Content uploaded by Ibrahim Mahamid
Author content
All content in this area was uploaded by Ibrahim Mahamid on Sep 25, 2022
Content may be subject to copyright.
Available via license: CC BY-NC-ND 4.0
Content may be subject to copyright.
International Journal of Advanced and Applied Sciences, 9(2) 2022, Pages: 160-166
Contents lists available at Science-Gate
International Journal of Advanced and Applied Sciences
Journal homepage: http://www.science-gate.com/IJAAS.html
160
Relationship between delay and productivity in construction projects
Ibrahim Mahamid *
Civil Engineering Department, Engineering Faculty, Arab American University, Jenin, Palestine
A R T I C L E I N F O
A B S T R A C T
Article history:
Received 30 September 2021
Received in revised form
24 December 2021
Accepted 26 December 2021
This study is conducted to recognize the major delay factors, the major
construction productivity factors, and to establish the relationship between
productivity and delay in construction projects in Saudi Arabia. A
questionnaire survey is performed to achieve study objectives. Fourteen-
time overrun factors and 13 construction productivity factors are listed in a
questionnaire form. Fifty contractors consultants are asked to rank the
identified factors according to their importance. The study also addresses the
relationship between labor productivity and time overrun based on data
collected from 34 building projects implemented in Saudi Arabia. Results
conclude that the top factors affecting delay in construction projects are:
poor labor productivity, poor coordination between construction parties,
lack of adequate manpower, bid award for lowest price, and mistakes in
design. It also indicates that the major labor productivity factors are:
payments delay, lack of labor experience, frequent change orders, rework,
and financial conditions of the contractor are ranked overall as the top 13
factors affecting labor productivity on construction sites. Regression analysis
for data collected from 34 building projects indicates a strong correlation
between the delay and labor productivity. It is hoped that the results of this
study will be helpful for construction parties and researchers in Palestine
and other developed and developing countries.
Keywords:
Buildings
Time overrun productivity
Residential
Labors
© 2022 The Authors. Published by IASE. This is an open access article under the CC
BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
1. Introduction
*
The construction industry is one of the biggest
dollar-generating segments of the economy in many
countries in the world. It varies from houses to
highways, schools, hospitals, plants, and many other
constructions. It pushes many other related
industries, such as concrete, lumber, steel, paint,
furniture, mining, paving, and shipping among other
industries. However, the construction industry is
complicated and associated with high risks, and
many factors influence the output of construction
projects. Enshassi et al. (2003) stated that “the
increasing complexity of infrastructure projects and
the environment within which they are constructed
place greater demand on construction managers to
deliver projects on time, within the planned budget
and with high quality.” One of the main problems in
construction projects is time overrun. It may be
expressed as a “percent difference between the
*
Corresponding Author.
Email Address: imahamid@ymail.com
https://doi.org/10.21833/ijaas.2022.02.018
Corresponding author's ORCID profile:
https://orcid.org/0000-0002-5357-1152
2313-626X/© 2022 The Authors. Published by IASE.
This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/)
actual completion time and the estimated
completion time, agreed by and between the client
and the contractor during the signing of the
contract” (Mahamid, 2017a). Ameh et al. (2010)
indicated that the history of the construction
industry is full of projects that were completed with
critical delay. For instance, Omoregie and Radford
(2006) found that the average time overrun in
Nigerian construction projects is 188%. Assaf and Al-
Hejji (2006) concluded that 70% of Saudi Arabian
construction projects were completed with critical
time overrun. In UAE, Faridi and El‐Sayegh (2006)
revealed that 50% of construction projects were
completed with schedule delay. Mahamid et al.
(2012) found that about 100% of highway
construction projects in Palestine were completed
with time overrun. Mahamid et al. (2012) concluded
that time overrun has negative effects on
construction projects in terms of cost increase,
conflicts, disputes, quality problems, and mistrust
between parties.
Productivity is simply defined as a ratio between
an output value and an input value used to produce
the output. It has its proven importance as a critical
factor for project success. Mahamid (2018) linked
labor productivity with a cost overrun; he concluded
a strong relationship between. Mahamid (2020)
Ibrahim Mahamid/International Journal of Advanced and Applied Sciences, 9(2) 2022, Pages: 160-166
161
found a high correlation between labor productivity
and rework in building projects. Thus labor
productivity plays a critical role in the financial
success of a project (Liu and Ballard, 2008).
