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Identifying the performance areas
affecting the project performance
for Indian construction projects
Prachi Vinod Ingle and Gangadhar Mahesh
Department of Civil Engineering, National Institute of Technology Karnataka,
Surathkal, India, and
Deepak M.D.
School of Construction Management, National Institute of Construction
Management and Research –Pune, Pune, India
Abstract
Purpose –The construction industry is facing challenges because of performance shortfalls. Construction
projects are highly complex, distinctive, fragmented and do not have well-established performance
assessment models to evaluate their project success. The purpose of this paper is to assess the direction
through determination of performance areas that would affect project performance in Indian construction
projects.
Design/methodology/approach –A survey instrument was developed to gather data on the perception
of industry professionals on these identified areas. Purposive sampling method was used to select
respondents for the survey. These performance areas are ranked using relative importance index to ascertain
a level of importance among the group. Factor analysis (FA) was conducted to identify the significant
performance areas project performance. Further to identify the most influence performance areas on Indian
construction projects, multiple regression analysis was carried out.
Findings –Findings indicated 28 significant performance areas. This shows the low level of adoption of
good construction management practices in Indian construction projects. FA resulted in the areas being
grouped to nine broad significant performance areas with 59.49% of the total variance, namely, quality,
schedule, environment and stakeholder satisfactions, cost, productivity, safety, communication management,
customer relations and finance. Multiple regression analysis revealed two pivotal factors “customer relations”
and “schedule”that significantly influence project performance in Indian construction industry.
Originality/value –The outcome of the study will guide project stakeholders, who desire to improve
project performance on construction projects, to prioritize their efforts. It also highlights performance areas of
project management which required more focussed research in the context of Indian construction projects.
The findings can be extended to thedeveloping countries.
Keywords Project success, Project performance, Indian construction industry, Performance areas
Paper type Research paper
Introduction
Construction industry is a prime driver behind socio-economic growth of a nation. In India,
construction industry contribution to gross domestic production (GDP) was 8% in 2017
[India Brand Equity Foundation (IBEF), 2018]. In spite of proliferation, construction
industry faces with problems of cost overruns, disputes and delays. Although construction
industry of all countries faces several challenges and problems, the problems faced by
Disclosure statement: No potential conflict of interest was reported by the authors.
Indian
construction
projects
1
Received 24 January2020
Revised 24 March 2020
Accepted 14 April2020
Journal of Engineering, Design
and Technology
Vol. 19 No. 1, 2021
pp. 1-20
© Emerald Publishing Limited
1726-0531
DOI 10.1108/JEDT-01-2020-0027
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/1726-0531.htm
developing countries are quite different because of the global market conditions, limited
resources and lack of skilful team members, budget and tough competition for construction
business.
Construction industry is a project-based industry in which different stakeholders need to
work together to accomplish a project. The success or failure of construction projects
significantly impacts construction industry and other industries linked to it. Like any other
industry, the ultimate goal of all projects is achieving success. Achieving success is
becoming critical because of competitive and complex nature of construction industry.
Owing to substantial competition in this industry, it is necessary to give additional attention
to identifying performance areas that impact performance of projects.
Assessment of construction projects is fulfilling with three main areas consisting of time,
cost and quality (Bannerman, 2008). Every project is unique in its size, complexity,
functionality, scope, etc. and thus the perceptions of stakeholders involved in the project will
interpret project success in different aspects (Karlsen and Gottschalk, 2004). Moreover, the
perception of researchers has gained importance for performance measurement and has
extended focus beyond cost, time and quality which is generally regarded as the traditional
approach to assess project performance. Improving the practice at project level requires
identification of performance areas and suggesting improvement on concerned stakeholders.
Similarly, industry organizations should continually review and use performance areas to
improve their performance (Desalegn and Gangadhar, 2019;Mengistu and Mahesh, 2019).
There are many performance areas that affect the performance of Indian construction
projects. As identified, majority of the literature explains the context in developed countries
and very few studies have explained in the context of developing countriessuch as India.
The main objectives of this study were as follows:
(1) to identify significant performance areas contributing to project performance of
Indian construction industry; and
(2) to assess the effect of performance areas on project performance for construction
industry.
Literature review
Review of literature focussing on project performance can be broadly distinguished into two
sections. The first includes studies concerned about understanding how project success can
be perceived and assessed. The second section includes studies that identify performance
areas contributing to project success.
Project success for construction
Project success is important for the project management team and is an extensively
researched topic. Project success can be achieved through good performance in desired
performance areas. The project is considered successful if the project meets the project
specifications and stakeholder satisfaction (De Wit, 1986). Chan et al. (2002) stated that
construction project is considered successful when it is completed on time, within budget,
and as per acceptable quality irrespective of the complexity and environment within which
it is constructed. Bakert (1988) considered a project successful “if the project satisfies the
technical performance standards and if there is level of satisfaction among all key people in
parents’organization”with key people being major project stakeholders.
