. (2015), Construction Operations Building information
exchange (COBie) which is a simplified non geometric subset of Industry Foundation Classes
(IFC), provides the capability to capture FM data requirements in a structured manner from the
early stages of project development.
COBie facilitates organising, documenting and sharing of building information in a
standardised way and helps to capture and record project handover data entered during design,
construction and commissioning stages (East 2014).
FM service delivery in the context of this study is the group of measurable attributes of FM
services which an organisation can use to track performance. Traditionally, researchers have
focused on three major criteria of cost, time and quality as benchmark for assessing performance
of projects. There is plausible evidence to show that despite the inhibiting factors associated with
BIM for FM, there are several ways in which it adds value to FM in terms of time, cost and
quality performance. For instance, data regarding space, systems, finishes, H&S, emergency
management can be captured in digital format within BIM and do not necessarily need to be
recreated in downstream FM system (Eastman et al. 2011) thereby reducing time and cost
required to collect and build FM systems during the building lifecycle.(IFMA 2013). Researchers
such as Huber et al. (2011) and Volk et al. (2014) also argue that the use of laser scanning
technology associated with BIM reduces cost of producing as built building information.
Additionally, adoption of BIM for FM roles implies that facilities managers are integrated into
the building lifecycle at a much earlier stage usually the design stage to convey their input and
expertise on issues of build ability and maintainability. The outcome is improved quality of
output (buildable designs and maintainable facilities) and satisfaction of stakeholders including
the clients.

RESEARCH METHODOLOGY
The purpose of the study contained in this paper was to investigate the current state of
adoption of BIM for FM roles in Nigeria with a view towards generating a proper understanding
of the current state of use and its effectiveness in FM service delivery.
In line with quantitative field survey adopted for this study, a self-completion questionnaire
was administered to 150 stakeholders (facilities managers, maintenance managers and property
managers) who are registered members of International Facilities Management Association
(IFMA), Nigeria’s chapter in three strategic cities of Lagos, Port Harcourt (PH) and Abuja. The
150 respondents comprising Lagos (70), PH (50) and Abuja (30) were drawn from the register of
IFMA, Nigeria’s chapter using purposive sampling technique. The technique was adopted to
enable the researcher draw out target respondents who possess knowledge of BIM and FM
applications such as CAFM and CMMS. Lagos was chosen because it is the centre of business
and commerce in Nigeria while PH was adopted because it is the home of major oil
multinationals and major stakeholder in the Nigeria FM industry. Abuja remains the capital of
Nigeria and one of the fastest developing cities in the world in terms of infrastructure.
Respondents were asked closed ended questions relating to (1) their backgrounds and that of
their organisations (2) BIM for FM applications and their impact on FM service delivery, and (3)
factors inhibiting full adoption of BIM for FM roles. A five point Likert scale (of 1=very low,
2=low, 3=moderate, 4=high, 5=very high) was used to measure attributes of the study variables.

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Data collected were processed using the statistical package for social sciences (SPSS) version 22.
Specifically, descriptive and inferential statistics were used to analyse demographics of
respondents, level of adoption of BIM for FM. The correlation between BIM for FM use and FM
service delivery was analysed with the help of spearman rank correlation.

RESULTS AND FINDINGS

Profile of survey respondents and their organisations: The result of analysis indicates
that, of the 150 respondents, 68 comprising Lagos (32), Port Harcourt (23) and Abuja (13)
returned copies of completed questionnaire giving a cumulative response rate of 45%. Besides,
in terms of job description, 38 were facilities managers, 21 were maintenance managers while 9
were property managers. In terms of years of experience in FM, 11 had experience of between 0
and 10 years, 39 had experience of between 10 and 20 years, 16 had experience of between 20
and 30 years while only 2 had over 30 years of experience. It is worth noting that over 80% of
respondents who returned valid questionnaires had experience of between 10 and 20 years. This
is an indication that the respondents had the requisite experience and knowledge about BIM and
FM thereby demonstrating reliability in their judgements and opinions about BIM and FM.
Meanwhile, the respondents were of 7 different organisations including oil exploration and
servicing (18), manufacturing (14), telecommunication (14) and government corporations (12).
Others are FM companies (8), educational institutions (1) and construction (1). The oil industry
had the highest number of respondents. This is attributed to widely held view that the practice of
FM was introduced into the country as a result of relocation of two foremost multinational oil
companies, namely, Chevron and Mobil in the early 1980s (Ikediashi et al. 2014).
(1) Use of BIM for FM applications. In order to explore the extent of use of BIM for FM
applications, respondents were asked to (1) indicate how BIM data are loaded into FM
applications in their organisations and (2) rate the frequency of use of the applications. 55 of the
68 respondents representing 81% indicated that although they have knowledge about COBie and
IFC, they (the BIM platforms) have never been applied in their organisations. However, 5
respondents (7%) admitted to using COBie while 8 (12%) admitted to using IFC. All the 13
respondents were from the oil and manufacturing sectors (see Table 1).