However, some previous studies found that
construction productivity variations are one of the
most daunting problems faced by the construction
industry, especially those in developing countries
and it is one of the main factors affecting cost and
time overrun (Mahamid et al., 2013; Liu and Ballard,
2008).
Literature review indicates that very few studies
have investigated the relationship between labor
productivity and time overrun in building projects.
This study addresses the problems of labor
productivity and time overrun in Saudi Arabia.
Furthermore, it investigates the relationship
between construction productivity and delays in
construction projects. This paper aims at (1)
identifying factors affecting labor productivity in
construction projects, (2) identifying factors
affecting delay, (3) establishing the relationship
between delay and labor productivity.
2. Previous studies
2.1. Construction productivity on sites
Liu and Ballard (2008) stated that despite the
advances in technology, the construction industry is
still labor-intensive. Labors continue to account for
between 30% and 50% of construction projects.
Mahamid (2020) stated that labors are success key
to any construction project and enhancing
construction productivity is the main issue to
increase profit and to complete projects on time. In
his study, Mahamid (2020) found a strong
relationship between labor productivity and rework
in construction projects. He concluded that lack of
manpower experience causes mistakes and misuse
of resources that negatively affect productivity.
Overall, he indicated that the main factors affecting
labor productivity in building projects are: Lack of
experience, rework, delay in payments, mistakes,
and material shortages. Through a questionnaire
survey, Mahamid (2018) found that the main factors
affecting labor productivity in highway construction
projects are: Material shortage, inaccurate
specifications, and poor labor experience. Montaser
et al. (2018) conducted a questionnaire survey to
test the main productivity factors in concrete works.
They concluded that design changes and equipment
factors are the top affecting factors.
Sweis et al. (2017) reported that “residential
construction involves labor-intensive tasks where
workers are frequently confronted with problems
that could lead to demotivation. Demotivation is
caused not simply by a lack of motivators but the
existence of certain situations that cause
dissatisfaction and discourage individuals, therefore
reducing overall productivity potential.” In their
study, they found that working overtime, quality
requirements, and inaccurate specifications are key
factors of manpower demotivation in residential
projects. Among various factors affecting
construction productivity shortage of materials,
equipment problems, improper planning, lack of
supervisor’s experience, delay in inspections,
rework, and payments delay topping the list. In
Saudi Arabia, Mahamid et al. (2013) addressed the
main productivity factors to be: Poor skills of labors,
poor communication between parties, delay in
payments, and bad working environment. Robles et
al. (2014) revealed that the top factors affecting
construction productivity in Spain are: Delay in
material supply, inaccurate project documents, clear
daily assignment, lack of equipment, and poor labor
skills. Alaghbari et al. (2019) concluded that the top
five factors affecting labor productivity in
construction projects are: Lack of labor experience,
shortage in materials on-site, poor site management,
shortage in materials in the market, and political
situation.
Abdel-Hamid and Abdelhaleem (2020)
concluded a strong relation between cost overrun
and poor labor productivity. Nasirzadeh et al. (2020)
investigated labor productivity factors in Australian
multi-story building construction projects. They
concluded that the top factors include: Lack of skilled
and experienced labors, fatigue, poor supervision,
award rates, and communication problem with
foreign workers.
2.2. Factors affecting time overrun in residential
projects
The construction industry is one of the most
competitive industry and it involved a high level of
risks due to the many resources and parties involved
in the projects. Therefore, completing projects with
limited time is one of the main issues that help in
improving the industry. However, the history of
construction projects is full of projects completed
with time overrun (Kaliba et al., 2009; Mahamid,
2017b). Mahamid et al. (2012) defined time overrun
as “the time difference between the actual
completion time and the estimated completion time,
agreed by and between the client and the contractor
during the signing of the contract.” Previous studies
revealed time overrun in construction projects
ranging from 30% to 188% (Omoregie and Radford,
2006; Faridi and El‐Sayegh, 2006; Assaf and Al-Hejji,
2006; Mahamid et al., 2012; Mahamid, 2017a).
