Uso de criterios múltiples para introducir y clasificar los criterios de diseño
de recompensa en proyectos de construcción
Using multiple criteria to enter and rank reward design criteria in construction projects
Masoud Koochakzadeh
1
, Valiollah Azizifar
2a
Ghaemshahr Branch, Islamic Azad University, Ghaemshahr, Iran
12
Orcid ID: https://orcid.org/0000-0002-2838-7169
1
Orcid ID: https://orcid.org/0000-0003-4671-129X
2
Recibido: 04 de abril de 2020 Aceptado: 19 de octubre de 2020
Resumen
El objetivo de este estudio fue el uso de la toma de decisiones de criterios múltiples para
introducir y clasificar los criterios de diseño de recompensa en proyectos de construcción. En
esta investigación se clasifican los criterios de diseño de recompensas en proyectos de
construcción. En el presente estudio, para identificar y clasificar los criterios de asignación de
recompensas a los empleados se utilizaron los métodos de Demetel y la expansión del
desempeño de calidad difusa en dos pasos. Los resultados mostraron que la ética profesional
es el criterio más importante para la asignación de recompensas a los empleados en los
proyectos de construcción. Los resultados muestran que considerar el clima laboral de los
proyectos de construcción, mantener la disciplina y tener compromiso organizacional y ayudar
a los demás es muy importante. Además, tener el espíritu de trabajo en equipo y cooperación
con los demás es muy importante para trabajar en estos entornos. Uno de los puntos destacables
en los hallazgos de este estudio es la menor atención prestada por los gerentes de obra al uso
de indicadores de medición de cantidad de mano de obra como criterio para la asignación de
recompensas y mayor atención a criterios de calidad como la ética profesional, la creatividad,
etc., que muestra la diferencia entre la naturaleza del trabajo y el producto final de esta industria
con industrias manufactureras como la fabricación de piezas.
Palabras clave: Desempeño de calidad difusa, salarios del personal, análisis jerárquico, diseño
de recompensas, proyectos de construcción
Abstract
The objective of this study was to The Use of Multi-Criteria Decision Making to Introduce and
Rank of Design Criteria of Reward in Construction Projects. In this research, the design criteria
of rewards in construction projects are ranked. In the present study, in order to identify and
a
Correspondencia al autor
E-mail: v.azizifar@gmail.com
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477
Apuntes Universitarios, 2021: 11(1), enero-marzo
ISSN: 2304-0335 DOI: https://doi.org/10.17162/au.v11i1.598
apuntesuniversitarios.upeu.edu.pe
rank the criteria of employee reward allocation the methods of Demetel and expansion of the
performance of fuzzy quality in two steps were used. the results showed that the professional
ethics is the most important criterion for reward allocation to the employees in the construction
projects. Results show that considering the work environment of construction projects,
maintaining discipline and having organizational commitment and helping others is very
important. Also, having the spirit of teamwork and cooperation with others is very important
for working in such environments. One of the notable points in the findings of this study is the
less attention paid by construction managers to the use of labor quantity measurement
indicators as a criterion for reward allocation and more attention to quality criteria such as
professional ethics, creativity, etc., which shows the difference between the nature of the work
and the end product of this industry with manufacturing industries such as parts manufacturing.
Keywords: Fuzzy Quality Performance, Personnel Wages, Hierarchical Analysis, Reward
Design, Construction Projects
Introduction
Undoubtedly, one of the effective ways to motivate and improve the productivity of
employees and the performance of an organization is the existence of a system of service
compensation and rewards fixed with the budget and revenues. The set of performance
evaluation and reward system and effective wage, forms the performance management of an
organization (Valipour, 2018).
The selection of an effective reward system is done in different ways, one of which is
the performance-based payment method. the reward is also one of the types of performance-
based payment that in various sectors of industry, both public and private, forms of It is
available. Housing as one of the primary and basic living needs of human beings and
households of a society in particular, and so the construction industry and its related jobs have
a special rank in Iran economy today (Sepehri Rad, 2019). This industry has a share of 14.2%
of employees in the country based on annual statistics of 2017 except the part of the service
sector that is indirectly related to it and is one of the thriving businesses in the country (Onishi,
2020).
Ontime delivery of projects, especially in the mass production sector, while having its
special importance in the profitability of the project, in terms of fluctuations in the price of
materials and wages of specialized works and compliance with the time table and schedule of
contracts, also has significant political effects in gaining popular satisfaction and economic
stability (Maslahi and Zafar Khan, 2019).