There are multiple definitions of the term “project success”that often changes from
project to project according to stakeholders involved, scope, project size, sophistication of
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2
the owner related to the design of facilities, technological implications and a variety of other
factors (Saqib et al., 2008). Yoke-Lian et al. (2012) remarked that the ability of the contractor
to select appropriate subcontractors during the process of bidding, as well as the ability to
suitably manage these subcontractors essentially results in a successful project.
Al-Momani (2000) classified project success into two important features:
service quality by contactors; and
owner’s expectations.
According to Cleland and King (1986), project is successful if it fulfils two criteria: project’s
technical performance objective with respect to time and budget, contribution that the
project made to the strategic mission. Moreover, Munns and Bjeirmi (1996) argued that
project success and project management are not certainly directly related. The objectives of
both project success and project management are different and the control of time, cost and
progress, which are often the project management objectives, should not be confused with
measuring project success. The role of project management is important for project success,
but it is affected by many other factors that are not in direct control of the project manager.
Meanwhile, Goatham (2016) stated that knowing the reasons for project failure is more
important than defining project success.
Defining project success is comparatively easy, but different people interpret project
success in different ways. Even though the definition of project success is different for each
stakeholder, it is based on the basic concept of overall achievement of project objectives and
expectations. According to Baccarini, (1999), project success consists of two components:
(1) project management success; and
(2) product success.
Project management success focuses on the project process and product success deals with
the effect of project’sfinal product. Project management success and product success are
different, e.g. a project has been managed efficiently, but eventually does not meet customer
or organizational expectation (Shrnhur et al.,1997). To properly assess project success,
performance areas should be identified. Existing studies related to performance
measurement focus on performance areas (also referred to as factors, attributes, variables,
metrics, key performance indicators and critical success factors) (Molenaar and Navarro,
2011;El Asmar et al., 2015;Tripathi and Jha, 2018). The criterion for measuring project
success varies depending on project stakeholders. It also depends on the size of the project
and technological tools. The project management team must define the criteria for
measuring project success at the beginning of the project. Thus, it becomes easy to
determine project success (Baccarini, 1999).
Project performance areas
Performance areas are indicators that determine the level of achievement in a project. A
performance area helps to measure the performance and compare it with project goals and
objectives. Several studies determined performance areas for measuring project success over
different performance dimensions such as cost, time, safety, etc. (Chan et al., 2002;Walker
and Shen, 2002;Hanna et al., 2014). Rockart (1982) was the first to use the term “critical
success factors”in the context of information systems and project management areas.
Critical success factors or performance areas are the factors that need to be monitored by
project management team in order to ensure project success. Table 1 summarised
performance areas suggested by different literatures.
Indian
construction
projects
3
Research methods
This section highlights the research methodology adopted in the study. The study focuses
on identifying and prioritizing performance areas suitable for Indian construction projects.
This involves an extensive literature review to be able to capture important performance
areas. Further, a structured questionnaire-based survey was conducted to elicit the opinion
Table 1.
List of performance
areas
Performance areas References
Cost
Cost estimation
Cost growth
Budget cost
Molenaar (1995),Pocock et al. (1996),Konchar and Sanvido (1998),
Atkinson (1999), Chan et al. (2004), Molenaar and Navarro, 2011,Kim
et al. (2012),PMI (2013),El Asmar et al. (2015)
Schedule
Construction speed
Delivery speed
Schedule growth
Molenaar (1995),Pocock et al. (1996),Konchar and Sanvido
(1998)Atkinson, (1999), Chan et al. (2004), Menches and Hanna (2006),
PMI (2013),El Asmar et al. (2015),Berssaneti and Carvalho (2015),
Meng (2012)
Quality
Systems
Punch-list items
Warranty Costs
Defect costs
Defect liability period.