Gopang et al. (2020) concluded that the main time
overrun factors in a building project in Saudi Arabia
are: Late decisions by the client, changes in design,
and delay in approvals. Some previous studies found
a good relationship between site conditions and time
overrun in building projects (Mahamid, 2017b;
Memon et al., 2012). Mahamid's (2017a) study
linked delay in a construction project with improper
planning at the early stages of projects. In his study,
Mahamid (2017a) revealed a relationship between
time overrun and conflicts, disputes, and arbitration
between construction parties.
Through a questionnaire survey in Saudi Arabia,
Mahamid et al. (2015) found that the top delay
Ibrahim Mahamid/International Journal of Advanced and Applied Sciences, 9(2) 2022, Pages: 160-166
162
factors include: Bidding policy, inaccurate
specifications, rework, lack of labors experience,
poor productivity, and late changes.) The top time
overrun factors in a construction project in Kenya
according to Atibu (2015) are Payments delay by
clients, improper planning, and weather effects.
In a study conducted by Mahamid et al. (2012) to
identify, analyze and rank delay factors in highway
projects in Palestine, contractors revealed that the
top factors include: Political situation, delay in
payments, delay in decision making, and poor
productivity while consultants indicated that the top
factors are: political situation, bidding strategy,
equipment shortage and misuse of schedule. Zafar et
al. (2019) conducted a study in Pakistan to
investigate the time overrun risk factors in highway
projects. They concluded that the top factors are:
Stakeholder interference and insecurity threats, lack
of contractors' experience in the line of work, lack of
labor productivity, poor contract management, and
shortages in materials. Johnson and Babu (2020)
stated that time overrun is the main indicator of
project success in the construction industry. They
found that the top five causes for time overrun are:
variations in design, tight schedules, unrealistic
completion dates projected by clients, delay in
government approvals, inaccurate time estimation
by the consultants, and frequent change orders.
Lindhard et al. (2020) stated that “for years, the
construction industry has looked for ways to avoid
time-overruns in construction. Despite previous
research mapping the factors affecting time
performance, site-managers have difficulties in
reducing the time-overrun.” They believed that time
overrun factors are categorized under the following
groups: (1) Construction design, (2) Connecting
works, (3) External conditions, (4) Workforce, (5)
Components and materials, (6) Space, (7) Equipment
and machinery.
3. Research methods
The objective of the study is to establish the
relationship between delay and labor productivity in
building projects implemented in Saudi Arabia. To
achieve this, a structured questionnaire is used to
collect primary data for the study. A questionnaire
survey was used to elicit the attitude of contractors
and consultants towards labor productivity factors
and delay factors in construction projects. 13 factors
that might affect labor productivity are considered in
this study, while 14 factors believed to affect time
overrun are identified. These factors are identified
based on previous studies conducted in the same
area and as recommended by local experts in
residential projects. Each respondent, from the
targeted contractors and consultants, is asked to
state the level of importance of each factor using an
ordinal 5-point scale as follow: 5 (very high), 4
(high), 3 (moderate), 2 (little), and 1 (very little). A
chance is given for each respondent to add and rate
other factors that are believed to affect either labor
productivity or time overrun.
The target population is the total number of
contractors the total number of consultants who
have experience in construction projects.
The questionnaire is distributed to 50 contractors
and 50 consultants. The contractors and consultants
are selected from an available list. Eighty-four (84)
questionnaires are received (84 %) as follow: 46
(92%) from contractors, and 38 (76%) from
consultants. The targeted participants have an
average experience of more than 10 years in building
projects.
Fig. 1 shows the respondents’ positions in their
organizations. It shows that the respondents
experienced office engineers are (13.6%), site
engineers (26.5%), designers (16.3%), construction
managers (18.2%), project managers (12.8%), and
others (12.6%).
3.1. Data analysis
Excel statistical tools are used to analyze the
information returned form the respondents. The
suggested time overrun factors and labor
productivity factors are ranked by the measurement
of the importance index which is a formula used to
rank the factors based on impact level as identified
by the participants (Eq. 1).
Importance Index (%)=∑ a (n/N)100/5 (1)
where, a is the constant expressing weighting given
to each response (ranges from 1 for very little up to
5 for very high); n is the frequency of the responses;
N is total number of responses.
3.2. Spearman rank correlation
To measure the correlation between contractors
and consultants on the importance of the identified
factors, the Spearman rank correlation test is used.