Research background
Nematbakhsh et al. (2016) examined the point of views of faculty members of the
University of Medical Sciences of Tehran about the effects of reward system on medical
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education in teaching hospitals. In this cross-sectional study, 69 faculty members were
interviewed and the results showed that the reward system has failed to promote medical
education, so there is a need to review the reward system to improve medical education. In this
study, the lack of a proper evaluation system has been identified as one of the main reasons for
the failure of the reward system project.
Sepehri Rad (2019) has proposed a mathematical model of reward payment for
employees of the organization with a 360-degree performance evaluation approach in the
National Productivity Organization. In this study, at first the indicators of employee
performance evaluation were extracted from the literature, then by a survey of experts and
based on the characteristics of the studied organization and similar to Valipour (2018) study
into four categories of personal characteristics, technical skills, human skills and perceptual
skills has been divided.
Yang and Chen (2018) propose an incentive payment system for project management
based on the responsibilities allocation matrix and fuzzy language variables. This study
presents a new payment system for active team members in each project. Performance
evaluation is performed without specifying a specific criterion and based on judgments made
with the help of fuzzy linguistic variables. In this system, four models are proposed for different
project management conditions.
Maslahi and Zafar Khan (2019) have studied the factors affecting the productivity of
employees in construction projects and in spite of considering factors such as temperature,
relative humidity, type of work and the method used. They have not pointed to the factors like
payment and reward and its effect on the efficiency.
Chai (2019) by use of a combined approach of the methods of either fuzzy hierarchical
analysis process and fuzzy TOPSIS has evaluated the performance of the employees of the
studied organization. The criteria used in this study to evaluate employee performance are:
production ability, ability to be creative and innovative, financial performance and how to serve
customers.
Opheli (2019) in a study on construction companies operating in the Nigerian industry,
considers the factors affecting the general reward systems as including the internal and external
factors. Internal factors include organizational culture, organizational strategy and
organizational life cycle. External factors also include the market, specialization, productivity
indicators, and human-personnel relations activities. He also suggests the factors affecting on
payment based on performance as the performance evaluation, education and development,
union-manager relations, and organizational culture. In this study, the determinant factors of
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reward policy include labor market conditions, laws, productivity, collective bargaining, cost
of living, employer financial ability, comparable wages, industry, staff level, and minimum
wage for life.
Lai et al. (2020) conducted a comparative study about the impact of human resource
operations, including performance and reward evaluation and reward, in safety management in
construction projects in the United States and Singapore. Based on this research, criteria such
as reporting unsafe or dangerous actions, fewer accidents, individual safety performance and
group safety performance have been selected as criteria for rewarding the safety management
of construction projects. The results show that evaluating the performance of employees in
terms of safety and rewarding employees based on their safety performance is effective on the
safety management of construction projects.
Cornellison et al. (2020) in their research show that employee satisfaction was higher
in jobs where performance-based pay was implemented than in other jobs. They then propose
a model in which employees with greater ability and higher risk tolerance receive greater
rewards through performance-based pay. With the implementation of this model, employee
satisfaction was assessed equally in all jobs, but employees in jobs that were paid based on
performance and had a higher risk tolerance, expressed higher satisfaction.
Onishi (2020) examines the effects of service compensation schemes on Research and
Developement Organization of Japan staff innovations. In this research, the evaluation criterion
is the criteria based on income and innovation and the results show that monetary incentives
based on the performance of inventions, lead to increasing the motivation of innovative
employees.
Methodology
In the present study, which is performed in order to both identification and ranking the
criteria of the reward allocation by use of DEMATEL and expansion of fuzzy quality
performance in two stages, the statistical population includes the senior managers and human
resources managers of the construction companies that are implementing the reward plan or
are at first steps of this implementation.
In this study, due to the limited number of experts as well as senior managers of the
studied construction organizations where were implementing the reward plan, the available
sampling method is used. Due to the fact that the statistical population of the research is limited
to experts with experience in the field of service compensation systems, reward systems and
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the senior managers responsible for decision making and planning in the organization under
study, research questionnaires are distributed among all eligible individuals. And all of them
will be questioned.
Research steps
Figure 1 shows the steps of conducting research.
Figure 1
The steps of this research
Validity and reliability of research
Validity:
To increase the validity and reliability of the theme analysis, the following method is
used in this research:
Triangular method: In this method, several researchers, several data sources, or several
methods are used to validate emerging data. In this research, by choosing a mixed
method and using the literature and opinions of experts, we try to increase the validity
of the obtained model.
Reliability:
To determine the reliability of the researches such as the present study, much of which
is qualitative, there is no need to determine reliability in the form of statistical research, but to
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ensure that the results are reliable, especially after theme analysis, there are three methods.
