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EAI/Springer Innovations in Communication and Computing

Dagmar Cagáňová · Michal Balog

Lucia Knapčíková · Jakub Soviar
Serkan Mezarcıöz Editors

Smart Technology
Trends in Industrial
and Business
Management
EAI/Springer Innovations in Communication
and Computing
Series editor
Imrich Chlamtac, CreateNet, Trento, Italy
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Dagmar Cagáňová • Michal Balog
Lucia Knapčíková • Jakub Soviar
Serkan Mezarcıöz
Editors

Smart Technology Trends

in Industrial and Business
Management
Editors
Dagmar Cagáňová Michal Balog
Slovak University of Technology Technical University of Košice
in Bratislava Department of Industrial Engineering
Trnava, Slovakia and Informatics
Prešov, Slovakia
Lucia Knapčíková
Technical University of Košice Jakub Soviar
Department of Industrial Engineering University of Žilina
and Informatics Faculty of Management Science
Prešov, Slovakia and Informatics
Žilina, Slovak Republic
Serkan Mezarcıöz
Temsa Ulaşım Araçları San. ve Tic. A.Ş.
Seyhan, Adana, Turkey

ISSN 2522-8595     ISSN 2522-8609 (electronic)

EAI/Springer Innovations in Communication and Computing
ISBN 978-3-319-76997-4    ISBN 978-3-319-76998-1 (eBook)
https://doi.org/10.1007/978-3-319-76998-1

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Preface

This publication is a collection of rigorous research projects that were presented at

the “Industry of Things and Future Technologies” international conference. The
event took place in Bratislava, Slovakia, during November 22–24, 2016, and was
endorsed by the European Alliance for Innovation, a leading community-based
organisation devoted to the advancement of innovation in the field of ICT. The con-
ference was organised by the Slovak University of Technology in Bratislava, Faculty
of Materials Science and Technology in Trnava (MTF STU) and the Technical
University of Košice, Faculty of Manufacturing Technologies with a seat in Prešov
(TUKE).
The Internet of Things (IoT) offers advanced connectivity of devices, systems,
and services that reach beyond machine-to-machine communications and covers a
variety of domains. Therefore, the main goal of the conference was to determine the
next level technologies that will drive Industry 4.0 and IoT forward and to introduce
industrial innovations, smarter key technologies, and novel approaches to data anal-
ysis, rethink strategic planning, develop new opportunities, address challenges, and
explore its solutions. Additionally, the focus of the conference reflected the European
Union thematic priorities for research and innovation to improve the quality of life
for citizens and make cities more sustainable with decreasing impact on the
environment.
The conference articles were presented in the four thematic areas:
• Technology (responsibility in IT business, creative technologies, intelligent
transport systems, advances in robotics and machine vision as a key success fac-
tor in innovative companies, the role of the human factor in the performance and
sustainability of manufacturing, challenges of IoT to cybersecurity, engineering
secure IoT systems, IoT impact on critical infrastructures, and others)
• Internet (future Internet, Internet of Things, security and safety, smart cities,
creative cities)
• Innovation (industrial networks and intelligent systems, social networks [social
marketing] and innovation in social areas, new perspectives in transport innova-
tion, green vehicles, fast track for transport innovation, socio-economic and