Molenaar (1995),Atkinson (1999), Chan et al. (2004), Molenaar and
Navaro (2011), Marques et al. (2011),PMI (2013),El Asmar et al. (2015)
Safety
OSHA recordable
LTI
Fatalities
Chan et al. (2004), Menches and Hanna (2006), Molenaar and Navaro (2011),
Cheng et al. (2012),El Asmar et al. (2015)
Productivity
Labour factor
Equipment factor
Chan et al. (2004), Duy Nguyen et al. (2004), Menches and Hanna
(2006), Meng et al. (2012)
Finance
Profit
Walker and Shen (2002), Chan et al. (2004), Menches and Hanna, (2006),
El Asmar (2015)
Environment
Political
Economic
Technical
Social
Belassi and Tukel (1996),Chen and Paulraj (2004),Molenaar and
Navaro (2011),Fuertes et al. (2013),Goh and Rowlinson (2013),Shen
et al. (2010),Testa et al. (2011)
Communication and collaboration
RFIs
Resubmittals
Communication management plan
Impact of meetings
Pocock et al. (1996),Walker and Shen (2002), Chan et al. (2004),
Menches and Hanna (2006), Meng et al. (2011), PMI (2013),Arriagada
and Alarcon (2013),El Asmar et al. (2015)
Relations
Return business
Claims
Feedback
Col and Ries (2006), Belout (1998),El Asmar et al. (2015)
Stakeholder satisfaction
expectation and commitment
Munns and Bjeirmi (1996),Yang et al. (2011),Jepsen and Eskerod (2009),
Yang et al. (2011),PMI (2013),Missonier and Loufrani-Fedida (2014)
Others (related by project)
clear objectives and scope
contracting method
risk management
Walker and Shen (2002),Turner and Muller (2005),Liu et al. (2010),
Nevo and Chan (2007),PMI (2013),Abrantes and Figueiredo (2014),
Sousa et al. (2014),Zou et al. (2010)
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19,1
4
of construction professionals. These performance areas were then evaluated by relative
importance index (RII) and factor analysis (FA). Significant performance areas were
identified and were grouped through FA. Prior to analysing data, reliability of the
measurement scale of the questionnaire and the appropriateness of FA was carried out.
Finally, stepwise multiple regression analysis was conducted to determine the significant
variables among performance areas that influence the success of Indian construction
projects. Figure 1 summarizes the research design for the current study as a detailed
methodology flowchart.
Identification of performance areas affecting project performance
Based on extensive literature review, a list of 37 performance areas was identified and
verified by construction professionals operating in Indian construction industry.
Considering the suggestions provided by these professionals, necessary modifications have
been made to the list of performance areas. A structured questionnaire was prepared.
Questionnaire survey design
Questionnaire survey approach is preferred to obtain reliable data and facilitate generalized
findings and is an effective instrument on approaches towards interrelationships between
variables (Alashwal et al.,2017;Deepak et al.,2019). The survey questionnaire consists of
two sections. First section includes the demographic information of the respondents,
including respondent’s experience, designation, etc. The second section consists of
performance areas, for which the respondents were asked to rate these areas based on the
level of importance with respect to success of a project. A five-point Likert scale was used
which represents (1) strongly disagree to (5) strongly agree (Table 2).
A pilot study was used to determine reliability, validity and effectiveness of the
questionnaire. A total of 5 experts participated in the pilot study who possess an experience
of more than 20 years in construction industry. Thorough discussions were done with these
experts to check for clarity and comprehensiveness of the proposed performance areas that
measure performance of the project. The questionnaire was then examined for content
validity. This indicates the description and measurement capability of the questionnaire. In
this regard, some of the statements was reframed to remove certain ambiguities of the
survey instrument. In this study, a Web-based survey was used to reach maximum
Figure 1.
Flow chart of
research
methodology
Literature review
Identifying project performance areas
Content validity check Expert review
Data collection method Questionnaire survey
Data analysis
Reliability test
Common method variance
RII analysis
Exploratory factor analysis
Regression analysis
Findings, Implications & Conclusions
n
Indian
construction
projects
5
respondents and to achieve a higher response rate. The questionnaire was thus refined and
was circulated for main study data collection.
Sampling technique and sample size for the study
This study targeted different stakeholders working in different projects of Indian construction
industry. This database includes a list of 353 experts who have been handling different
construction projects such as residential, commercial and infrastructures were invited to
participate in the survey. The study used a purposive sample, for collecting survey responses
from targeted population in Indian construction industry. The respondents were selected such
that they should possess relevant working experience of at least 3 years in construction
projects. The sampling frame considered for the study includes stakeholders such as project
managers, senior project managers, project executives, quality engineers, safety engineers,
designers, consultancies, client, academicians, etc. The unit of analysis are construction
professionals and practitioners in Indian construction projects. The formula that is used to
estimate the minimum sample size is given in equation (1) (Oyewobi et al., 2015):
N¼Z2pq
ðÞ
e2(1)
where: Z = 1.96 at 5% level of significance, the p= estimated proportion of an attribute that
is present in the population (p= 0.5), qis 1 pand e= acceptable margin of error for
proportion being estimated (8%):
N¼1:962x0:510:5
ðÞ
0:082¼149:656 150
The required sample size calculated using the above formula is 150. Generally in
construction industry, the response rate for questionnaire-based survey is as low as
20%-30% (Oyewobi et al.,2015).
Table 2.
Sample of
questionnaire
Please tick mark (_) the applicable cellto rate the following performance areas based on five-pointscale from
strongly disagree 1 to strongly agree 5) with respect to the degree of their impact on the project success in
construction projects.