(Maryam, 1988) Used:
- Triangulation: In this method, similar to what is used to confirm validity, it is also
used to confirm reliability. This means that the use of mixed research method can show the
reliability of research findings.
- Auditing by an arbitrator: In this method, the researcher increases the reliability of the
research results by clarifying how to collect data, how categories are derived and how to make
a decision during the investigation for the auditor and its approval by the arbitrator. In this
research, this audit is performed by the professors.
- Retest method: To conduct the retest method, three interviews are selected and each
of them is coded twice in a period of 20 days by the researcher. Then the retest reliability
percentage is calculated by use of the equation 1. In this study, this number was equal to 78%,
which was more than the minimum acceptable value of 60%.
Equation 1:
Retest reliability percent =
2 ∗ 𝑇ℎ𝑒 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑎𝑔𝑟𝑒𝑒𝑚𝑒𝑛𝑡𝑠
𝑇ℎ𝑒 𝑓𝑖𝑛𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐶𝑜𝑑𝑒𝑠
100%
Data analysis tools
Qualitative data analysis
In this research, in order to analyze the qualitative data obtained from the interviews,
the theme analysis method is used. Theme analysis is a method of determining, analyzing, and
expressing patterns (themes) within data. This method, at a minimum, organizes the data and
describes it in detail. But it can go beyond this and interpret different aspects of the research
topic. The six stages of theme analysis are described below (Clark and Brown, 2016):
Step 1. Prepare and familiarize with the data: Before analyzing the data, the data should
be easy to work with.
Step 2. Creating the initial codes: The second step begins when the researcher has
organized, read, and become familiar with the data.
Step 3. Search for Themes: This step involves categorizing different codes into potential
themes, and sorting all the summaries of the encoded data into specified themes.
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Step 4. Creating meanings and concepts: In this stage, the researcher needs to move
more freely and have a productive and exciting mind.
2-5-3- Quantitative Data Analysis:
In the present study in order to the analysis of the quantitative data, two multi- criterion
decision making methods were used that are explained as below in the framework of data
analyzing steps:
DEMATEL Method
Gabus and Fontla (1972) suggest a method for DEMATEL implementation that has
been used in the present study. The output of the noted method in this study, is the identification
of the most important criteria of reward allocation and expected consequences of the reward
plan among the identified factors and consequences in order to go inside the qualitative blanks
of the approach of the expansion of Fuzzy qualitative performance.
- In the first step, the initial direct relation matrix A = [aij] is formed using the opinions
of experts. Where A is a non-negative matrix n × n and aij represents the direct effect of factor
i on factor j.
In the second step, the initial direct relationship matrix must be normalized. The
normalized direct relation matrix is obtained from Equation 2.
2
In the third step, using Equation 3, we obtain the total relational matrix T. The tij
component represents the indirect effects of factor i on factor j.
3
- In the fourth step, the sum of the rows and columns of the matrix T is calculated. ri
and cj are obtained through equations 4 and 5, respectively.
4
5
A
a
D
ni
n
j
ij
1
1
max
1
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- In the fifth step, by calculating the values of ri + ci and ri-ci, causal and influential
factors and disabled factors are identified.
- In the sixth step, the causal relationship diagram is made based on the values of ri +
ci and ri-ci.
Scope of Research
This research started from the beginning of spring 2019 and lasted until the end of
summer 2019.The location of research is a number of construction companies in Mashhad city
that have used the reward plan or intend to implement the reward plan. The specialty of this
research is human resource management. In this research, the most important criteria for reward
allocation in construction companies and their relationship with the consequences of the
implementation of this project in construction companies are examined.
Results
After a comprehensive review of the literature and research background, the most
important identified criteria for reward allocation are presented in Table 1.