v
vi Preface

behavioural research for policy-making, novel trends in production devices and

systems, and others)
• Mobility (mobility within Danube strategy, smart mobility, mobility and its con-
sequences on health and well-being, urban mobility, E-mobility, congestion-free,
and sustainable mobility)
This publication encompasses a total of 34 research articles with worldwide con-
tributors. Among the project findings featured in this publication are those written
by the conference keynote speakers, e.g. Dr.h.c. Mult. Prof. Ing. Juraj Sinay, DrSc.,
the Head of the Department of Safety and Quality in Mechanical Engineering at the
Technical University in Košice and the President of Automotive Industry Association
of the Slovak Republic. Prof. Dr. Dragan Perakovic, the Head of Department for
Information and Communication Traffic and Head of Chair of Information
Communication Systems and Services Management at the University of Zagreb,
and the chief editor of the International Journal of Cyber-Security and Digital
Forensics (IJCSDF), contributes with his research article on Smart Wristband
System in Traffic Environment. His study is included in the Smart Transportation
Applications and Vehicle Data Processing System for Smart City Buses section of
this release.
Next, at the conference presented highly acclaimed scholar Prof. Pedrag Nikolič
who serves as a Dean of the Faculty of Digital Production at Educons University,
Serbia, together with Prof. Adrian David Cheok, the director of Imagineering
Institute in Malaysia. Among others, we are proud to achieve the scholarly success
of this edition which resulted from our cooperation with the Comenius University
in Bratislava, the Faculty of Management, and their prestigious contributors Assoc.
Prof. Ján Papula, Assoc. Prof. Zuzana Papulová with the research team, Assoc. Prof.
Gabriela Bartáková-Pajtinková, and Assoc. Prof. Katarína Gubíniová. We were
additionally delighted to welcome Assoc. Prof. Katarína Stachová and Assoc. Prof.
Zdenko Stacho from The School of Economics and Management in Public
Administration in Bratislava. The Department of Management at MTF STU and
The Institute of Management from Slovak Technical University were represented by
Prof. Tatiana Kluvánková, Prof. Maroš Finka, and Assoc. Prof. Daniela Gažová with
their teams at the conference.
Moreover, thanks to an excellent collaboration between MTF STU and the
Department of Marketing and Trade at the Slovak Agricultural University in Nitra.
Prof. Ľudmila Nagyová and Dr. Mária Holienčinová shared their scholarly expertise
in the Smart Technology Trends Business Management section of the publication.
We are also thankful for the research article contribution under the leadership of the
Assoc. Prof. Marian Králik from STU Faculty of Mechanical Engineering, Dr. Peter
Pištek with his colleagues from Faculty of Informatics and Information Technologies,
and Prof. Michal Cehlár, the Dean of Faculty of Mining, Ecology, Process Control
and Geotechnologies (BERG) at the Technical University of Košice (TUKE) with
his team whose contributions are included in the Smart Transportation Applications
and Vehicle Data Processing System for Smart City Buses section of the publica-
tion. Furthermore, we are grateful to Assoc. Prof. Dagmar Petríková who leads the
Department of Spatial Planning and Management at the MTF STU.
Preface vii

Additionally, we would like to show appreciation to the PhD candidates and

other academics from the MTF STU Faculty of Materials Science and Technology,
particularly to Dr. Natália Horňáková, MSc. M.A. Richard Jurenka, and MSc.
Augustín Stareček who mastered the exemplary teamwork and for their rigorous
contributions to this publication as well as many other outstanding contributions
from various institutions. Other areas of expertise covered in this edition include
Industry of Things and Future Technologies and Smart Technology Trends in
Industrial Management and Materials.
As chairs of the conference, we were particularly impressed by the wide range of
innovative research solutions presented at the symposium. In the light of the latest
knowledge and findings from scientific projects, the authors present actual R&D
trends in the given field. Therefore, the Scientific Committee members and organis-
ers would like to express their sincere thanks to all the authors who attended the
conference in Bratislava, Slovakia, and particularly to the authors, who contributed
to the creation of this publication. This issue not only defines the state of the art in
the field, but it additionally explores related topics for future research. Moreover, we
would like to thank the audience members who actively interacted in the discussion
on the topics mentioned above.

Trnava, Slovakia Dagmar Cagáňová

Dorota Horvath
Acknowledgment to the International
Conference on Management of Manufacturing
Systems (MMS 2016)

I would like to thank all the authors and reviewers, especially Prof. Juraj Sinay,
Prof. Dragan Perakovič, and Assoc. Prof. Juraj Pančík who are our keynote
speakers. My thanks to the Dean of Faculty of Manufacturing Technologies with a
seat in Prešov of Technical University of Košice Dr. h. c. Prof. Dr. Jozef Zajac, to
the Head of the Department of Industrial Engineering and Informatics, to Assoc.
Prof. Dr. Michal Balog, and to my colleague Dr. Jozef Husár.

Lucia Knapčíková

ix
Contents

Part I Industry of Things and Future Technologies

1 Application of AHP Method in Decision-­Making Process ������������������    3
Richard Jurenka, Dagmar Cagáňová, and Daniela Špirková
2 An Integrative Spatial Perspective on Energy Transition:
Renewable Energy Niches ����������������������������������������������������������������������   17
Filip Gulan, Maros Finka, and Michal Varga
3 Can Concept of Smart Governance Help to Mitigate
the Climate in the Cities?������������������������������������������������������������������������   35
Alfréd Kaiser and Tatiána Kluvánková
4 Operational Characteristics of Experimental Actuator with
a Drive Based on the Antagonistic Pneumatic Artificial Muscles��������   49
Miroslav Rimár, Peter Šmeringai, and Marcel Fedák
5 Critical Values of Some Probability Distributions and Standard
Numerical Methods����������������������������������������������������������������������������������   61
Dušan Knežo, Jozef Zajac, and Peter Michalik
6 Measuring Production Process Complexity������������������������������������������   71
Soltysova Zuzana, Bednar Slavomir, and Behunova Annamaria
7 IoT Challenge: Older Test Machines Modernization
in an Automotive Plant����������������������������������������������������������������������������   85
Juraj Pančík and Vladimír Beneš