Sr. no Performance areas
Scale
(1)
strongly
disagree
(2)
less
disagree
(3)
moderately
disagree
(4)
highly
disagree
(5)
strongly
agree
1 Cost
2. Schedule
3. Quality
4. Safety
5. Productivity
6. Finance
7. Environment
8. Communication and collaboration/
Modifications
9. Relations
10. Stakeholder satisfaction
11. Other related to Project
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19,1
6
Analysis methods
The analysis methods focus on identifying the significant impact of project performance on
performance areas in construction projects. These established performance areas are ranked
using RII to determine the level of importance among its group. Multiple regression analysis
is used to define and establish the relationship between dependent and independent
variables. FA was carried to understand the relationship among the variables. Statistical
analysis is carried out with SPSS version 21 software.
Relative importance index analysis
RII analysis is a technique used for ranking the performance areas from the survey given by
various respondents. RII is calculated as shown in equation (2):
RII ¼Xn
n¼i
WiXi
AN (2)
where:
W = weight assigned by respondents;
X = frequency of each weight;
A = highest weight; and
N = number of respondents.
The range of RII value is from 0 to 1, and an element with higher RII value is considered
more important than others (Deepak et al.,2019).
Multiple linear regression analysis
Multiple linear regression (MLR) analysis is a technique for examining the relationship
between a dependent variable with two or more independent variables (Hair et al.,2006).
MLR was used to predict each performance area to project performance. This analysis is
used to define the relationship of each dependent factor of project performance to that of
each independent factor of performance areas.
Factor analysis
FA is a statistical method to understand the interrelationship among variables (Hair et al.,
2010) . It can be used to reduce a larger number of variables to a smaller number of latent
factors. This technique was used to identify the underlying cluster of factors that affect
project performance. Principal components analysis (PCA) with varimax rotation was used
to identify the underlying factors, which is a useful tool for determining the interdependence
of variables (Field, 2009).
Results and discussions
Demographic profile of respondents
Respondents were selected from a wide range of construction professionals in the Indian
construction projects. A total of 353 respondents involved in construction projects in Pune
region (Maharashtra, India) was contacted to participate in the survey. The responses were
collected from different types of projects. Survey was conducted from November 2017 to
March 2018. In return, 193 responses were received, resulting in a response rate of 54%,
which is considered acceptable for a survey-based study in construction industry (Oyewobi
et al.,2015). The responses obtained from the survey are discussed below:
Indian
construction
projects
7
Types of stakeholders. The respondents were of different stakeholders. Among them, 45
respondents (23%) were contractors, 39 were clients (20%), 45 were designers (23%), 26
were consultants (14%) and38 were academicians (20%), as shown in Figure 2.
Experience of the respondents. Based on the responses, the respondents were having
good experience in handling different types of projects in India. More than 61% of the
respondents had experience of more than 10years which reflects a high level of impact on
responses for this study (Table 3). Therefore, the results of the survey are adequate to
identify the influence of performance areas on Indian construction projects.
Respondents designations. When the respondent’s designation is considered, highest
contribution was from assistant managers (23%), followed by project consultants (20%) (Figure 3).
Reliability analysis
Cronbach’s alpha test was conducted to test the reliability and suitability of the measuring
scale. (Fellows and Liu, 2008). This method evaluates core consistency depending on
average correlations among the data that is identically computed. The reliability of the
factors can be calculated as shown in equation (3):
a
¼n
n11R
s
2
i
s
2
i
! (3)
where, n = number of items,
s
2
i= variances of sum of all scores, R
s
2
i= variance of sum of
all standard deviations of all the items.
The analysis was carried out in SPSS software version 21. Reliability analysis provides
an assessment of the degree of consistency between multiple measures of a variable. The
acceptable range for Cronbach’s alpha value should be greater than or equal to 0.7. Test
result shows that Cronbach’s alpha score is 0.775, indicating a good internal reliability (Hair
et al.,2006) for all thirty-seven performance areas. All performance areas identified in this
study are considered reliable and are utilized for further analysis.
Relative importance index
RII values for each of performance area is calculated using equation (2) as shown in previous
section. Based on the responses from the survey conducted, the factors having RII more than
0.7 were considered for further analysis. In this regard, 28 factors are considered and as
shown in Table 4.
Figure 2.
Percentage of
respondents for
construction projects
23%
20%
23%
14%
20%
Contractor
Client
Design
Consultant
Academician
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8
Common method variance
There is a high chance of common method bias in case of self-reported data from multiple
sources. In this regard, Common Method Variance test was carried out to mitigate the risk of
the common method bias in the sample. Harman’s single factor test was conducted by
entering all the measurement variables into a single factor in FA. If the extracted variance is
less than 50%, the method is considered acceptable (Podsakoff, 2013). There is high
probability of common method bias because of self-reported data from multiple sources.
Results indicate that the factor variance extracted is 21%, which is below 50% and,
therefore, there is no significant problem in the data. Table 5 shows the detailed results of
common method variance test.