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Table 1
Identified criteria for reward allocation of research literature
The Criterion of Reward
Allocation
Research
The quantity of Duty
Mozaffar (1996) Yousefpoor (1998) Rahbari (2000) Vafaee
(2000) Alem Tabriz (2002) Metis and Jackson (2009) De Senzo
and Robins (1998) Chai (2010)
The quality of Duty
Royaee (1991) Yoosefpoor (1998) Rahbari (2000) Vafaee
(2000) Tizro (2001) Alem Tabriz (2002) Metis and Jackson
(2009) Aplbam and Shapiro (1992)
The hours of presence
Sa’adat (2007) Metis and Jackson (2009) De Senzo and Robins
(1998)
Collaboration and Team working
Metis and Jackson (2009) Sepehri Rad (2011) De Senzo and
Robins (1998)
Effectiveness
Royaee (1992) Taheri (2003) Wang (2004)
Performance
Royaee (1992) Vafaee (2000) Alem Tabriz (2002) Taheri
(2003) Saadat (2007) Sepehri Rad (2011)
Profitability
Royaee (1992) Anvari Rostami( 2001) Chai ( 2001)
Efficiency
Royaee (1992) Anvari Rostami( 2001) Alem Tabriz ( 2002) Li
wan (2007) Onishi ( 2013)
Job and work Experience
Rahbari (2000) Vafaee (2000) Tizro (2001) Alem Tabriz (2002)
Job Condition
Alem Tabriz (2002) Taheri (2003) Sa’adat (2007) Moslehi and
ZafarKhan (2010)
Discipline
Vafaee (2000) Tizro (2001) Alem Tabriz (2002) Sepehri Rad
(2011)
Innovation
Yoosefpoor (1998) Tizro (2001) Alem Tabriz (2002) Taheri
(2003) Sepehri Rad (2011) De Senzo and Robins (1998) Chai
(2010) Onishi (2013)
Skill and Knowledge
Yoosefpoor (1998) Seyed Javadin (2003) Sa’adat (2007)
Sepehri Rad (2011) De Senzo and Robins (1998) Cornilson et
al. (2011)
Profession Ethics
Tizro (2001) Sepehri Rad (2011) De Senzo and Robins (1998)
Li wan (2007)
Interested persons satisfaction
Rahbari (2000) Tizro (2001) Chai (2010)
Graduation
Rahbari (2000) Vafaee (2000) Tizro (2001)
Qualitative part of the research
By reviewing the results of literature review and analyzing the data obtained from
interviews, eight criteria for reward allocation and ten consequences of reward plan
implementation were identified, which are presented in Tables 2 and 3 below. Criteria and
consequences are introduced in these tables, which in addition to the results of data analysis,
have been approved by various research literature.
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Table 2
Final criteria for reward allocation in construction projects (extracted from the
qualitative part of research)
Interview
Researcher
Criterion
Tag
8
7
6
5
4
3
2
1
*
*
*
*
*
Royaee (1992) Vafaee (2000)
Alem Tabriz (2002) Taheri
(2003) Saadat (2007) Sepehri Rad
(2011)
Project
performance
C1
*
*
*
*
*
Royaee (1991) Taheri (2003)
Wang (2014)
Li Wan (2017) Onishi (2020)
Doing Duties
C2
*
*
*
Yoosefpoor (1998) Tizro (2001)
Alem Tabriz (2002) Taheri
(2003) Sepehri Rad (2011) De
Senzo and Robins (1998) Chai
(2010) Onishi (2013)
creativity
and
innovation
C3
*
*
Metis and Jackson (2009) Sepehri
Rad (2011) De Senzo and Robins
(1998)
team work
C4
*
*
Rahbari (2000) Tizro (2001) Chai
(2010)
Satisfaction
of
stakeholders
C5
*
*
Yoosefpoor (1998) Seyed
Javadin (2003) Sa’adat (2007)
Sepehri Rad (2011) De Senzo and
Robins (1998) Cornilson et al
(2011)
Knowledge
and ability
to use it
C6
*
*
*
*
Royaee (1992) Anvari Rostami
(2001) Metis and Jackson (2018)
Aplbam and Shapiro (1992)
Profitability
And value
creation
C7
*
*
Vafaee (2000) Tizro (2001) Alem
Tabriz (2002) Sepehri Rad (2011)
De Senzo and Robins (1998) Li
wan (2017)
Professional
Ethics
C8
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Table 3
Expected consequences of the implementation of the reward plan in construction projects
(extracted from the qualitative part of the research)
interview
research fellow
Criterion
Tag
8
7
6
5
4
3
2
1
*
*
*
*
*
*
*
Mozaffari(1996) Yoosefpoor(
1998) Abdol Abadi et al(
2005) Cornilson et al ( 2020)
Onishi( 2020)
Increase
employee
motivation and
job satisfaction
O1
*
*
*
*
Yoosefpoor( 1998)
AbdolAbadi et al( 2005)
Establishment
organizational
justice
O2
*
Tizro( 2000)
Improvement
of customer
and
stakeholder
satisfaction
O3
*
*
*
Yosefpoor( 1998) Tizro (
2000)
Improve
effectiveness
O4
*
Mozaffari ( 1995) Tizro (
2000) Lai et al ( 2020)
Increasing
safety
O5
*
Shimon and Rendal( 1999)
Agrel et al ( 2002) Onishi
(2020)
Promoting
creativity and
innovation
O6
*
*
*
*
*
Yoosefpoor (1998) Tizro(
2001) Agrel et al( 2002)
Improving
Performance
O7
*
*
Shimon and Rendal ( 1998)
Desler( 1999)
Increase
profitability
O8
*
Agrel ( 2002)
Staff learning
and personal
growth
O9
Clustering and identifying the most effective criteria and consequences
Clustering of reward allocation criteria
In this part of the research, the 8 reward allocation criteria obtained in the qualitative
part of the research are clustered using the Demetel method to identify the final and causal
reward allocation criteria. In addition to clustering, data analysis using DEMETEL helps to
evaluate the relationships and interrelationships between reward allocation criteria. In this step,
the criteria are divided into two groups of cause and effect factors, and the cause criteria are
entered due to the greater importance of the ranking process by using fuzzy quality
performance expansion. In the following, data analysis using DEMETEL method is presented.