Judgment on the correlation is based on the value of
Spearman correlation (rs) such that: rs value of (+1)
shows a perfect positive correlation, rs value of (-1)
shows a perfect negative correlation, and values
between (-1) and (+1) shows a correlation less than
perfect. The value of rs is computed using Eq. 2
(Harnett and Murphy, 1975):
(2)
where,
=Spearman rank correlation coefficient (the
agreement between contractors and consultants);
d=difference between ranks on one variable and
ranks on the other variable; n=number of factors.
4. Results and discussion
4.1. Ranking of factors affecting delay in
construction projects
Literature review and feedback from local experts
in residential buildings identified 14 delay factors as
shown in Table 1. Using a 5-point Likert scale,
Ibrahim Mahamid/International Journal of Advanced and Applied Sciences, 9(2) 2022, Pages: 160-166
163
contractors and consultants rank the identified
factors. The overall ranking shows that the top
factors affecting time overrun in residential projects
are poor labor productivity, poor coordination
between construction parties, lack of adequate
manpower, bid award for lowest price, and mistakes
in design. These factors are recognized by both
contractors and consultants as top factors, but in a
different order as shown in Table 1.
Fig. 1: Respondents’ positions
“Poor labor productivity” implies that activity
takes more time than planned. Poor productivity
could be because of a series of factors such as
payment delay, low wages, bad relations between
labors, and poor skills. This result is in line with
Mahamid (2017a). “Poor coordination between
construction parties”; coordination between
construction parties during all project stages is a
success key, it helps in determining the project needs
and to be ready on time. Inversely, poor coordination
leads to interruptions and disputes between parties
that cause time overrun. This result is in line with
Mahamid et al. (2015). “Lack of adequate
manpower” is a major problem in the Saudi
construction market because of limitations and extra
taxes implied by the government. This result agrees
with Mahamid et al. (2015). “Bid award for lowest
price” is the main problem that leads to time
overrun. This is because a contractor with the lowest
price normally is a contractor with low
qualifications. “Mistakes in design” indicates that
change orders and rework are needed which implies
that more time and effort are required to complete
the same activity. This result is in line with Mahamid
et al. (2015), Kaliba et al. (2009), and Mahamid
(2017a).
Table 1: Ranking of factors affecting delay in construction projects
Factor
Contractors
Consultants
Overall
IMP.I
Rank
IMP.I
Rank
IMP.I
Rank
Poor labor productivity
82.14
1
82.33
2
82.23
1
Poor coordination between construction parties
78.12
3
84.25
1
80.89
2
Lack of adequate manpower
81.36
2
80.07
3
80.78
3
Bid award for lowest price
77.50
4
77.63
5
77.56
4
Mistakes in design
73.00
5
79.49
4
75.94
5
Unreasonable project time frame
71.12
7
74.86
6
72.81
6
Late design work
72.89
6
69.92
8
71.55
7
Poor relationship between managers and labors
67.59
9
72.86
7
69.97
8
Lack of coordination between design and contractors
68.47
8
65.81
10
67.27
9
Lack of contractor experience
67.41
10
66.97
9
67.21
10
Disputes on site
64.76
11
63.66
12
64.26
11
Additional work
62.11
13
65.19
11
63.50
12
Poor resource management
62.99
12
59.17
14
61.26
13
Effects of weather
61.17
14
60.3
13
60.78
14
4.2. Ranking of factors affecting labor
productivity
Thirteen (13) affecting labor productivity in
residential projects are identified from literature and
experts’ feedback as presented in Table 2.
Respondents are asked to identify the importance of
the identified factors based on their influence on
labor productivity. The result is presented in Table 2.
As shown in Table 2, payments delay, lack of
labor experience, frequent change orders, rework,
and financial conditions of the contractor are ranked
overall as the top 13 factors affecting labor
productivity in residential projects. The same factors
are identified by both contractors and consultants as
the top factors but in a different order. “Payments
delay by the client” is ranked as the top factor
affecting labor productivity. It affects the ability of
12.80%
18.20%
16.30%
26.50%
13.60%
12.60%
Project manager construction manager design engineer site engineer office engineer others
Ibrahim Mahamid/International Journal of Advanced and Applied Sciences, 9(2) 2022, Pages: 160-166
164
the contractor to pay for his labors, which negatively
affects their moral, loyalty, and motivation. “Lack of
labor experience”; is an “established fact from
learning effect that if the same task or project is
repeated more than one time, it will be controlled
better with less time and less cost” (Mahamid et al.,
2012). This leads to many problems on construction
sites such as mistakes, rework, and poor
productivity. “Frequent change orders” and “rework”
indicate that more time and effort are required to
redo the same activity. These results are in line with
Kaliba et al. (2009), Mahamid et al. (2015), and
Mahamid (2017a).