Table 1.Results of Analysis on Frequency of Use of FM Applications.

S/n FM Application MS Standard Deviation Rank
1 CAFM 4.32 0.84 1
2 CMMS 4.18 0.77 2
3 BMS 3.16 1.15 4
4 DMS 3.22 1.03 3
5 BAS 2.89 1.22 5

The results on the frequency of use of 5 BIM for FM applications presented in Table 1
indicate that CAFM received the highest mean score (MS) of 4.32 with standard deviation (SD)
of 0.84, followed by CMMS with a MS of 4.18 and SD of 0.77. DMS was rated third with a MS
of 3.22 and SD of 1.03. BAS was the least rated with a MS of 2.89 and SD of 1.22.
(2) Effectiveness of BIM for FM applications for FM roles. In order to examine the
effectiveness of BIM for FM applications, respondents were asked to rate the level of
effectiveness of the 5 applications for 10 FM roles derived from literature. The result of analysis
is presented in Table 2.

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The result indicates that BIM for FM applications have been most effective in asset
management (MS=4.49, SD=0.32), energy and safety management (MS=4.44, SD=0.58), and
inventory management (MS=4.29, SD=0.64) as the three most rated while the three least rated
were cleaning (MS=4.22, SD=0.57), H&S (4.10, SD=0.67), and financial management (3.39,
SD=0.52). However, a cross tabulation carried out to examine the nature of relationship between
extent of use of BIM for FM applications and their effectiveness for the given FM roles indicates
that 64 of the 68 respondents agree that CAFM is the most effective for asset management, 63 of
them agree that it is the most effective for energy and safety management, while 63 of the 68
respondents agree that it is the most effective for inventory management. Meanwhile, it is
important to quickly point out that, 9 out of the 10 FM roles used for the study received high
scores of over 4 points which is an indication that BIM for FM applications have been very
effective in the FM industry.

Table 2.Results of Analysis on Level of Effectiveness of FM Applications for FM Roles.

S/n FM Roles MS Standard Deviation Rank
1 Asset management 4.49 0.32 1
2 Space management 4.24 0.58 7
3 Health and Safety (H&S) 4.10 0.67 9
4 Operation and maintenance (O&M) 4.25 0.66 6
5 Security & IT management 4.28 0.57 4
6 Financial management 3.39 0.52 10
7 Project management 4.26 0.51 5
8 Energy & Safety management 4.44 0.58 2
9 Cleaning 4.22 0.57 8
10 Inventory management 4.29 0.64 3

Impact of extent of use on FM service delivery: In order to explore how the use of BIM for
FM applications has impacted on FM service delivery, a hypothesis is postulated as follows:
H0: There is no significant correlation between the level of use of BIM for FM applications
and FM service delivery
Respondents were then asked to indicated the level to which the use of BIM for FM
applications have impacted FM service delivery operationalized as four dimensional constructs
of life cycle cost reduction, timely delivery of services, quality of output, and stakeholders
satisfaction. For the purpose of the evaluation, the 5 BIM for FM applications were correlated
with the 4 constructs of FM service delivery using spearman’s rank correlation. The decision rule
is that the hypothesis is accepted for all values of p>0.05 while it is rejected for all values of
p<0.05. The result of analysis is shown in Table 3.
The result form Table 3 shows that DMS and BAS have no significant correlation with any
of the FM service delivery variables with p-values ranging from 0.195 to 0.895. On the contrary,
the tests of correlation between CAFM and cost reduction as well as quality output; CMMS and
cost reduction as well as timely delivery of FM services; and BMS and cost reduction had p-
values lower than the significant level. Therefore, the rejection of the hypothesis is an indication
that (1) the use of CAFM has significant influence on lifecycle cost reduction and timely
delivery of FM services but not on quality of output and stakeholder satisfaction (2) the use of
CMMS has significant influence on cost reduction and timely delivery of services but no
influence on quality of output and stakeholder satisfaction, (3) BMS has significant influence on
lifecycle cost reduction.