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Formation of direct impact matrix of reward allocation criteria
In this step, first, using the criteria presented in Table 2, experts were asked to determine
the impact of each criterion on other criteria, by use of the numbers 0 (no effect), 1 (Low
impact), 2 (high impact) and 3 (very high impact) in order to determine the effects of each of
criteria on the other creteria. Then by use of the arithmetic mean to we reached summarize the
opinions of experts (Wu, 2018). Table 4 summarizes the 8 expert opinions that were
interviewed in the qualitative section, and in fact the matrix shows the direct impact. This
summation is calculated using Equation 6. In this regard, n is the number of criteria and m is
the number of experts.
6
m
a
nj
ni
m
k
ijk
1
1
1
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Table 4
Summary of expert opinions using arithmetic mean (direct impact matrix) for
reward allocation criteria
Factors
Projec
t
perfor
mance
(C
1
)
Duty
(C
2
)
Cretivity
and
Innovati
on
(C
3
)
Team
Work
(C
4
)
Stakeho
lders
satisfact
ion
(C
5
)
Knowled
ge and
ability to
use it
(C
6
)
Profita
bility
and
Value
creatio
n
(C
7
)
Prof
essio
nal
Ethi
cs
(C
8
)
Project
performance
(C
1
)
0.000
1.000
1.000
2.125
3.000
1.000
2.500
1.12
5
Duty
(C
2
)
3.000
0.000
1.125
1.500
3.000
1.000
2.125
1.00
0
Cretivity and
Innovation
(C
3
)
3.000
2.000
0.000
1.500
2.125
2.000
3.000
2.00
0
Team Work
(C
4
)
2.125
2.500
2.000
0.000
2.000
1.000
2.500
2.00
0
Stakeholders
Satisfaction
(C
5
)
1.000
1.000
1.000
2.000
0.000
1.000
2.000
2.00
0
Knowledge and
ability to use it
(C
6
)
2.000
3.000
3.000
1.500
2.125
0.000
3.000
2.00
0
Profitability
and Value
creation
(C
7
)
2.000
1.000
1.000
1.000
3.000
1.000
0.000
1.00
0
Professional
Ethics
(C
8
)
2.000
3.000
1.500
3.000
2.500
2.000
2.000
0.00
0
Formation of normalized direct impact matrix of reward allocation criteria
In this step, the direct effect matrix is normalized using the equation 2 . Table 5 shows
the normalized direct impact matrix.
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Table 5
Normalized direct impact matrix
Factors
C
1
C
2
C
3
C
4
C
5
C
6
C
7
C
8
C
1
0
0.0602
0.0602
0.1278
0.1805
0.0602
0.1504
0.0677
C
2
0.1805
0
0.0677
0.0902
0.1805
0.0602
0.1278
0.0602
C
3
0.1805
0.1203
0
0.0902
0.1278
0.1203
0.1805
0.1203
C
4
0.1278
0.1504
0.1203
0
0.1203
0.0602
0.1504
0.1203
C
5
0.0602
0.0602
0.0602
0.1203
0
0.0602
0.1203
0.1203
C
6
0.1203
0.1805
0.1805
0.0902
0.1278
0
0.1805
0.1203
C
7
0.1203
0.0602
0.0602
0.0602
0.1805
0.0602
0
0.0602
C
8
0.1203
0.1805
0.0902
0.1805
0.1504
0.1203
0.1203
0
Formation of the total impact matrix of all reward allocation criteria
In this step, the total effect matrix is calculated using the equation 3. Table 6 shows the
total direct impact matrix.