Exploratory factor analysis
PCA is a method of FA, which aims to identify factors from a set of intercorrelated variables
(Hair et al.,2006). Rotated component matrix can be used to enhance the result of PCA and
explore the best pattern of loadings. Appropriateness of data was ensured through FA by
Bartlett’s test of sphericity and Kaiser–Meyer–Olkin (KMO) values. KMO test checks the
sampling adequacy and Bartlett’s test of sphericity signify whether the correlation matrix is
an identity matrix. These tests are conducted to check the statistical requirements of FA. In
this study, the KMO-value was equal to 0.69, which is well above the acceptable threshold,
indicating that the data was appropriate for FA. Bartlett’s test of sphericity showed that the
approximate chi-square value was 1077.769 and the associated significance level was 0.000,
suggesting that the sample correlation matrix is not an identity matrix. Therefore, it was
considered appropriate for further analysis. Exploratory FA was performed to determine the
resultant factors and results of the analysis are shown in Table 6. Rotation approach carried
out was varimax rotation. FA resulted in nine groups with an eigenvalue greater than one
was extracted and accounted for 59.49% of the total variance. Communalities of all variables
were above 0.50.
Table 3.
Experience of the
respondents
Experience (in years) Years (%)
1-10 61
11-20 22
21-25 9
26 and above 8
Figure 3.
Respondents’
designation
14%
23%
20%
20%
23% Project Manager
Assitant Manager
Project Consultant
Engineer
Others
Indian
construction
projects
9
From the table, factor loadings were above 0.5 for all extracted variables. Detailed
discussion about the extracted group is presented below.
Group 1: quality. The first extracted component consists of performance areas related to
quality area. This component can be called “Quality”and it explains about 9% of the total
variance of performance area as shown in Table 4. Variance depends on the following
factors: defect liability period (DLP), item beyond scope (IBS), defect cost (DC), frequency of
meeting (FOM) and project quality (PQ).
The importance of quality area is essential, and all project stakeholders should have a
clear understanding of measuring quality. The defects in construction will lead to
reconstruction of work which will consume money and time and hence impacts project
completion duration (Love, 2002). Thus, poor quality leads to failure of the project and
resulting in rework. Rework can impact the project negatively not only financially but also
in terms of time. For defects to be least considering in DLP, the work done should be of the
desired quality (Hwang et al., 2009). Adopting project quality control and quality assurance
programmes will reduce the cost for project failure (Hasan and Jha, 2013). Project is
considered successful if no additional cost other than maintenance cost occurs during the
DLP. FOM can help the stakeholders to share the information, discuss problems and
solutions to the team and keeps track records of project activities.
Group 2: schedule. The second extracted group accounts for 8.14% of the total variance
and has three factors as shown in Table 6. Factors that include under schedule areas are
schedule payment (SP), schedule growth (SG) and construction speed (CS).
Table 4.
Relative importance
indices for
performance areas
impacting project
performance
Sr no. Coding Performance areas RII Rank
1 RB Return business 0.84 1
2 DC Disputes claims 0.74 20
3 F Feedback policy 0.79 9
4 OS Osha recordable 0.78 13
5 LTI Loss time injuries 0.72 24
6 Fa Fatalities 0.70 27
7 CS Construction speed 0.78 14
8 SP Schedule payment 0.79 10
9 SC Schedule growth 0.79 11
10 CUC Construction unit cost 0.78 15
11 CG Cost growth 0.78 16
12 RC Rework cost 0.73 21
13 PQ Project quality 0.79 12
14 DLP Defect liability period 0.71 26
15 IBS Item beyond scope 0.72 22
16 DC Defect cost 0.70 28
17 RFI Request for Information 0.72 23
18 CMP Communication management plan 0.78 17
19 FOM Frequency of Meeting 0.71 25
20 IOM Impact of Meeting 0.81 6
21 P Profit 0.82 3
22 EP Equipment productivity 0.84 2
23 LP Labour productivity 0.82 4
24 EL Expectation level 0.81 7
25 S Social environment 0.81 8
26 T Technical environment 0.77 18
27 P Political environment 0.81 5
28 E Economic environment 0.74 19
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10
The basic criterion for project success is the completion of project within the estimated duration
of the project. Hence, project management teams should focus on project activities and
determine critical activities and achieve accurate milestones (Demirkesen and Ozorhon, 2017).
Thus, construction professionals should monitor project through all stages of construction.
Group 3: environment and stakeholder satisfaction. Group 3, accounts for 6.95% of total
variance and has five factors as shown in Table 6. The factors that include under
environment and stakeholder areas are as follows: social (S), technical (T), political (P),
economical (E) and expectation level (EL).
The changes in the environment during the life of project will influence decisions.
Environment analysis should be carried out at the early stages of a project for identification
Table 5.