Part II Smart Technology Trends in Industrial Management

8 Industry 4.0: Preparation of Slovak Companies,
the Comparative Study���������������������������������������������������������������������������� 103
Ján Papula, Lucia Kohnová, Zuzana Papulová, and Michael Suchoba

xi
xii Contents

9 Transformations of Urbanized Landscape Following

the Smart Water Management Concept������������������������������������������������ 115
Matina Lazarová, Michal Varga, and Daniela Gažová
10 RFID Labels and Its Characteristics on Labeled Products ���������������� 133
Dušan Dorčák, Romana Hricová, and Peter Šebej
11 Basic Assumptions of Information Systems for Increasing
Competitiveness of Production Companies within the EU
and their Application of the CAPP System Design ������������������������������ 145
Katarina Monkova, Peter Monka, Helena Zidkova,
Vladimir Duchek, and Milan Edl
12 Cooperation as a Key Element Between Universities
and Factories��������������������������������������������������������������������������������������������� 165
B. Mičieta, J. Herčko, Ľ. Závodská, and M. Fusko
13 Zilina Intelligent Manufacturing System: Best Practice
of Cooperation Between University and Research Center������������������ 183
Milan Gregor, Jozef Hercko, Miroslav Fusko, and Lukas Durica
14 Improvement of the Production System Based
on the Kanban Principle�������������������������������������������������������������������������� 199
Ľuboslav Dulina, Miroslav Rakyta, Ivana Sulírová,
and Michala Šeligová
15 Quality Assurance in the Automotive Industry and Industry 4.0��������  217
Štefan Markulik, Juraj Sinay, and Hana Pačaiová

Part III Smart Technology Trends Business Management

16 Potential of Human Resources as Key Factor of Success
of Innovation in Organisations �������������������������������������������������������������� 229
Stacho Zdenko, Stachová Katarína, and Cagáňová Dagmar
17 Environmental Policy as a Competitive Advantage
in the Global Environment���������������������������������������������������������������������� 249
Zuzana Tekulova, Zuzana Chodasova, and Marian Kralik
18 Sustainable Organization of Cooperation Activities
in a Company: Slovak Republic Research Perspective������������������������ 263
Jakub Soviar, Viliam Lendel, Josef Vodák, and Jana Kundríková
19 Green Markets and Their Role in the Sustainable Marketing
Management �������������������������������������������������������������������������������������������� 281
Katarína Gubíniová, Gabriela Pajtinková Bartáková,
and Jarmila Brtková
Contents xiii

20 A New Approach to Sustainable Reporting: Responsible

Communication Between Company and Stakeholders
in Conditions of Slovak Food Industry�������������������������������������������������� 291
Mária Holienčinová and Ľudmila Nagyová
21 Cooperative Relations and Activities in a Cluster in the Slovak
and Czech Automotive Industry ������������������������������������������������������������ 303
J. Vodák, M. Varmus, P. Ferenc, and D. Zraková

Part IV Smart Technology Trends in Materials

22 Composites Manufacturing: A New Approaches to Simulation���������� 319
Lucia Knapčíková, Michal Balog, Alessandro Ruggiero,
and Jozef Husár
23 Study of the Cutting Zone of Wood-Plastic Composite
Materials After Different Types of Cutting ������������������������������������������ 327
Dusan Mital, M. Hatala, J. Zajac, P. Michalik, J. Duplak,
J. Vybostek, L. Mroskova, and D. Knezo
24 Risk Analysis Causing Downtimes in Production Process
of Hot Rolling Mill ���������������������������������������������������������������������������������� 337
Marcela Malindzakova, Dagmar Cagáňová, Andrea Rosova,
and Dusan Malindzak
25 Evaluation of Roughness Parameters of Machined Surface
of Selected Wood Plastic Composite������������������������������������������������������ 345
J. Zajac, F. Botko, S. Radchenko, P. Radič, A. Bernat, J. Roman,
and B. Zajac
26 Evaluation of the Transverse Roughness of the Outer and Inner
Surfaces of the Thin-Walled Components Produced by Milling �������� 353
Peter Michalik, Jozef Zajac, Michal Hatala, Dusan Mital,
and Łukasz Nowakovski