Table 6
Total Matrix
Factors
C
1
C
2
C
3
C
4
C
5
C
6
C
7
C
8
C
1
0.3381
0.3513
0.2972
0.4127
0.5696
0.2672
0.5181
0.3289
C
2
0.5195
0.3099
0.3176
0.4038
0.6013
0.2812
0.5274
0.3386
C
3
0.6134
0.5016
0.3210
0.4812
0.6679
0.3905
0.6728
0.4563
C
4
0.5333
0.4918
0.3978
0.3636
0.6128
0.3158
0.6018
0.4255
C
5
0.3670
0.3299
0.2763
0.3792
0.3729
0.2496
0.4561
0.3462
C
6
0.6024
0.5800
0.5004
0.5066
0.7054
0.3048
0.7094
0.4813
C
7
0.3986
0.3095
0.2633
0.3180
0.5141
0.2390
0.3343
0.2864
C
8
0.5819
0.5692
0.4175
0.5682
0.7010
0.3984
0.6412
0.3630
Determining the internal relations of reward allocation criteria
In this step, we first calculate the values ri + ci and ri-ci using equations 4 and 5. Tables
7 and 8 show these values for each criterion. Then, based on the obtained values, we draw the
causal diagram of the reward allocation criteria, which is shown in Figure 3-4. After calculating
the values ri + ci and ri-ci, the causal diagram you see in Figure 4 is drawn.
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Table 7
The values of r and c for each factor
Factors
C
1
C
2
C
3
C
4
C
5
C
6
C
7
C
8
r
C
1
0.3381
0.3513
0.2972
0.4127
0.5696
0.2672
0.5181
0.3289
3.0831
C
2
0.5195
0.3099
0.3176
0.4038
0.6013
0.2812
0.5274
0.3386
3.2993
C
3
0.6134
0.5016
0.321
0.4812
0.6679
0.3905
0.6728
0.4563
4.1047
C
4
0.5333
0.4918
0.3978
0.3636
0.6128
0.3158
0.6018
0.4255
3.7424
C
5
0.367
0.3299
0.2763
0.3792
0.3729
0.2496
0.4561
0.3462
2.7772
C
6
0.6024
0.58
0.5004
0.5066
0.7054
0.3048
0.7094
0.4813
4.3903
C
7
0.3986
0.3095
0.2633
0.318
0.5141
0.239
0.3343
0.2864
2.6632
C
8
0.5819
0.5692
0.4175
0.5682
0.701
0.3984
0.6412
0.363
4.2404
C
3.9542
3.4432
2.7911
3.4333
4.745
2.4465
4.4611
3.0262
-
Table 8
ri + ci and ri-ci values
Factors
R
i
+c
i
r
i
-c
i
C
1
7.0373
- 0.8711
C
2
6.7425
- 0.1439
C
3
6.8958
1.3136
C
4
7.1757
0.3091
C
5
7.5222
-1.9678
C
6
6.8368
1.9438
C
7
7.1243
-1.7979
C
8
7.2666
1.2142
Figure 2
Causal diagram of reward allocation criteria
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The results of data analysis at this stage show that according to ri + ci values,
stakeholder satisfaction (C5), professional ethics (C8), teamwork (C4) and profitability and
value creation (C7) are the factors which have both a high impact on other criteria and a high
impact from other criteria. But the factors of creativity and innovation (C3), teamwork (C4),
knowledge and ability to use it (C6) and professional ethics (C8) according to the positive
values of ri-ci, are located in the cluster of causal criteria. Also, the factors of project
performance (C1), task performance (C2), stakeholder satisfaction (C5) and value creation and
profitability (C6) with respect to the negative values of ri-c, are known in the cluster of disabled
criteria.
The causal criteria that have the greatest impact on other criteria and therefore should
be used in designing an effective reward system are: knowledge and ability to use it (C6),
creativity and innovation (C3), professional ethics ( C8) and teamwork (C4). But since the
DEMATEL method is a tool that is used always to identify the internal relationships between
concepts than rather than rank them Therefore, it is necessary to prioritize the four criteria of
identified causes by using a complementary multi-criteria decision method. For this purpose,
the fuzzy quality performance expansion approach is used.
Clustering the expected consequences of the implementation of the reward plan.
In this part of the research, the 9 expected consequences of the implementation of the
reward plan, which are extracted from the qualitative part, are clustered using the DEMATEL
method to identify the most effective consequences. In addition to clustering, data analysis
using DEMATEL helps to evaluate the expected consequences of the implementation of the
reward plan and identify their internal relationships. In this step, the consequences are divided
into two groups: cause and effect consequences. And because consequences are entered due to
their greater importance in the ranking process by using fuzzy quality performance expansion.
