Identification and Evaluation of Risk Allocation Criteria and Barriers: A Malaysian Public Private Partnership Project Case Study
Norhazilan Md Noor
Risk allocation is a key to managing risks associated with the public private partnership projects. Optimal risk allocation between the parties involved, namely public and private, is the essence of successful PPP project implementation. This study intends to identify and prioritize significant risk allocation criteria and barriers preventing the optimal allocation of risk to PPP projects in Malaysia. Due to interaction among criteria and barriers, this research has adopted analytic network process in order to decompose decision model into meaningful network and weight decision elements. Data has been collected through literature review, questionnaire and interview with PPP project experts. This study reveals that "Bear the risk at lowest price, Control the chance of risk" and "Risk attitude" are three major optimal risk allocation criteria. Different sets of information about project risk, "Lack of efficient risk allocation mechanisms" and Lack of understanding the benefits of optimal allocation are of three major optimal risk allocation barriers identified throughout the study. The outcome can be used to improve the implementation of PPP project in Malaysia by more rationally allocating risks between parties involved.
Received: January 03, 2014;
Accepted: April 09, 2014;
Published: April 29, 2014
Policymakers today prefer to choose Public Private Partnership (PPP) for the
implementation of public mega projects, especially when the government is short
of financial resources (Terry, 1996; Alfen
et al., 2009). Following the successful implementation of a PPP model
in a number of countries including the UK, Hong Kong, Singapore and Australia,
the rate at which PPP based projects have been adopted in Malaysia has increasingly
risen. Malaysia is striving to become a modern and industrialized country by
2020 and Vision 2020 has been set up by the government to help achieve this
target. One aspect of development is the win-win delivery of public projects,
hence, a number of policies have been set up in order to strengthen the relationship
between the public and private sectors which play important roles in project
delivery (Nambiar, 2007; Rusmani,
2010). The government has emphasized in the 10th Malaysian plan that the
pivotal role of PPP is in forming a successful partnership between the public
and private sector. As a result, 52 recent PPP based projects worth an estimated
of RM63 billion have been initiated (EPU, 2010). Such
projects result in the active involvement of the private sector which contributes
hugely to the economy (Leong, 2010).
The need to manage risk in PPP projects has been highlighted by many authors.
Successful completion of PPP projects depends highly on the quality of risk
assessment. It has been found that many construction projects that adopted PPP
in Western countries have not successfully achieved the project objectives although
it is more than a decade since a PPP project was adopted and implemented there
(Thomas et al., 2003). The need to design a
mechanism which systematically allocates risk to PPP in order to manage PPP
project risk is tangible. It is a fact that construction project delays directly
impose extra costs which are mainly due to uncontrolled risk. Risk is inherent
with construction projects (Kartam and Kartam, 2001)
and PPP projects are no exception as stakeholders need to manage complexities
associated with documentation, capital budget, taxation, technical details,
policies and market conditions. Grimsey and Lewis (2002),
Heravi and Hajihosseini (2011). According to AS/NZS
ISO 31000 (2009), risk management is a project management tool. Risk management
process in PPP project contains four main steps that are namely identification
of risk, risk assessment, allocation of risk and replies to reduce risk (Shen
et al., 2006). Risk in PPP project cannot be removed completely.
Probably the word management is more appropriate when dealing with PPP project
risk (Ng and Loosemore, 2007). Malaysia PPP guidelines
define optimal risk sharing as essential features of risk management. It has
been indicated that risk should be allocated to the party who is best able to
manage it. Hence, risk allocation is considered a significant component of the
risk management process of PPP projects.
Hashim (2010) describes how improper risk allocation
has a negative impact on time, cost and PPP project quality. While the risk
allocation process is complex, it is very flexible as it depends on many parameters
such as participants risk attitude and the ability to manage risk and
risk premiums (Zhang et al., 2002; Lam
et al., 2007). In addition to Hashim (2010)
findings, inappropriate risk allocation in PPP projects leads to disagreement,
disputes, claims and eventually distorts relationships among the project parties
(Kumaraswamy, 1997). For the past ten years, several
studies have been conducted on how to optimally allocate the risk of PPP projects
in order to minimize the aforementioned adverse impacts. Notable among these
studies are those of (Rahman and Kumaraswamy, 2005;
Akintoye and Main, 2007; Bing
and Tiong, 1999; Erikson, 1979) who worked on joint
risk management, collaborative relationships in construction, joint ventures
and risk sharing, respectively. Optimal risk allocation is defined as not transferring
all risk to one party (Ke et al., 2011). According
to Gao and Jiang (2008), it is better to pairwise compare
the parties management capabilities and then allocate risk based on these abilities
because the public sector is used to allocating risk to the private sector due
to the inability to manage risk or unwillingness to take responsibility.