Part V Smart Transportation Applications and Vehicle Data

Processing System for Smart City Buses
27 Designing Behavioral Changes in Smart Cities Using Interactive
Smart Spaces�������������������������������������������������������������������������������������������� 367
Predrag K. Nikolic and Adrian D. Cheok
28 Social Innovations in Context of Smart City ���������������������������������������� 383
Richard Jurenka, Dagmar Cagáňová, Natália Horňáková,
and Augustín Stareček
29 Towards Creating Place Attachment and Social Communities
in the Smart Cities ���������������������������������������������������������������������������������� 401
Matej Jaššo and Dagmar Petríková
xiv Contents

30 Awareness of Malicious Behavior as a Part of Smart

Transportation in Taxi Services�������������������������������������������������������������� 413
Peter Pistek and Martin Polak
31 Alternative Lights for Public Transport in Smart Cities���������������������� 421
Michal Cehlár and Dušan Kudelas
32 Smart Wristband System for Improving Quality of Life
for Users in Traffic Environment������������������������������������������������������������ 429
Dragan Peraković, Marko Periša, Rosana Elizabeta Sente,
Petra Zorić, Boris Bucak, Andrej Ignjatić, Vlatka Mišić,
Matea Vuletić, Nada Bijelica, Luka Brletić, and Ana Papac
33 Smart Transportation Applications and Vehicle Data
Processing System for Smart City Buses ���������������������������������������������� 451
Serkan Mezarcıöz, Enis Aytar, Murat Demizdüzen, Mert Özkaynak,
and Kadir Aydın
34 A Model Approach for the Formation of Synergy Effects
in the Automotive Industry with Big Data Solutions:
Application for Distribution and Transport Service Strategy ������������ 467
Martin Holubčík, Gabriel Koman, Michal Varmus,
and Milan Kubina

Index������������������������������������������������������������������������������������������������������������������ 489
 Part I
Industry of Things and Future
Technologies
Chapter 1
Application of AHP Method
in Decision-­Making Process

Richard Jurenka, Dagmar Cagáňová, and Daniela Špirková

Abstract The paper deals with the application of method – analytical ­hierarchy
process in action of decision-making in the field of innovation management of
industrial companies. Analytical hierarchy process is a tool for application of
exact methods in process of decision-making. The paper contains theoretical
description of analytical hierarchy process and subsequently also application of
this method in the field of innovation management. Method of analytical hier-
archy process brings into action of decision-making objectivity, exactness, and
also the quality of the evaluation. Perhaps the biggest advantage of this method is
that this method allows to evaluate comprehensively all the criteria of alternative
solutions​. This paper aims to highlight the widespread use of method – analytical
hierarchy process in the decision-­making process, including in the field of inno-
vation management.

Introduction

In the modern business environment, organizations must respond to new challenges,

constant changes, and opportunities and also must respond to the different require-
ments and various restrictions. Permanent transformation of the business environ-
ment is in contemporary world the necessity of continuous innovation and changes.

R. Jurenka (*) · D. Cagáňová

Slovak University of Technology in Bratislava, Bratislava, Slovakia
Faculty of Materials Science and Technology in Trnava, Trnava, Slovakia
Institute of Industrial Engineering and Management, Trnava, Slovakia
e-mail: richard.jurenka@stuba.sk; dagmar.caganova@stuba.sk
D. Špirková
Institute of Management, Bratislava, Slovakia
Slovak University of Technology in Bratislava, Bratislava, Slovakia
e-mail: daniela.spirkova@stuba.sk

© Springer International Publishing AG, part of Springer Nature 2019 3

D. Cagáňová et al. (eds.), Smart Technology Trends in Industrial and Business
Management, EAI/Springer Innovations in Communication and Computing,
https://doi.org/10.1007/978-3-319-76998-1_1
4 R. Jurenka et al.