In the following, data analysis using DEMATEL method is presented.
Formation of a matrix of direct impact of the expected
consequences of the implementation of the reward plan
In this step, first, using the expected consequences of the implementation of the reward
plan presented in Table 3, experts were asked to in order to determination of impacts of each
of the expected consequences on the others and to identification the internal relationship among
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these consequences by DEMATEL, express their opinion about the impact of each of the
consequences on the other consequences and with the numbers 0 (no impact), 1 (low impact),
2 (high impact) and 3 (very high impact). Then the arithmetic mean led to summarize the
opinions of experts. Table 9 summarizes the opinions of experts in this regard.
Discussion
The main purpose of this study was to identify and rank reward allocation criteria in
companies and construction projects. In this regard, during the research process, the following
measures were taken to achieve the research goal and answer these questions: In this regard, a
large number of reward allocation criteria were identified from the literature.
In this case, with the help of semi-structured interviews with construction industry
experts who had sufficient experience and knowledge in the implementation of the reward plan,
the most important criteria that can be used in construction projects were identified. In order to
prioritize the above criteria, it was necessary to identify the expected consequences of the
implementation of the reward plan in order to prioritize the reward allocation criteria based on
these consequences. The expected consequences of the implementation of the reward plan were
also identified with the help of semi-structured interviews.
In this regard, by using interviews and questionnaires from face-to-face meetings with
experts and then using DEMATEL method, the expected criteria were clustered and then the
criteria and causal consequences which had more impacts were identified. In fact, the most
important reason for using DEMATEL, in addition to identifying the internal relationships
among the criteria, is to identify the criteria that are known as the criteria of the cause and also
affect other criteria, ie the effect criteria. Another reason for clustering reward allocation
criteria and using causal criteria in the continuation of the research process is the fact that
interviews with industry experts show that designing a reward system with a wide variety of
criteria is very difficult and inefficient, and impose a heavy cost of performance evaluation on
the organization. Therefore, the use of DEMATEL and clustering of criteria helps, in addition
to reducing the number of used criteria , due to the use of causal and vital criteria, the role of
other criteria is also indirectly considered.
In this regard, while benefiting from the face-to-face meeting with experts and
questionnaires prepared using the fuzzy quality expansion approach as a complementary
method, reward allocation criteria were ranked. It is worth noting that the present study is
innovative in two aspects. The first aspect is the identification and ranking of reward allocation
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criteria in construction projects, which has received less attention due to the nature of this
industry and projects, and the second aspect is to provide a mixed qualitative and quantitative
approach that in addition to identifying and ranking reward allocation criteria and Identifying
the consequences of reward plan implementation also helps to identify the internal relationships
between criteria and consequences. In this section, it is tried to answer the research questions
in form of the description of the research findings. With a comprehensive review of the
literature on reward allocation criteria, the following 16 criteria were identified as the most
widely used reward allocation criteria:
- Quantity of tasks; - Quality of tasks; - Hours of presence at work; - Cooperation and
teamwork; - Effectiveness; - Performance; - Profitability; - Efficiency; - work
experience; - working conditions; - Discipline; - creativity and innovation; - Skills and
knowledge; - Ethics; - stakeholders satisfaction; - education;
The results of conducting semi-structured interviews with experts and analyzing the
data obtained from the interviews using the theme analysis method show that the
following 8 criteria are the most important criteria in reward allocation in construction
projects:
- Project performance; - doing duties; - creativity and innovation; - team work; -
stakeholders satisfaction; - Knowledge and ability to use it;- Profitability and value
creation; - Ethics;
It should be noted that out of 13 criteria extracted from the interviews, 5 criteria were
again removed with the consideration of experts’ opinion, which can be considered as a kind
of innovation and localization of the subject. These criteria are : changeability spirit, quality of
work, duration of presence in the organization, level of experience and level of education. In
addition, the criterion of quality of work performance was removed from the criteria because
its evaluation is usually synonymous with performing the assigned tasks and in accordance
with the criteria of performance evaluation and stakeholder satisfaction. The three criteria of
length of presence in the organization, level of experience and level of education, although
used in many companies as criteria for reward allocation, but since the reward is related to non-
fixed payment, and the criteria of length of presence in the organization, the level of experience
and the level of education are usually included in the payments and fixed salaries of individuals,
were eliminated from the final criteria.
The results of the analysis of the data obtained from the interviews with the experts
show that there are other themes that need to be considered. One of the most important themes
discovered from qualitative data is the expected consequences of reward plan implementation.