Table 2: Ranking of labor productivity factors in construction projects
Factor
Contractors
Consultants
Overall
IMP.I
Rank
IMP.I
Rank
IMP.I
Rank
Payments delay by the client
78.90
3
82.25
1
80.42
1
Lack of labor experience
81.50
1
77.18
5
79.55
2
Frequent change orders
79.36
2
78.26
4
78.86
3
Rework
77.21
4
80.13
2
78.53
4
Financial conditions of contractor
76.47
5
79.15
3
77.68
5
Low wages
75.25
6
76.89
6
75.99
6
Material shortages
72.51
8
74.55
8
73.43
7
Poor site management
73.39
7
73.13
9
73.27
8
Low quality of raw materials
68.50
10
74.69
7
71.30
9
Equipment’s shortages
69.28
9
72.16
10
70.59
10
Lack of supervisor’s experience
68.40
11
68.23
13
68.32
11
Project size
63.56
12
71.09
11
66.97
12
Bad labor relations
57.27
13
70.12
12
63.08
13
4.3. Spearman rank correlation
The correlation between contractors and
consultants on the importance of delay factors and
labor productivity factors is tested using Eq. 2.
Results indicate a good correlation between
contractors and consultants on the importance of
delay factors (rs=0.85) and labor productivity factors
(rs=0.82). The results of Correlation values show that
the study is reliable.
4.4. Predictive models of labor productivity
impact on delay on construction sites
One of the main objectives of this study is to
establish the relationship between labor
productivity and delay. To achieve this objective,
data from 34 building projects implemented in Saudi
Arabia over the years 2018-2020 (during the last 3
years) are gathered. Records from the targeted
contracting firms are used to gather the required
data. Then the data have been checked to ensure
none double-counted and all are clearly defined. The
collected data included information about the time
overrun and labor productivity in ceramic works and
bricks works. Some considerations are taken to
when the data is collected such as Number of floors
(2 floors (31%), 3 floors (37%), and 4 floors (32%)),
a number of projects per year (2018 (35%), 2019
(35%), 2020 (30%), and all projects are residential
buildings. After that, regression linear analysis is
used to test the relation between the considered
variables. According to Mahamid (2020), linear
regression analysis is a widely used and well-defined
approach to describe the relationship between
variables (dependent and independent).
In the developed models, the dependent variable
is time overrun and the independent variable is
labor productivity. Eq. 3 shows the standard form of
linear regression:
Y=α + βX (3)
where: Y=delay (% of planned duration); X=labor
productivity; α=intercept; β=coefficient of labor
productivity.
4.5. Predictive model of labor productivity
impact on delay in ceramic works
Fig. 2 shows the relationship between delay and
labor productivity in ceramic works. It shows an
inverse relationship between them: The higher
productivity the lower delays and vice versa. The
results show that the average delay in ceramic works
is 49.73 and the average labor productivity is
31.84m2/day (for 2 labors crew). Model 1 describes
the impact of labor productivity on delays in ceramic
works. It is observed that the mathematical model
expressed in model 1 can well predict the impact of
labor productivity on delay. Therefore R2=0.75,
F(1,33)=152.31, p=0.000 (Table 3). The coefficient of
labor productivity gives the magnitude of change in
time overrun due to change in labor productivity
which in this case is 2.91. This indicates that a unit
increase in ‘labor productivity’ results in about a
2.91 unit decrease in time overrun and vice versa,
while the intercept (constant) is 142.53. The
prediction model is presented in the following
Equation:
Model(1)
where; Y is delay in ceramic works (%), X is labor
productivity in ceramic works (m2/day).