Nowadays from existing organizations, some flexibility, dynamism, and constant

adaptation to changing conditions are expected. The current social conditions are
reflected in organizational behavior of individual companies and also in their
decision-­making process.
Social environment in this century is very dynamic, changeable, unstable and
hardly predictable. Result of these factors is instability and unpredictable develop-
ment in social environment. Different changes in such an environment and condi-
tions are becoming a necessity and everyday reality with which organizations must
deal by their flexibility and ability to adapt to new and new conditions. In dynamic
environment, in which organizations want to operate and develop, constantly bring-
ing new enhancements, innovations, ideas, and thoughts is fundamental for compa-
nies. For selection the correct option of advancement is a necessary perfect
decision-making process that will consider all the factors, risks, and opportunities
in outside and inside environment.

Exact Methods in Managerial Decision-Making

Decision-making is an integral part of management processes in every company and

intersects across all functions of management – planning, organizing, staffing and
maintaining staff, leadership people, and controlling. All managers at all levels of
directing make decisions, while the ultimate effect of these decisions can have a
significant impact on a range of other activities. Some decisions are strategic in their
nature and significantly affect company’s survival on the market; other decisions
can be seemingly pointless. However, all decisions have the certain impact on busi-
ness performance; therefore it is very important to give adequate attention to
decision-­making issue [1].
Decision-making as a complex process involves a number of different phases
that must be met in order to have a final decision. Final decision is selected from
several variants of solutions. Managers and competent persons, respectively, have to
make decisions even under changing conditions, under pressure, in a state of uncer-
tainty or risk, and under the influence of certain restrictions, respectively. The
decision-­making process is therefore a nonrandom selection of one variant of the
solution according to certain criteria in order to meet predefined objectives.

Decision-Making Process

Decision-making process constitutes a comprehensive system which is character-

ized by the following parts:
• Decision problem – is a reflection of the significant deviation between the desirable
state (planned or established standards) of specific decision object and its real state
• Decision-making situations – is given by the object of decision (selected process
or operation), by state of internal or external conditions which cause deviations
1 Application of AHP Method in Decision-Making Process 5

Fig. 1.1 Decision problem and decision-making situations [2]

from the desired state, by setting targets or its alternative aims, and by criteria,
variants, and sometimes also consequences of possible decisions
• Decision-making process – the process of choosing between several possible
solutions (search and selection of suitable alternatives solutions for the current
problem)
• Variations of decisions – option of several possible and different solutions which
ideally suits to specific criteria [2]
Decision-making process is affected among other things by ambient conditions,
subject making decision, the object of decision-making, decision-making criteria,
and setting of goals. The following picture shows how the abovementioned ele-
ments affect decision-making process (Fig. 1.1).
Necessary assumes for creating high-class decisions:
• Clear statement of the target goal which must be achieved by decision
• Adequate, verified, quality, timely, reliable information that are the basis for
making any high-grade decision
• Adequate qualification and competence of decision-makers. Using appropriate
methods, tools, and knowledge [3]
Decision-making process is divided by majority of authors into several main
groups of steps (e.g., analytical part, project part, evaluation part). In books from
many authors, it is possible to find several models of decision-making process. In
context of this paper, we suggest to determine the content and steps of decision-­
making process in general as [2]:

1. Discovering of the problem and acceptance of decision to resolve the existing problem
2. Identification and analysis of the situation and analysis of the problem, causes of the
problem, and possible consequences in the event of failure to resolve the whole problem
3. Determining criteria for choosing the right solution (general requirements for possible
solutions, which must be legal, ethical, economic, and feasible)
4. Creating (generating) possible variants of solutions
5. Assessment of possible variants of solutions according to established criteria
6. Selecting the optimal solution
7. Evaluation (testing) of the chosen decision – assessment of its positive and negative
consequences
8. Formulation of decision and determination of implementers, procedures, and forms
6 R. Jurenka et al.

Fig. 1.2 Decision algorithm [2]

The following figure shows a decision algorithm:

In business practice the decision-making process is not always as objective,
uninfluenced by each successive step, which is shown in Fig. 1.2, because a specific
decision-making process can be affected by in-house arrangements, conventions, or
stakeholder or under the influence of a supervisor person [4].