In fact, the results of the interviews showed that it is not possible to prioritize the reward
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allocation criteria without considering the results of its implementation. This means that first
the managers' priority in implementing the reward plan must be determined, then the criteria
for reward allocation must be prioritized and the reward plan must be implemented. According
to the research findings, the most important consequences of the implementation of the plan
are:
- Increasing employee motivation and job satisfaction; - Establishing organizational
justice; - Improving customer and stakeholder satisfaction; - Improve effectiveness;-
Increase safety; - Promoting creativity and innovation; - Improving Performance; -
Increase profitability; - Learning and personal growth of employees;
The results of this research are in line with the following research. Yang and Chen
(2018) in them study presents a new payment system for active team members in each project.
Performance evaluation is performed without specifying a specific criterion and based on
judgments made with the help of fuzzy linguistic variables. In this system, four models are
proposed for different project management conditions. Maslahi and Zafar Khan (2019) have
studied the factors affecting the productivity of employees in construction projects and in spite
of considering factors such as temperature, relative humidity, type of work and the method
used. They have not pointed to the factors like payment and reward and its effect on the
efficiency.
Findings of the research after examining the internal relationships between reward
allocation criteria and their clustering using the DEMATEL method show that among the final
8 criteria, knowledge and ability to use it, creativity and innovation, professional ethics and
teamwork will be placed in the causal criteria cluster. And the criteria of project performance,
task performance, stakeholder satisfaction and value- profitability creation are placed in the
cluster of effect criteria. Also, although the DEMATEL method is not commonly used for
ranking and its function is to examine the internal relationships between the factors of a system,
but from the output of this method, the factors that should be considered more can be identified.
This is done by identifying the factors that generally have the greatest impact on the system
and receive the most impact from the system. Accordingly, the results of data analysis using
the DEMATEL method show that the criteria of stakeholder satisfaction, professional ethics,
teamwork and profitability and value creation have the greatest impact on the system and the
most impact from the system.
Also, findings of the research after examining the internal relationships between the
expected consequences of the reward plan implementation and their clustering using the
DEMATEL method show that among the 9 consequences, the learning and personal growth of
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employees, promoting creativity and innovation, increasing safety and establishment
Organizational justice is placed in the cluster of causal consequences. And the consequences
of increasing employee motivation and job satisfaction, improving customer and stakeholder
satisfaction, improving effectiveness, improving efficiency and increasing profitability are
placed in the cluster of effect consequences.
The results of this research are in line with the following research. Cornellison et al.
(2020) in their research show that employee satisfaction was higher in jobs where performance-
based pay was implemented than in other jobs. They then propose a model in which employees
with greater ability and higher risk tolerance receive greater rewards through performance-
based pay. With the implementation of this model, employee satisfaction was assessed equally
in all jobs, but employees in jobs that were paid based on performance and had a higher risk
tolerance, expressed higher satisfaction. Onishi (2020) examines the effects of service
compensation schemes on Research and Developement Organization of Japan staff
innovations. In this research, the evaluation criterion is the criteria based on income and
innovation and the results show that monetary incentives based on the performance of
inventions, lead to increasing the motivation of innovative employees.
Likewise, the results of data analysis using DEMATEL method show that the
consequences of improving efficiency, learning and personal growth of employees and
improving effectiveness have a high impact on other factors and a high impact from other
consequences of the implementation of the plan and therefore should be considered. After
identifying the effective criteria and consequences, by determination the relationship between
each of the criteria and expected consequences, as well as the correlation between the criteria
and determining the importance of the consequences for managers, the reward allocation
criteria were ranked. The results of this ranking show that the criterion of having professional
ethics is the most important criterion for reward allocation. After this criterion, is the criterion
of teamwork. After these two criteria are the criteria of creativity - innovation and knowledge-
ability to use it, respectively. These findings show that considering the work environment of
construction projects, maintaining discipline and having organizational commitment and
helping others is very important.
Conclusion
According to the results, it can be said that the professional ethics is the most important
criterion for reward allocation to the employees in the construction projects. findings show that
considering the work environment of construction projects, maintaining discipline and having
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organizational commitment and helping others is very important. Also, having the spirit of
teamwork and cooperation with others is very important for working in such environments.
One of the notable points in the findings of this study is the less attention paid by
construction managers to the use of labor quantity measurement indicators as a criterion for
reward allocation and more attention to quality criteria such as professional ethics, creativity,
etc., which shows the difference between the nature of the work and the end product of this
industry with manufacturing industries such as parts manufacturing.
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