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Table 3. Results of Correlation Analysis of Level of Use of FM Applications on FM Service

Delivery.
Correlated Item MS SD R-value P-value Decision
CAFM 4.32 0.84
Cost reduction 4.28 0.59 0.252 0.038 Reject
Timely delivery 4.25 0.56 0.098 0.427 Accept
Quality output 4.21 0.74 0.304 0.021 Reject
Stakeholder satisfaction 4.41 0.65 -0.064 0.607 Accept
CMMS 4.18 0.77

Cost reduction 4.28 0.59 0.233 0.032 Reject

Timely delivery 4.25 0.56 0.188 0.004 Reject
Quality output 4.21 0.74 -0.081 0.514 Accept
Stakeholder satisfaction 4.41 0.65 0.047 0.705 Accept
BMS 3.16 1.15
Cost reduction 4.28 0.59 0.358 0.003 Reject
Timely delivery 4.25 0.56 0.099 0.421 Accept
Quality output 4.21 0.74 0.051 0.678 Accept
Stakeholder satisfaction 4.41 0.65 0.118 0.336 Accept
DMS 3.22 1.03
Cost reduction 4.28 0.59 0.159 0.195 Accept
Timely delivery 4.25 0.56 0.105 0.393 Accept
Quality output 4.21 0.74 0.114 0.355 Accept
Stakeholder satisfaction 4.41 0.65 0.114 0.355 Accept
BAS 2.87 1.22
Cost reduction 4.28 0.59 0.132 0.282 Accept
Timely delivery 4.25 0.56 0.016 0.895 Accept
Quality output 4.21 0.74 0.105 0.394 Accept
Stakeholder satisfaction 4.41 0.65 0.113 0.360 Accept
Note: R=Spearman’s rank correlation coefficient; SD=Standard deviation; P=degree of significance.

Discussion and Implications: The result on the general level of use of BIM for FM
technologies in the Nigerian FM industry suggests CAFM is the most frequently used FM
application. The findings which is consistent with previous studies (Williams 2013; Becerik-
Gerber et al. 2012; Patacas et al. 2015) confirms the acclaimed use of the application for
achieving transparency in information flow, easy access to data, while also ensuring reduction in
operational cost at both short and long term. Findings also indicates that BIM for FM
applications have been most effective in asset management, energy and safety management, and
inventory management as the three most rated. It is a plausible indication that BIM for FM
technologies support both operational and strategic FM amongst organisations within the
Nigeria’s FM industry.
The significant influence of CAFM and CMMS on both cost reduction and timely delivery of
FM services may be linked to the widely held view among researchers (IFMA 2013; Huber et al.
2011; Volk et al. 2014) and practitioners that they are the most preferred due to their improved
processing and efficiency, data quality and cost savings. The acceptance of the null hypothesis
for DMS and BAS on FM service delivery may be due to the fact that they are not as popular as
the other three BIM for FM applications among the respondent organizations in the Nigerian

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economy.
This study complements the body of knowledge on BIM and FM. It has provided the first
ever insight into the relationship between use of BIM for FM technologies and FM services
delivery. For instance, consistent with previous studies, it has established key positive
relationships between use of CAFM & CMMS, and life cycle cost reduction as well as timely
delivery of services. With regards to practice, findings from this research has provided facilities
managers and stakeholders alike with key information on the component of FM delivery where
the use of BIM for FM technologies has impacted positively.

CONCLUSION
Based on a questionnaire survey of 68 respondents, this research explored the level of use of
BIM for FM technologies in the Nigerian FM industry and analysed their impact on FM service
delivery. Data collected were analysed using descriptive and inferential statistics. Spearman’s
correlation procedure was used to analyse the influence of use of BIM for FM technologies on
FM service delivery.
The paper concludes that CAFM is the most frequently used BIM for FM application in the
Nigerian FM industry, followed by CMMS and DMS in that order. BAS was however the least
rated. The paper also concludes that BIM for FM technologies especially CAFM and CMMS
have been most effective in asset management, energy and safety management, and inventory
management. Besides the paper concludes that (1) the use of CAFM has significant influence on
lifecycle cost reduction and timely delivery of FM services but not on quality of output and
stakeholder satisfaction (2) the use of CMMS has significant influence on cost reduction and
timely delivery of services but no influence on quality of output and stakeholder satisfaction, (3)
BMS has significant influence on lifecycle cost reduction.
However, this study is limited to three strategic cities within Nigeria. Although it could be
generalized in a lesser scale to other parts of the country, more comparative research could be
carried out in other developing nations to generate a comprehensive database of BIM for FM.

