1. Introduction
Generally, corruption has various definitions, depending on the context and scope.
One of the most common is defined by the World Bank as: “offering, giving, receiving,
or soliciting, directly or indirectly, anything of value to influence improperly the
actions of another party.” Corruption also occurs in the private sector and principal
when an agent betrays the principal’s interest in pursuit of one’s own (Klitgaard,
1988).
However, globally, construction is distinguished as a sector associated with corruption
(International, 2002; Kwan and Ofori, 2001; Wong et al., 2000; Zarkada-Fraser and
Skitmore, 2000). According to Transparency International (2010, 2002), due to the
rapid growth of construction business during these decades, recently it has been revealed
that the construction industry has become the most corrupt industry. Annually, $340
billion US dollars was estimated as being lost due to the corruption in the global
construction sector (Sohail and Cavill, 2008).
According to Sierra (2000) corruption is one of the main principal issues preventing
economic and social development. It exists in both developed and developing countries
and its occurrence is dependent on economic growth (Ehrlich and Lui, 1999). Inevitably,
Iran, as a developing country is not an exception and numerous construction projects
suffer from this issue in bidding, tendering procedure, contracts etc. Therefore,
due to the importance of this issue, this study aimed to identify the root causes
of corruption and highlight them for construction projects authorities. Hence, this
study’s objective is firstly, identifying the causes of corruption in construction
projects, and secondly, to evaluate the most significant factors causing corruption
in construction projects in Iran. To this aim, an intensive literature review has
been performed which will be discussed in the following section. The methodology of
this research and the procedures is explained in the third section. Data analysis
and findings, and conclusion will be in the fourth and fifth sections respectively.
2. Main Discussion
2.1 Literature Review
An intensive literature review has been done in order to discover different forms
of corruption as well as identifying factors contributing to corruption in construction
projects. Twelve different forms of corruption, occurred in the construction industry,
identified from the previous studies in developed countries. Those twelve forms of
corruption in construction are namely; bribery, fraud, collusion, bid rigging, embezzlement,
kickback, conflict of interest, dishonesty and unfair conduct, extortion, negligence,
front companies, and nepotism which are described as below:
1.Bribery: is defined as “offering, giving, receiving, or soliciting of anything of
value to influence the action of an official in the procurement or selection process
or in contract execution” (Hartley, 2009).
2.Fraud: occurs in the forms of misinformation, deceit, and theft (Bowen et al., 2007;
De Jong et al., 2009; Sohail and Cavill, 2008; Tabish and Jha, 2011; Van den Heuvel,
2005; Vee and Skitmore, 2003).
3.Collusion: when a secret agreement is made between two or more parties for a fraudulent
or deceitful purpose (Besfamille, 2004; Brockmann, 2009; Cheung et al., 2012; Chotibhongs
and Arditi, 2012; De Jong et al., 2009; Sichombo et al., 2009; Tabish and Jha, 2011;
Van den Heuvel, 2005).
4.Bid rigging: when a tenderee intentionally lets the tenderer win the contract (Bowen
et al., 2012; De Jong et al., 2009; Hartley, 2009; Krishnan, 2009; Sichombo et al.,
2009; Vee and Skitmore, 2003).
5.Embezzlement: when a person intentionally misuses their power to acquire unlawful
personal benefits (De Jong et al., 2009; Green, 1993; Hartley, 2009; Stansbury, 2009).
6.Kickback: when a person looks for a favorable decision from a client’s staff, in
terms of unlawful economic incentives (Barco, 1994; Bowen et al., 2012; De Jong et
al., 2009; Sohail and Cavill, 2008).
7.Conflict of Interest: when experts cannot fairly accomplish their duties due to
personal interests or contradictory proficiency (Bowen et al., 2007; Bowen et al.,
2007; De Jong et al., 2009; Hartley, 2009).
8.Dishonesty and Unfair Conduct: typically it arises in the bidding, contract negotiation
and signing, and project construction phases (Alutu, 2007; Vee and Skitmore, 2003).
9.Extortion: it’s an incentive for higher revenue, taken from lower project positions;
for instance from a major contractor to the subcontractors (Bowen et al., 2012; Cavill,
2006; Sichombo et al., 2009; Stansbury, 2009; Tabish and Jha, 2011).
10.Negligence: Vee and Skitmore (2003) identified some common form of negligence in
construction as: insufficient project management skills, weak supervision, poor safety,
low quality materials, insufficient quality requirements, and poor performance.
11.Front Companies: when senior positions in government establish corporate entities
to get unlawful personal benefits during the awarding of construction contracts (Vee
and Skitmore, 2003).
12.Nepotism: also called the “good old boys’ network” (Singh and Shoura, 1999), is
an assistantship with a tenderer who has a common race, origin or friendship (Bowen
et al., 2007; Hartley, 2009; Kadembo, 2009; Ling and Tran, 2012).