Common Method
Variance Test Result
Component
Initial eigenvalues Extraction sums of squared loadings
Total % of Variance Cumulative (%) Total % of Variance Cumulative (%)
1 8.280 21.788 21.788 8.280 21.788 21.788
2 4.230 11.132 32.921
3 2.533 6.666 39.587
4 1.616 4.252 43.838
5 1.588 4.179 48.017
6 1.502 3.952 51.970
7 1.389 3.656 55.626
8 1.147 3.018 58.644
9 1.093 2.877 61.521
10 1.047 2.756 64.277
11 1.013 2.666 66.944
12 0.989 2.604 69.547
13 0.891 2.346 71.893
14 0.863 2.270 74.163
15 0.805 2.118 76.281
16 0.753 1.983 78.264
17 0.719 1.892 80.156
18 0.699 1.839 81.995
19 0.646 1.700 83.696
20 0.640 1.685 85.381
21 0.597 1.570 86.951
22 0.514 1.352 88.303
23 0.477 1.255 89.559
24 0.441 1.162 90.721
25 0.409 1.075 91.796
26 0.389 1.023 92.819
27 0.358 0.941 93.759
28 0.322 0.847 94.606
29 0.320 0.842 95.449
30 0.290 0.763 96.211
31 0.266 0.701 96.912
32 0.254 0.669 97.582
33 0.238 0.627 98.209
34 0.186 0.490 98.699
35 0.145 0.382 99.081
36 0.141 0.370 99.451
37 0.116 0.306 99.757
38 0.092 0.243 100.000
Note: Extraction method: principal component analysis
Indian
construction
projects
11
of risks which affects the completion of project. The pre-planning stages of construction are
dependent on project environment. Economical aspects will impact the project on the type of
materials to be used in the projects (Lam et al., 2007). Technical aspects will impact how fast
the project can be constructed Akinsol et al. (1997). The last factor is the expectation level of
customer. The project is considered successful if it meets its expectations of stakeholders.
Project participants are considered as the key elements for project success (Leon et al.,2017).
All the factors have an impact on project performance.
Group 4: cost. Group 4, accounts for 6.69% of total variance and has two factors as
shown in Table 6. It consists of two factors: construction unit cost (CUC) and construction
cost growth (CG). The project is considered successful in how well the project cost has been
managed in the project. Project management can directly influence the project objectives
particular its cost as all departments are directly controlled by the management team
therefore it can have both adverse and positive effects on the construction projects.
Therefore, regular meetings need to be conducted to discuss different ways to control costs.
Group 5: productivity. Group 5, accounts for 6.53% of total variance and has two factors
as shown in Table 6. It consists of two factors: labour productivity (LP) and equipment
productivity (EP). The modern techniques and tools should be used to control and monitor
the resources. The resources should be managed as per availability, priority and as per
budget of the project. The project managers should improve the labour skills through
Table 6.
Factor analysis
results
Factor Eigen value Variance (%) Variables
Factor
loading Communality
Quality 4.20 8.959 Defect liability period 0.68 0.62
Item beyond scope 0.76 0.68
Defect cost 0.81 0.72
Frequency of meeting 0.63 0.62
Project quality 0.52 0.57
Schedule 2.53 8.14 Schedule payment 0.77 0.67
Schedule growth 0.76 0.67
Construction speed 0.56 0.55
Environment and
stakeholder
satisfaction
1.68 6.95 Social impact 0.54 0.54
Technical impact 0.70 0.66
Political impact 0.52 0.54
Economic impact 0.68 0.65
Exception level 0.51 0.52
Cost 1.59 6.69 Construction unit cost 0.60 0.59
Construction cost growth 0.71 0.69
Productivity 1.47 6.53 Labor productivity 0.68 0.62
Equipment productivity 0.75 0.68
Safety 1.37 6.33 Loss of time injuries 0.68 0.65
Fatalities 0.75 0.69
Communication
management
1.11 5.65 Disputes claims 0.68 0.65
Communication management
plan
0.75 0.72
Customer
relation
1.06 5.12 Return business 0.76 0.68
Feedback policy 0.53 0.51
Finance 1.01 5.13 OSHA 0.50 0.52
Profit 0.69 0.59
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12
appropriate training programme. Suitable vendor selection, monitoring inventory and
regular maintenance of equipment’s are some of practices to improve productivity.
Improving productivity is important because proper management of resources in
construction projects will help to save time and cost.
Group 6: safety. Group 6, accounts for 6.33% of total variance and has two factors as
shown in Table 6. It consists of two factors: fatalities (F) and loss of time injuries (LTI).
Construction safety is of paramount importance in construction projects. Major accidents
caused on site can lead to significant delay of project can even shut down of project. Thus,
safety practices must be encouraged for workers to minimise (LTI) of construction projects.
Safety should be considered as a part of project from beginning Site safety should include
training, supervision and leadership and not just compliance with processes and policies.
Therefore, safety has significant impact on project performance.