Exact Methods and Analytical Hierarchy Process (AHP)

Exact methods of operational analysis can be classified among the most advanced
quantitative methods for decision-making. The main role of these methods is to find
among the possible variants of solutions the best variant in accordance to existing
problem or target goal. Among the exact methods, which are designed for resolving
decision-making problems, are the relationships between the elements mainly
expressed quantitatively which may include:

• Methods of mathematical statistics – theory of probability, correlation analysis, and time

series analysis
• Methods of mathematical analysis and linear algebra – differential numbers, extrapolation,
and matrix number
• Methods of operational analysis – economic-mathematical methods, structural analysis,
network analysis, models of mass operation, etc.
• Multi-criteria decision-making methods [5]

The analytical hierarchy process is a systematic approach created in 1970 for

structuring the experience, intuition, and heuristic-based decision-making into a
properly defined methodology based on mathematical principles. The AHP method
was created for the needs to return to quantitative assessment in decision-making
process. This method provides a formalized approach for creating solutions [6].
1 Application of AHP Method in Decision-Making Process 7

The AHP method was created in the late 1960s by Thomas L. Saaty, an American
professor who worked at the University of Pittsburgh. Saaty’s analytical hierarchy
process offers a methodology that allows to model complex decision situation and
determine the appropriate choices.
This approach has been developed to help solve complex problems. Although
this method was not originally intended for collective decision-making, nowa-
days thanks to its transparency and consistency is using also for group decision-
making process [6].
The method of analytical hierarchy process is based on scientific analysis. This
method, among other things, can be used also in the process of formulating the
strategic objectives of stakeholders as well as in decision-making process in terms
of crisis or risk management. The AHP method provides the framework for making
effective decisions in situations, when the choosing of best decision is needed or
fundamental. AHP method enables to prepare effective solutions in complex situa-
tions and simplifies the natural decision process [7].
The AHP method is one of the most exact objective methods of multi-criteria
decision-making but still has several disadvantages. One of the major disadvantages
of the method is burdening some steps in its application with a certain degree of sub-
jectivity. For this reason it is necessary to objectify the allocation of specific weights
for the individual criteria, which minimize subjectivity and ultimately lead to an over-
all objectification of the AHP method. Therefore it is necessary to create a tree struc-
ture as far as possible in an exact way that could minimize the subjective impacts of
evaluators. Possible solution that partially removes such a problem is performing of
an evaluation with the participation of a group of evaluators that are experts in the
specific field. Objectivity could be increased by assignment of weights to individual
evaluators; this process could reflect the importance of individual experts [8].
Structured hierarchy of AHP method represents a system for optimization, which
consists of a primary objective, criteria, and alternatives, respectively, in other
words variations. The criteria can be further spaced out to sub-criteria; this division
can lead to as many levels as necessary for resolving the problem.
AHP is a method of decomposition of complex unstructured situation into sim-
pler components. This method is first done by an expert method and then by math-
ematical method, which divides the main problem into smaller and more detailed
elements [7].

Advantages and Disadvantages of the AHP Method

Advantages of the AHP method [7]:

• Pair comparison allows to make easier conclusion

• The method requires just one pair comparison between all criteria and between all variants of
solutions
• The method is very simple and clear
• Exact weighting of individual criteria and clear results from quantitative assessments
8 R. Jurenka et al.

Disadvantages of the AHP method [7]:

• The scale of the evaluation is created by the evaluator (evaluator could think that one
criterion is more important than other)
• Assignment of weights by one evaluator may not be acceptable to other evaluators
• Formation of the tree structure is influenced by a certain degree of subjectivity
• In the case of additional adjustment of the decision matrix is coming to disruption of
objectivity in process of evaluation;
• This method could be time-consuming in terms of the amount of comparisons that must be
made
• Validity of the method is limited by consistency, because in practice is assessment some-
times inconsistent

Principles of AHP Method

The flexibility of the AHP method as a decision-making model helps to clearly

identify the most optimal solution among the other possible variants of solutions.
Decision-making process is influenced by three principles [9].

• Prioritization
• Priority
• Consistency

Prioritization – under this term it is possible to understand the linear structure that
contains several levels, whereby each of the levels contains a number of elements.
The arrangement of the individual levels of the hierarchical structure corresponds to
the arrangement from general to specific. If the individual elements are more gen-
eral in relation to the decision-making problem, then these elements have higher
importance in the hierarchy and vice versa [7].
Priority – method is based on a pair comparison. On the other hand, the evaluation
is based on the expert judgment. These expert judgments are made by experts from
the field and after that compare mutual influences of the two factors. They rank
criterions and variants between each other with the scale: same, weak, medium,
strong, or very strong [7].
Consistency – expresses the level of credibility of the final result. In cases where it
is necessary to compare a large number of criteria, the consistency gives us warranty
or credibility that the final result will be objective and optimal [7].