Although extensive studies have been conducted in developing countries, it has been
revealed through the literature review that just a few research studies have been
performed in developing countries, such as India, South Africa, Nigeria, and Pakistan.
In India, Tabish and Jha (2011) evaluated the irregularities in public procurement.
They classified the irregularities into five categories as follows: transparency,
professional standards, fairness, contract monitoring and regulation and procedural
irregularities. Among these categories, transparency was ranked as the key factor.
In South Africa, Bowen et al. (2012) identified that the factors facilitating corruption
in the South African construction industry are “Shortage of skills and ineffective
processes”, “Public officials as role models”, “Absence of deterrents and sanctions”,
“Poor standards of ethics.” Bowen et al. (2007), discovered that collusion, bribery,
negligence, fraud, dishonesty, and unfair practices are the verities of unethical
behaviors encountered in South African construction projects. In addition, Bowen et
al. (2007) indicated that the breaches in professional responsibilities include “conflicts
of interest” and “the divulging of confidential and proprietary information to a third
party”. In Nigeria, Alutu and Udhawuve (2009) identified the various factors causing
unethical practices in Nigerian engineering industries. Among those factors, the highest
ranked factors were: “people want to acquire wealth by all means to enhance public
status” and “people are driven by their inherent greed for money.” Moreover, the two
most prevalent unethical practices as perceived from the engineers’ viewpoint are
“contractors get vital information on the contract by paying agreed sums of money
to officers of the awarding organizations” and “contractors must include ‘kickbacks’
in their tender or else they will not win the contracts” (Alutu, 2007). Corruption
was revealed as one of the most important project risk factors in the construction
industry in Pakistan (Choudhry and Iqbal, 2012).
Basically, corruption has different aspects such as social, economical, political,
government, human resources, clients, management and organizational (Mousavi and Pourkiani,
2013). However, the studies regarding corruption in construction projects in developing
countries are limited and ought to have more scrutiny on this topic.
Fig. 1.
Research Procedure Framework
2.2 Research Methodology
The aim of this study is to evaluate the most significant factors causing corruption
in construction projects in Iran. Therefore, an intensive literature review has been
conducted to discover various forms of corruption and the potential factors which
encourage corruption in the construction industry. An initial questionnaire was designed
by factors extracted from the previous studies. Through the pilot study, Twelve experts,
in the Iranian construction industry, were interviewed and asked to evaluate and revise
the questionnaire as to whether it was qualified and applicable or not. The experts
added some other affecting factors and omitted irrelevant factors from the questionnaire
list. Consequently, the ultimate questionnaire included 77 factors (coded as FCC)
and was distributed among the participants in Iran. The participants were asked to
evaluate the importance of factors based on the five point Likert scale. Out of 220
distributed questionnaires, 188 were returned by the participants. The valid collected
data sets were analyzed and the mean index for each factor calculated. The factors
with less than 3.5 mean score were eliminated from the data set. Consequently, Exploratory
Factor Analysis (EFA) was applied to analyze with 36 factors to uncover the underlying
structure of variables. The research procedures framework is shown in Fig. 1 below.
2.3 Data Analysis and Findings
In order to check the reliability of the questionnaire, Cronbach's Alpha measured
and discovered that =0.734 (Table 1). According to Field (2009), for the amount of between 0.7 ≤ < 0.8 the reliability is “Acceptable”.
According to Majid and McCaffer (1997) the factors with less than 3.5 score average
mean index should be removed from the potential factors list, based on the appropriate
classification of rating, shown on the Table 2. Hence, the factors less than 3.5 omitted
and then data analyses proceed with 36 factors (Table 3). The average index (Mean
Index) is calculated based on equation as follow:
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Table 1. Reliability Statistics
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Table 2. Appropriate Classification of Rating
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Table 3. Potential Factors Causing Corruption with Mean Scores in Descending Order
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Table 3. Potential Factors Causing Corruption with Mean Scores in Descending Order(Continue)
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(1)
Where, = constant expressing the weight given to i
= the frequency of response for i=1,2,3
Before applying the factor analysis, initially KMO and Bartlett's Test should be checked
as to whether factor analysis is applicable or not. The KMO measure must be equal
or higher than 0.6, and the Significance measure must be equal or less than 0.05 in
the Bartlett’s test. According to the Table 4, KMO was 0.818 and Significance for
the Bartlett’s test was 0.00 therefore they’re qualified and factor analysis was applicable.
Exploratory Factor Analysis (EFA) was applied to uncover underlying relationships
between measured variables. Therefore, the Principal Component’s method with the Varimax
rotation applied. From the EFA outcomes, the Total Variance Explained and the Rotated
Component Matrix are shown in the Tables 5 and 6, including the factors with factor
loading higher than 0.700.
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Table 4. KMO and Bartlett’s Test
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