Group 7: Communication management. Group 7, accounts for 5.65% of total variance
and has two factors as shown in Table 6. It consists of two factors: disputes claim (DC) and
communication management plan (CMP). Dispute claims consume a lot of time and cost and
are essential for successful completion of project which leads to enhance project
performance (El Asmar et al., 2015). The top management must devise suitable means to
avoid disputes among stakeholders. Another factor was communication management plan.
A project requires proper coordination among all the project stakeholders and allows
understanding the requirement and issues of stakeholders. Communication and
coordination arising among stakeholders are key for managing crisis and for achieving
project success. Improved communication plan leads to higher chance of project success
(Chang and Shen, 2009).
Group 8: customer relation. The second last group accounts for 5.12% of total variance
and has two factors as shown in Table 6. It consists of two factors: return business (RB) and
feedback policy (FP). Project stakeholders are considered as key elements for a successful
project. The success of project is also based on trust and understanding between
stakeholders. Customers are stakeholders in project who are the potential users of facilities.
The customer relations, when managed successfully will result in stakeholder satisfaction
and repeated business (Shahbaz et al., 2018). Literature on construction projects success has
identified these factors as a vital factor responsible for project success.
Group 9: finance. The last group extracted 5.13% of total variance. It consists of two
factors: OSHA (OS) and Profit (P). In a construction project, cash flow is the most important
factor.
To mitigate financial viability risk, proper attention needs to be given for budget
requirements and preparation of budget and monitoring cash flows (Demirkesen and
Ozorhon, 2017). The issues may be avoided by arranging reliable source of funds and
choosing truthful stakeholders.
Regression analysis results
A regression model can relate a number of independent variables to a dependent variable
and can summarize the relationships among variables (Chan et al., 2005). Multiple regression
analysis was carried out to study the relationship between project success (dependent
variables) and performance areas (independent variables). A stepwise variable selection was
adopted as it is the most recommended method to identify performance areas (George and
Mallery, 2006). The stepwise method was criteria selected the pvalue= 0.05 for a variable to
enter the regression equation and p-value = 0.10 to remove an entered the variable. Finally,
the model gives an equation that contains a constant and partial regression coefficient for
each of the performance areas. A total of 9 performance areas extracted by FA from the 28
Indian
construction
projects
13
variables were used as independent variables in evaluating the relationship with perceived
project performance.
Regression models take the form of the following equation (4):
Y¼B0þB1X1þB2X2þB3X3þ...:BNXN(4)
where, Y is the dependent variable, X
1
;X
2
;...;X
n
are the known independent variables
b
0
;
b
1
;
b
n
are the partial regression coefficients. Table 7 shows B values,
b
, adjusted R
2
,
t-values and significance values. Quality (Factor 1), environment and stakeholder
satisfaction (Factor 3), cost (Factor 4), productivity (Factor 5), safety (Factor 6),
communication management plan (Factor 7) and finance (Factor 9) were excepted from the
regression model because they failed the entrance criteria of stepwise variable selection as
described earlier.
Results indicate that, “customer relation”(Factor 8) and “schedule”(Factor 2) will result
in having a significant influence on project performance at p<0.05. For the success of a
project, all the stakeholders should understand the scope and milestones of the project,
coordination and discussion of issues with all stakeholders of the project. Hence the MLR
equation for safety performance is:
Project performance ¼3:80 þ0:14 F8
ðÞ
þ0:13 F2
ðÞ (5)
Equation (5) gives relationship between perceived project performance and significant
performance areas. The
b
value indicates the relative impact of the entered variables, thus
customer relation (Factor 8) has more impact on project performance (
b
= 0.14) followed by
schedule (Factor 2) with
b
= 0.13. R
2
change value of 0.26 indicates that 26% of the variance
in project performance is explained by Factor 8. The adjusted R
2
value of the model is 21%.
Discussion
Most of the performance areas are specific to some context and specific to countries. Hence
there is a need for identifying performance areas for Indian construction projects. Thus, the
performance areas preferred can be used as a practice to identify construction project
success. It is very difficult to choose the performance areas from thewide range of industries
ensured that the performance areas have wide range of applicability. Thus, FA results of the
survey helped to identify the most relevant performance areas for Indian construction
projects. The performance areas identified in the paper will highlight the areas that
construction projects need improvements in their performance. The integration of these will
lead to improve overall performance.
The multiple regression analysis determines the two most influence performance areas
on project success i.e. “customer relation”(Factor 8) and “schedule”(Factor 2). Customer
relation and schedule are the potential performance areas for assessing project performance
Table 7.
Regression analysis
results
Independent variables B
sb
t-values p-values
Dependent variable: project performance; R
2
= 0.26, Adjusted R
2
= 0.21
Constant 3.80 0.08 NA 61.13 0.00
Factor 8: Customer relation 0.14 0.08 0.15 2.29 0.05
Factor 2:
Schedule
0.13 0.08 0.15 2.21 0.04
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and is widely accepted in many studies (Col and Ries, 2006; Belout, 1998; Menches and
Hanna, 2006; PMI, 2013;El Asmar et al., 2015;Berssaneti and Carvalho, 2015;Meng, 2012).