The risk assessment process begins with the identification of risk and it is
the responsibility of those who create the risk (Loosemore
and McCarthy, 2008). Risk should then be analyzed in terms of the likelihood
(Thomas et al., 2003) and severity of the impact
on the project target (Lam et al., 2007). One
who can accurately assess risk is more capable to handle risk (Loosemore
and McCarthy, 2008) manage and control the consequence of risk (Loyd,
2001; Lam et al., 2007). Resources to compensate
the consequences of risk must be available when risk occurred (Abednego
and Ogunlana, 2006). Moreover, handling risk requires access to instruments
based on the enlargement of risk (Loosemore and McCarthy,
2008), authority (Loyd, 2001) and expertise (Abednego
and Ogunlana, 2006) to use these instruments. If an individual attempts
to secure additional revenue or provides special security measures, it could
be more capable to bear the risk (Abrahamson, 1973).
Xu et al. (2010) identified and evaluated risk
allocation criteria in a Chinese PPP project which identified 23 criteria for
risk 3 allocation. There are several barriers and basic general factors associated
with risk allocation in the construction industry such as cooperation, negotiation,
teamwork, collaboration, trust and communication. Negotiation is actually a
social decision-making procedure through which two or more people confirms how
to allocate scarce resources (Thompson, 2001).
Loosemore and McCarthy (2008) explained that risk allocation
takes place by means of negotiation regarding contract clauses between project
partners. Communication is a vital factor of negotiation. Open communication
in risk management allows a corporation to evaluate its risk management towards
related organizations which may present relative feedback (Tang
et al., 2006).
Insufficient negotiation and lack of good communication among construction
project sectors could be a barrier to optimal risk allocation. Trust can be
explained as a disposition and attitude regarding readiness depending on the
actions of or the susceptibility towards another party using the potential for
cooperation (Smyth et al., 2010). A lack of
trust can be a major barrier to the collaborative connection between project
partners (Akintoye and Main, 2007). Risk attitudes
and risk awareness of the various participating parties in a construction project
could be a barrier to optimal risk allocation (Alsalman,
2012). Therefore it is necessary to broadly consider the criteria of risk
allocation and barriers to allocate the risk fairly. The objective of this study
is to identify and rank the optimal risk allocation criteria and barriers which
guarantee equitably and optimal allocation of risk for PPP projects in Malaysia.
Analytic network process which is able to see dependence and feedback, is used
in order to rank the importance of barriers and criteria. The results of this
study, which focuses on assigning priority to allocation criteria and barriers
contributes to the existing body of knowledge and can be used in PPP projects,
especially in the construction sector.
MATERIALS AND METHODS
For the sake of data collection, this study reviews journal papers and reports in the area of PPP projects. Review of such literature guides the research work to identify criteria and barriers to decision making for optimal allocation of risk to PPP projects.
Questionnaire: Following the development of a list of criteria and barriers,
a questionnaire was designed and experts were asked to verify the identified
factors. Less significant factors were disregarded in this step. Careful respondent
selection is made for the purpose of knowledge acquisition. All respondents
are selected based on expertise and experience in Malaysia PPP projects in order
to get more realistic data. The main objective of this stage is to identify
significant criteria and barriers of optimal risk allocation for the PPP projects
in Malaysia. The questionnaire for this study is designed in three sections.
The first section explored general demographical information about the survey
respondents, the second section was the main section of the questionnaire (criteria
and barriers to optimal risk allocation in the PPP project) and in the final
section, respondents were given the opportunity to add criteria and barriers
that not otherwise addressed in this survey.