Ibrahim Mahamid/International Journal of Advanced and Applied Sciences, 9(2) 2022, Pages: 160-166
165
Fig. 2: Delay vs labor productivity in ceramic works
Table 3: Regression statistics of model 1
Regression Statistics
Coefficients
t Stat
P-value
R Square
0.75
Intercept
142.53
5.21
0.00
Observations
34
Labor productivity in ceramic works (m2/day)
-2.91
5.98
0.00
F
152.31
5. Summary and conclusion
This study is conducted to identify the major
delay factors, the major labor productivity factors,
and to establish the relationship between labor
productivity and delay in construction projects. It
concludes that the top factors affecting delay in
construction projects are: Poor labor productivity,
poor coordination between construction parties, lack
of adequate manpower, bid award for lowest price,
and mistakes in design. It also indicates that the
major labor productivity factors are: Payments
delay, lack of labor experience, frequent change
orders, rework, and financial conditions of the
contractor are ranked overall as the top 13 factors
affecting labor productivity in construction projects.
Spearman rank correlation test shows a good
agreement between contractors and consultants on
the importance of delay factors (rs=0.85) and labor
productivity (rs=0.72). Therefore, the study is
reliable.
To establish the regression models that describe
the relationship between delay and labor
productivity, data from 34 building projects
implemented in Saudi Arabia are gathered. Delay is
considered as the dependent variable while labor
productivity is the independent variable. The
predictive model reveals a significant relationship
between delay and labor productivity. Equally, the
nature of the relationship is inversely proportional
i.e. the higher the labor productivity the lower the
delay, and vice versa.
The following points are recommended to
improve construction productivity on sites and to
minimize delay: (1) Continuous training programs
should be conducted to develop labor skills and
managerial skills of construction participants, (2)
Owners should pay progress payments on time, so
the contractors could pay for labors and other
resources on time, (3) Owner should check for
contractor’s qualifications before awarding the
contract. Bidding on the lowest price basis should be
improved.
Compliance with ethical standards
Conflict of interest
The author(s) declared no potential conflicts of
interest with respect to the research, authorship,
and/or publication of this article.
References
Abdel-Hamid M and Abdelhaleem MH (2020). Impact of poor
labor productivity on construction project cost. International
Journal of Construction Management: 1-8.
https://doi.org/10.1080/15623599.2020.1788757
Alaghbari W, Al-Sakkaf AA, and Sultan B (2019). Factors affecting
construction labour productivity in Yemen. International
Journal of Construction Management, 19(1): 79-91.
https://doi.org/10.1080/15623599.2017.1382091
Ameh OJ, Soyingbe AA, and Odusami KT (2010). Significant factors
causing cost overruns in telecommunication projects in
Nigeria. Journal of Construction in Developing Countries,
15(2): 49-67.
Assaf SA and Al-Hejji S (2006). Causes of delay in large
construction projects. International Journal of Project
Management, 24(4): 349-357.
https://doi.org/10.1016/j.ijproman.2005.11.010
Atibu M (2015). An investigation into factors causing delays in
road construction projects in Kenya. American Journal of Civil
Engineering, 3(3): 51-63.
https://doi.org/10.11648/j.ajce.20150303.11
y = -2.9147x + 142.53
R² = 0.7509
0.00
10.00
20.00
30.00
40.00
50.00
60.00
70.00
80.00
90.00
0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00
Time overrun in ceramic works (%)
Labro productivity in ceramic works (m2/day)
Ibrahim Mahamid/International Journal of Advanced and Applied Sciences, 9(2) 2022, Pages: 160-166
166
Enshassi A, Liska R, El-Sawalhi NI, and Radwan I (2003).
Contributors to construction delays in Palestine. American
Professional Constructor, 27(2): 45-53.
Faridi AS and El‐Sayegh SM (2006). Significant factors causing
delay in the UAE construction industry. Construction
Management and Economics, 24(11): 1167-1176.
https://doi.org/10.1080/01446190600827033
Gopang RKM, alias Imran QB, and Nagapan S (2020). Assessment
of delay factors in Saudi Arabia railway/metro construction
projects. International Journal of Sustainable Construction
Engineering and Technology, 11(2): 225-233.
https://doi.org/10.30880/ijscet.2020.11.02.028
Harnett D and Murphy J (1975). Introductory statistical analysis
.
Addison-Wesley Publishing, Boston, USA.