Customer relation is aimed at long term relationships with customers. The role of customer
relation is throughout the life cycle of a project. Customers are also stakeholders and hence
customer relationships should be improved. Moreover, all stakeholders have a strong
interest in the performance of project. Customer relationships can be done by quick response
to the changing requirement of customers and address customer’s issues which will lead to
customer’s satisfaction. A good customer relationship practice can be done through
feedback, predicting key factors impacting customer relationships, interacting with
customers, updating about work progress and issues, suggesting solution for issues and
satisfying expectations of the client. Good relationships among stakeholders are necessary
for steady process in construction projects. To have a well-defined relationship among the
parties, all related parties should be involved from the initial stage of the project. Any
project is successful only if the end customer is happy and accepts the project. It is evident
from the discussion that customer relation to project performance and will enhance project
performance in a positive direction.
In today’s highly competitive environment, managing schedule of the project is very
important. A project manager possesses the capability to ensure that the project is
completed within the budget and on schedule. To ensure that timely decisions, clear project
scope, regular monitoring of schedules, conducting meetings, discussion of issues arising
during construction activities, smooth cash flow, coordinating among parties, management
of site are few recommendations to control schedule performance of projects. Experience of
contractor, construction methods and speed of decision making of owners also impact
schedule performance of project (Hwang et al.,2013).
Research implications
The finding of this study will facilitate construction professionals during different phases of
construction to manage their projects activities and tasks efficiently and shall improve the
performance of projects. In the construction industry, developing effective project
performance needs; first to identify performance areas that are responsible for project
success; assessing those performance areas and lastly devising a mechanism to monitor and
control the project performance. Results of the analysis show the importance of different
performance areas for development of project performance as perceived by the respondents.
The identified performance areas can help project management team to better coordinate
projects by analysing the importance of performance areas. This will improvise the project
to perform better throughout the project life cycle. This will also help project manager’s
experience to improve performance and will be able to gain trust for future projects. Low
performing areas can be improved by adopting strategies for improving performance. The
findings identified can be used for their local or global construction projects.
The ultimate aim of the study is to understand and evaluate the casual relationship
between performance areas and project performance in construction industry. This will
benefit organizations in multiple ways. It helps in improving productivity of workers, to set
targets, timely monitoring and evaluation of project performance which is measured by
developing project performance areas. For measuring project performance effectively, there
is a need to measure those performance areas as it helps to evaluate project performance in
the organization. If the organisation does not have an effective measure to evaluate project
performance, then it is desired to develop and implement the model as it will assist project
management practitioners to monitor the project success in the Indian construction
industry.
Indian
construction
projects
15
Limitation and future scope of study
As with any other opinion-based study, the present study also has some limitations. The
data was collected from professionals of Indian construction project and therefore, it reflects
their experiences and opinions. Moreover, the study was carried out only in the Indian
context. Thus, the findings of this study may not be pertinent to developing countries. The
factors considered in this study can be further tested through conducting case studies for
checking the effectiveness in implementation in construction projects. The study can further
be extended by developing a framework model by incorporating all performance areas for
Indian construction projects. In addition, to this, a large number of companies would be
required to generalize the study results.
Conclusions
There is a need for more awareness to be created about the performance areas among
construction professionals. The study of performance areas is necessary as it majorly
focuses on improving construction project performance. Hence, this study focuses on
identifying the significant performance areas for Indian construction projects. A
questionnaire survey was used to understand the level of impact of performance areas on
project performance. The impact of performance areas on project performance was evident
from the findings of this study. The developed questionnaire can be used to assess
construction projects in India as well as developing countries.
Based on the result of FA, the study identified nine performance areas such as quality,
schedule, environment and stakeholder satisfaction, cost, productivity, safety,
communication management plan, customer relation and finance. The study has proposed
performance areas for Indian construction projects. Findings of the study will help the
project stakeholders to prioritize their efforts towards achieving excellence in project
performance. Finding from the study are expected to help construction professionals to
focus on performance areas in order to achieve optimum results for that particular
performance areas.
Furthermore, multiple regression analysis revealed that “customer relation”and
“schedule”are performance areas affecting Indian construction projects. The project
management team should prioritise the critical activities, approximate duration of activities
and appropriate determination of milestones to avoid delays in schedule and cost overruns.
Performance area pertaining to customer relations can be enhanced by maintaining
adequate relationships and addressing issues with regular communication among project
stakeholders. This thereby develops trust and leads to maintain good relationship among
project stakeholders. Further research can be made on establishing benchmarking
standards using these performance areas developed in this study to Indian construction
projects.
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Corresponding author
Prachi Vinod Ingle can be contacted at: prachi03ingle@gmail.com
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