Analytic network process: The next important step is to rank decision
elements. Optimal risk allocation of PPP projects can be viewed as a decision
making problem. Analytic network process is used to derive priority for decision
elements. The Analytic Network Process (ANP) is a multi-criteria decision making
(MCDM) approach which is able to solve complex decision problems (Saaty
and Vargas, 2006). It is a generalized form of analytic hierarchy process
in which a decision problem is decomposed in a network instead of hierarchy
order. In the real world, decision making using ANP is more preferable since
it is able to see dependence and feedback among decision elements and derive
alternative priorities when decision alternatives themselves influence the criteria
(Saaty, 1996). In contrast to AHP where additive synthesis
is employed to derive overall priority of decision alternatives, ANP uses super
matrix approach. A well-structured super matrix needs clear problem decomposition.
In order to fill the necessary elements of super matrix, with the aid of questionnaire,
expert judgments are elicited by asking the experts to compare the relative
dominance of a pair of elements.
Saaty's fundamental 1-9 scale is used during questionnaire design where 1 indicates
the equal importance of two elements and 9 indicates element i overpowering
j. With respect to the fact that no judgment is perfect, especially when it
is being performed by humans, during or reasonably after knowledge elicitation,
the consistency of judgments should be tested and evaluated against Saaty's
consistency index (Saaty, 2005). In order to achieve accurate
results, experts who made inconsistent judgments should be asked to correct
their judgment. Next, local priority vectors of pairwise matrix is estimated
by solving equation Aw = λ max.w where, A is the positive reciprocal matrix
of pairwise comparisons, w is the principal eigenvector (priority vector) and
λmax is the largest eigenvalue of A. Subsequently, super matrix is formed
by entering estimated local priority vectors. In order to determine the final
priority of decision alternatives, unweighted supermatrix which is obtained
right after entering vectors should be transformed first into the stochastic
column or weighted super matrix. Weighted super matrix is a matrix in whose
columns sum to unity. In order to synthesis all interactions, the stochastic
matrix column are raised to large power (Saaty, 2005).
In this study, a "Super Decisions" special software for decision making with
dependence and feedback is used in order to facilitate decision making and minimize
error during the matrix manipulation process. The flow of the research methodology
for this study is schematically illustrated in Fig. 1.
|| Schematic diagram of research methodology
DATA ANALYSIS OF CASE STUDY
Identify risk allocation criteria and barriers: The first step of this study was to identify risk allocation criteria and barriers. Hence, a group of experts including representatives from the design team, project management team, contractors and the most contributing stockholders and clients were gathered and asked to brainstorm a list of criteria and barriers of optimal risk allocation. In addition, library based mechanisms such as a detailed review of relevant journal papers and books, interviews with PPP experts and questionnaire survey were also adopted to collect necessary data. Concerning the questionnaire survey, a total of 120 sets of questionnaires were distributed among the respondents. Among them, a total of 74 valid questionnaires representing 61.67% of the total number of design questionnaires were returned by the correspondents, of which 28 were obtained from the private sector and 46 from the public sector. The results show that the experts have identified 15 significant criteria and 11 barriers for the optimal risk allocation in PPP projects (Table 1 and 2).
Application of ANP method: Saaty's fundamental scale was used and respondents were asked to rank 11 identified risk allocation barriers and 15 criteria based on their experience expertise. Moreover, expert judgments were aggregated by applying geometric mean equation.
A network structure of risk allocation criteria and barriers: Following
the identification of criteria and barriers, decision problems were decomposed
into a meaningful network with the aid of seven experts. Experts identified
inner and outer dependencies among decision elements and the network of connections
were, respectively formed. Indirect comparison of components in arranged Bi
was performed matching to their influence on Cij by considering component
set Bi (i = 1, 2, 3) as the main step for the group criteria and
criteria components set Cj (j = 1, 2, . . ., 10). The ANP network
structure of the criteria is shown in Fig. 2. This is then
followed by indirect comparison of components in set Di matching
to their influence on Eij by considering component set Di
(i = 1, 2, 3) as primary standard for group of barriers and barrier factors
set Ej (j = 1, 2,...,5) as a secondary step, that is, to create judgment
matrix for barriers.
|| Significant risk allocation criteria in Malaysia PPP project
|1: Thomas et al. (2003), 2:
Lam et al. (2007), 3: Gao
and Jiang (2008), 4: Loosemore and McCarthy (2008),
5: Khazaeni et al. (2012), 6: Xu
et al. (2010), 7: EU (2003), 8: Zhu
et al. (2007), 9: Jin and Doloi (2008),
10: Zhang et al. (2002), 11: Wang
et al. (2007)
|| Fundamental comparison scale
|| Pairwise comparison matrix for C22
|| Pairwise comparison matrix for E21
|| Network criteria process
|| Network barrier process
The ANP network structure of the barriers is illustrated in Fig.