REFERENCES
Abubakar, M., Ibrahim, Y.M., Kado, D. and Bala, K. (2014). “Contractors’ perception of the
factors affecting Building Information Modelling (BIM) adoption in the Nigerian
construction industry.” Proceedings of 2014 International Conference on Computing in Civil
and Building Engineering, Florida, U.S., 167-178.
Alufohai, A.J. (2012). “Adoption of Building Information Modeling and Nigeria’s quest for
project cost management.” Proceedings from FIG Working Week, Rome, Italy, 1-7.
Aranda-Mena, G., Crawford, J., Chevez, A. and Froese, T. (2009). “Building Information
Modeling demystified: does it make business sense to adopt BIM?” International Journal of
Managing Projects in Business, 2(3), 419-434.
Atkin, B. and Brooks, A. (2009). Total facilities management (3rd ed.), Wiley-Blackwell,
Chichester.
Becerik-Gerber, B., Jazizadeh, F., Li, N. and Calis, G. (2012). “Application areas and data
requirements for BIM-enabled facilities management.” Journal of Construction Engineering
and Management, 138(3), 431-442.
BIM Task Group (BIMTG). (2013). “Government soft landings: departmental implementation brief.”
<http://www.bimtaskgroup.org/wp-content/uploads/2013/02/GSL-Department-Implementation-
Brief-18022013.pdf> (Feb. 17, 2013).

© ASCE
ICCREM 2016 9

Booty, F. (2006). Facilities management handbook 3rd edition, Butterworth -Heinemann,

Oxford.
Coates, P., Arayici, Y., Koskela, L., Kagioglou, M., Usher, C. and O’Reilly, K. (2010). “The key
performance indicators of the BIM implementation process.” Proceedings of the
International Conference on Computing in Civil and Building Engineering, Nottingham,
England, 157-157.
East, W.E. (2014). “Construction-Operations Building information exchange (COBie).”
<http://www.wbdg.org/resources/cobie.php> (Aug. 4, 2014).
Eastman, C., Teicholz, P., Sacks, R. and Liston, K. (2011). BIM handbook: a guide to Building
Information Modeling for owners, managers, designers, engineers and contractors, Wiley,
New Jersey.
Gu, N. and London, K. (2010). “Understanding and facilitating BIM adoption in the AEC
industry.” Automation in Construction, 19(8), 988-999.
Huber, D., Akinci, B., Adan, A., Anil, E., Okorn, B. and Xiong, X. (2011). “Methods for
automatically modeling and representing as-built building information models.” Proceedings
of 2011 NSF Engineering Research and Innovation Conference, Atlanta, Georgia, 1-8.
Ikediashi, D.I., Ogunlana, S.O. and Ujene, A.O. (2014). “An investigation on policy direction
and drivers for sustainable facilities management practice in Nigeria.” Journal of Facilities
Management, 12(3), 303-322.
International Financial Management Association (IFMA). (2013). BIM for facility managers,
John Wiley & Sons, New Jersey.
Kaseem, M., Kelly, G., Dawood, N., Serginson, M. and Lockley, S. (2015). “BIM in facilities
management applications: a case study of a large university complex.” Built Environment
Project and Asset Management, 5(3), 261-277.
Khosrowshahi, F. and Arayici, Y. (2012). “Roadmap for implementation of BIM in the UK
construction industry.” Journal of Engineering, Construction and Architectural
Management, 19(6), 610-635.
Kuroshi, P.A. and Omorogbe, N.E. (2010). “BIM enabled system of expenditure control for
construction projects.” Proceedings from Engineering Project Organization Conference
(EPOS), California, U.S., 1-12.
Parsanezhad, P. and Dimyadi, J. (2014). “Effective facility management and operations via a
BIM-based integrated information system.” Proceedings from CIB Facilities Management
Conference, Copenhagen, Denmark, 1-12.
Patacas, J., Dawood, N., Vukovic, V. and Kaseem, M. (2015). “BIM for facilities management:
evaluating BIM standards in asset register creation and service life planning.” Journal of
Information Technology in Construction, 20(2015), 313-331.
Philip, D. (2012). “BIM and the UK construction strategy.”
<http://www.thenbs.com/topics/bim/articles/bimAndTheUKConstructionStrategy.asp> (Jun. 17,
2015).
Vanlande, R., Nicolle, C. and Cruz, C. (2008). “IFC and building lifecycle management.”
Automation in Construction, 18(1), 70-78.
Volk, R., Stengel, J. and Schultmann, F. (2014). “Building Information Modeling (BIM) for
existing buildings-Literature review and future needs.” Automation in Construction,
38(2014), 109-127.
Williams, R. (2013). Utilizing Building Information Modelling for Facilities Management.
University College London, London, U.K., 10-11.

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ICCREM 2016 10

World Bank. (2013). “Nigeria economic report, No. 1, May 2013.”

<https://openknowledge.worldbank.org/bitstream/handle/10986/16568/776840WP0Niger0B
ox0342041B00PUBLIC0.pdf?sequence=1> (Apr. 5, 2014).

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