Johnson RM and Babu RII (2020). Time and cost overruns in the
UAE construction industry: A critical analysis. International
Journal of Construction Management, 20(5): 402-411.
https://doi.org/10.1080/15623599.2018.1484864
Kaliba C, Muya M, and Mumba K (2009). Cost escalation and
schedule delays in road construction projects in Zambia.
International Journal of Project Management, 27(5): 522-531.
https://doi.org/10.1016/j.ijproman.2008.07.003
Lindhard SM, Neve H, Terje Kalsaas B, Møller DE, and Wandahl S
(2020). Ranking and comparing key factors causing time-
overruns in on-site construction. International Journal of
Construction Management: 1-7.
https://doi.org/10.1080/15623599.2020.1820659
Liu M and Ballard G (2008). Improving labor productivity through
production control. In the 11th Annual Conference of
International Group for Lean Construction, Production
Planning and Control, Blacksburg, USA: 657-666.
Mahamid I (2017a). Schedule delay in Saudi Arabia road
construction projects: Size, estimate, determinants and effects.
International Journal of Architecture, Engineering and
Construction, 6(3): 51-58.
https://doi.org/10.7492/IJAEC.2017.017
Mahamid I (2017b). Analysis of schedule deviations in road
construction projects and the effects of project physical
characteristics. Journal of Financial Management of Property
and Construction, 22(2): 192-210.
https://doi.org/10.1108/JFMPC-07-2016-0031
Mahamid I (2018). Study of relationship between cost overrun
and labour productivity in road construction projects.
International Journal of Productivity and Quality
Management, 24(2): 143-164.
https://doi.org/10.1504/IJPQM.2018.10012944
Mahamid I (2020). Study of relationship between rework and
labor productivity in building construction projects. Revista
de la Construcción, 19(1): 30-40.
https://doi.org/10.7764/rdlc.19.1.30-41
Mahamid I, Al-Ghonamy A, and Aichouni M (2013). Major factors
influencing employee productivity in the KSA public
construction projects. International Journal of Civil and
Environmental Engineering, 14(01): 16-20.
Mahamid I, Al-Ghonamy A, and Aichouni M (2015). Risk matrix for
delay causes in construction projects in Saudi Arabia.
Research Journal of Applied Sciences, Engineering and
Technology, 9(8): 665-670.
https://doi.org/10.19026/rjaset.9.1452
Mahamid I, Bruland A, and Dmaidi N (2012). Causes of delay in
road construction projects. Journal of Management in
Engineering, 28(3): 300-310.
https://doi.org/10.1061/(ASCE)ME.1943-5479.0000096
Montaser N, Mahdi I, Mahdi H, and Abdul Rashid I (2018). Factors
affecting construction labor productivity for construction of
pre-stressed concrete bridges. International Journal of
Construction Engineering and Management, 7(6): 193-206.
Nasirzadeh F, Rostamnezhad M, Carmichael DG, Khosravi A, and
Aisbett B (2020). Labour productivity in Australian building
construction projects: A roadmap for improvement.
International Journal of Construction Management: 1-10.
https://doi.org/10.1080/15623599.2020.1765286
Omoregie A and Radford D (2006). Infrastructure delays and cost
escalation: Causes and effects in Nigeria. In the 6th
International Postgraduate Research Conference, Delft
University of Technology and TNO, Amsterdam, Netherlands:
79-93.
Robles G, Stifi A, Ponz-Tienda JL, and Gentes S (2014). Labor
productivity in the construction industry-factors influencing
the Spanish construction labor productivity. International
Journal of Civil and Environmental Engineering, 8(10): 1061-
1070.
Sweis NJ, Sweis RJ, Kassab G, Elfar A, Athammneh D, and Sweis GJ
(2017). Demotivating factors influencing productivity in
Jordanian residential construction projects. International
Journal of Productivity and Quality Management, 20(2): 154-
168. https://doi.org/10.1504/IJPQM.2017.10002162
Zafar I, Wuni IY, Shen GQ, Ahmed S, and Yousaf T (2019). A fuzzy
synthetic evaluation analysis of time overrun risk factors in
highway projects of terrorism-affected countries: The case of
Pakistan. International Journal of Construction Management:
1-19. https://doi.org/10.1080/15623599.2019.1647634