Potential Uses of AHP

The AHP method can be applied to decision-making processes and evaluation of

tasks in different sectors, but one condition must be always met that there must be
at least two alternatives for decision-making process [8].
1 Application of AHP Method in Decision-Making Process 9

From the factors which make the AHP method a very popular decision-making
method in the world, it is necessarily highlighted that this method quickly adapts to
fixed data like price, speed of delivery, personal experience, and also intuition. This
method allows mathematical deduction weights of the individual criteria instead of
the subjective choice of weighting criteria. In the first phase, before the method is
applied, the subject that makes evaluation must define all the criteria and sub-­criteria
on which will be evaluation based. The selection of individual criteria and sub-­
criteria is based on the previous knowledge and experience of each evaluator. If this
is the first rating of a single subject, then this evaluator must sort criteria on their
own intuition or in accordance with specific pattern [8].
AHP method can be applied to decision-making processes or to assessment of
the goals in different business sectors, but one condition must be respected every
time, that decision-making process must have at least two alternatives [8].
AHP method can be used in various fields as:
• Management
• Logistics
• Economy
• Health care
• Education
• Research
• Agriculture and forestry
• Energy
• Transportation
• Industry

Application of AHP Method in Innovation Management

AHP method was used to select the most innovative variants. For application method
of analytical hierarchy process, the software Expert Choice was used, which com-
prises the following steps:
1. Goal setting
2. Determination of the individual criteria
3. Assessment of alternative solutions
4. The assignment of weights to each criterion
5. Evaluation of the alternatives by paired comparison
6. Reviewing the current state of the system of values
Goal setting represents stage of choosing the best innovation variant from six
selected innovative activities that are in the field of innovation management very
often used. List of individual innovation variants are as follows:
• Introduction of a new product
• Modifying of the product
• Change the size of the package
• Change the appearance of a product (design)
10 R. Jurenka et al.

• Amendments of the product

• Introduction a new method of production
Criteria for evaluation of possible alternative solutions – for selection of the most
appropriate innovative variants, seven criteria were selected. The criteria are actu-
ally kinds of parameters of individual innovation activities. The criteria are given
below:
• Price
• Quality of manufacturing
• Material
• Appearance
• Utilization
• Durability
• Energy consumption

 pplication of AHP Method: Use and Application of Expert

A
Choice

In finding solution for our target goal to select the most innovative variant in innovation
management, the computer software Expert Choice was used. Expert Choice software
offers multi-criteria decision-making process. Expert Choice offers the opportunity to
split decisions in several hierarchical levels and sub-levels, respectively; thereby the
entire decision-making process is divided into separate and simpler parts.
Such allocation is done through the tree structure which distributes and organizes
the entire hierarchy. Criteria and options are stored into the decision matrix.
Individual preferences are granted according to Saaty’s nine-point scale. Preferences
can be given by numerical method or by verbal expression. Expert Choice offers
evaluation by numerical or graphical representations. Our goal was by the AHP
method to find the most suitable alternative innovation activities. In order to find
such a variant with computer software Expert Choice, at first we selected the main
goal, at second we selected variants of innovation activities, and then we entered the
decision-making criteria. Target goal can be defined by clicking on the icon Goal.

Defining Criteria

After setting the primary objective, the next step was defining the decision-
making criteria that represent a kind of basic parameters in the selection process
of the best innovative variant or activity. Defined criteria are shown in Fig. 1.3
(price, quality of manufacturing, material, appearance, utilization, durability, and
energy consumption).
1 Application of AHP Method in Decision-Making Process 11

Fig. 1.3 The file of decision criteria

Fig. 1.4 Determination of the individual variants

Assessment of Alternative Variants

The next step in the application was to determine the individual variants of innova-
tion activities, which are used in the field of innovation management (Fig. 1.4).

Assignment of Weights to Variants and to Individual Criteria

The next task was to determine specific values for the selected variants in accor-
dance with the established criteria. The allocation of weights to each variant and
criterion is undoubtedly an important step in the whole process. For the objectivity
and better results of calculation of the best innovative activities, the individual val-
ues in the table were determined by two experts in the field.
Consequently, it is necessary to compare each individual variant with others and
do the same comparison between each criterion with each other. This comparison is
12 R. Jurenka et al.

Fig. 1.5 Entering the values to individual criteria

performed separately for each variant and criterion. The procedure is identical in
Expert Choice, and this software can provide for us verbal, numerical, and graphi-
cal, respectively, representation of a particular comparison. Figure 1.5 shows the
assignment of values for them.
Word comparison of criteria (Fig. 1.5) is performed by verbal designation. The
relationship between each criterion (or variation) can be equal, moderate, strong,
very strong, or extreme.

Evaluation of Paired Comparison of All Criteria

After the successful assignment of particular values to compared criteria, it is pos-

sible to determine which criterion is the most important for us as well as which
criterion is the least important in concrete decision-making process. Figure 1.6 is a
displayed graph which tells us that price criterion is the most important criterion
from all criteria in the process of choosing the best innovation activity. Consequently,
it is possible to see the order of the other criteria importance.

Final Evaluation

The final evaluation is the ending phase. The paired comparison of variations and
criteria with the software Expert Choice gave us a result, in the form of various
graphs and diagrams. The final evaluation can be either numerical or graphical. In
this project, the main goal was selecting the most innovative variant or activity.
Evaluation of the whole process which was realized in Expert Choice can be seen in
1 Application of AHP Method in Decision-Making Process 13

Fig. 1.6 Graphical comparison of the most important criteria in the process of choosing the best
innovation activity

Fig. 1.7 Percentage evaluation of individual criteria and variation

the following Fig. 1.7 that gives us graphic and numerical information. From the
figure it can be revealed that the most important criterion is price and the most
important variant was the chosen introduction of a new product.
The abovementioned figure shows in detail the results of the percentage of the
whole evaluation. As from the figure results, the most important criterion for choos-
ing the best innovation activity is the price with 26.4%. The second most important
criterion is the design, which is reflected by 22.3%. Next, the criteria quality of
manufacturing with 15.4%, utilization with 11.6%, and material with 10.0% follow.
Durability has 8.4%, and the least important criterion chosen was the energy con-
sumption with 6.1%.
14 R. Jurenka et al.

Introduction of a new product is determined by final evaluation of variants as the

best innovation activity. This result is represented by 20.1% share. The most impor-
tant innovation activity is followed by the introduction of a new process for the
production, this activity was very close, and its importance is reflected with 19.6%.
On third place is located the change of design with 17.0%. Next, modifying the
product with 15,7%, change of the size of package with 14.6% and on the last place
are amendments of the product with 13.0% share.

Conclusion

The article discusses and describes how the program Expert Choice works. Expert
Choice applies the method of analytical hierarchy process in business practice.
Application of AHP method was performed in decision-making processes falling
into the field of innovation management; in this case the application of AHP method
is an ideal tool for selecting the most suitable variants. AHP method as a method of
multi-criteria decision-making can work with a number of criteria. In this paper we
managed to choose the most innovative options, namely, the introduction of a new
product with an assistance of the software program Expert Choice. The aim of the
project and the article was to point out the large-scale use of AHP method.
The final evaluation shows us that the most important criterion for choosing the
best innovation activity is the price with 26.4%. Introduction of a new product was
determined by final evaluation of variants as the best innovation activity. This result
is represented by 20.1% share. The work itself is served to the general public and in
a simple way explains AHP method and the use of software Expert Choice in many
sectors within the decision-making process.

References

1. Čambál, M., Holková, A., & Lenhardtová, Z. (2011). Základy manažmentu. Bratislava Alumni
Press. ISBN 978-80-8096-138-1.
2. UNIZA. Rozhodovacie procesy. [online]. Accessible at: http://fsi.uniza.sk/kkm/old/publikacie/
ma/ma_05.pdf
3. Máca, J., & Leitner, B. (2002). Operačná analýza I.: Deterministické metódy operačnej
analýzy. [online]. Accessible at: http://fsi.uniza.sk/ktvi/publikacie/11_operanal1_u_2002.pdf
4. Baďo, R., & Vrablic, P. (2011). Využitie metódy multikriteriálneho rozhodovania metódou
AHP pri rozhodovaní v podnikateľskom prostredí. Transfer informácií 21/2011. Bratislava:
Strojnícka fakulta STU. [online]. Accessible at: http://www.sjf.tuke.sk/transferinovacii/pages/
archiv/transfer/21-2011/pdf/082-085.pdf
5. Hrablik Chovanová, H., Sakál, P., Drieniková, K., & Naňo, T. (2012). Operačná analýza : časť
II. Trnava: AlumniPress. ISBN 978-80-8096-165-7.
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nocení a podpoře rozhodování.v Sborniku příspěvku z konference: Matematika v ekonomické
praxi. Jihlava. [online]. Accessible at: https://most.vspj.cz/files/11/Matematika-v-ekonomicke-
praxi.pdf
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