Determination of pairwise comparison matrix: Following the development of the network model, pairwise comparisons are conducted to derive weight and importance of various criteria and barriers involved in decision model. Experts were asked to pairwise compare the dominance of each criterion with respect to other criterion according to the decomposed model and connections. They were asked to answer this question: given two elements of i and j, with respect to node k, which of i or j are more influential on k? The 1-9 scale as shown in Table 3 was used in order to acquire this knowledge.
In this study, a group pairwise comparison was employed. A total of 21 experienced
and knowledgeable experts were involved into decision making process. Consequently,
for each set of pairwise comparisons, 21 answers have been obtained. In order
to aggregate 21 sets of pairwise comparisons into a single answer, geometric
average of answers were acquired. A Consistency Ratio (CR) of less than 0.1
demonstrates that judgments were consistent (Saaty, 2005).
For comparison matrices with a value greater than 0.1, experts are asked to
evaluate their judgment and make necessary corrections. In this study, experts
made consistent judgments and the aggregated values were then entered into super
decisions software in order to estimate the weight vector of each decision criteria.
It is noteworthy that aggregations of consistent judgments are still consistent.
The estimated CR after entering aggregated judgments into super decisions software
proves the consistency of judgments. Two examples of pairwise comparison matrices
and CR obtained for the given matrices are shown in Table 4
Determination of the unweighted, weighted and limit super matrix: After
estimating the priority of decision elements, a super matrix should be formed.
A super matrix starts with an unweighted super matrix and merges into a powered
super matrix. Local priorities are directly entered into a matrix of the unweighted
supermatrix. When there is no influence from one element to other elements,
a value of "zero" has been assigned (Saaty, 2005). The
unweighted super matrix was then transformed into a weighted super matrix where
the summation of each column is equal to one. The final priority of a decision
element is derived by increasing the weighted super matrix into power.
|| Weighted super matrix for barriers
|| Limit super matrix for barriers
The computation process has been done with the aid of super decisions software
version 2.2.4. Weighted super matrix and limit barrier matrices are shown in
Table 6 and 7. The outcomes of the priorities
were then obtained from the limit matrix.
RESULTS AND DISCUSSION
Table 8 and 9 show the final priority of
each risk allocation barrier and criteria estimated by limit super matrix of
ANP. In this study with the aid of literature review and questionnaire survey,
11 significant barriers of optimal risk allocation in PPP projects in Malaysia
were identified. These barriers have been categorized into three main groups
namely, behavioral, technical and organizational barriers. The final priority
of risk allocation barriers showed the respondents concurred Different
sets of information about project risk (E31) is the most significant barrier
for optimal risk allocation with the score of 0.1842. In a competitive environment
with a lack of trust between the construction parties, each party tends not
to share his/her information with the other party in the construction project.
Accurate and up-to-date information are necessary to identify, assess and manage
project risks. The second significant barrier is Lack of efficient risk
allocation mechanisms (E21) with a score of 0.1395. Lack of understanding
of the benefits of optimal allocation (E13) is the third barriers factor
with a score of 0.1338.
|| Weight of each risk allocation barriers
|| Weight of each risk allocation criteria
On the other hand, Lack of trust among project participants (E14),
Competitive attitude (E15) and Contract complexity (E22)
are the least significant barriers to optimal risk allocation with a score of
0.0183, 0.0306 and 0.0434, respectively. Accurate and up-to-date information
is necessary to identify, assess and manage project risks. Meanwhile, it is
suggested that for PPP projects, a mechanism should be made in order to more
rationally allocate risks to the parties and to overcome this barrier.
In this study, after reviewing literature and conducting questionnaire survey, 15 significant criteria of optimal risk allocation have been identified. Similar to the barrier stage, a set of criteria have been categorized as risk management competency, incentive mechanism and risk preference. The final weights of elements of these categories shows that Bear the risk at lowest price (C14) is the most important criteria with a score of 0.1527. Among the other risk allocation criteria, Control the chance of risk (C17) and Risk attitude (C32) were the most important criteria with scores of 0.1274 and 0.1099, respectively. On the contrary, Capability of controlling risk (C15) and Foreseeing risk (C12) are the least important with scores of 0.0153 and 0.0156, respectively. The final weight of each risk allocation criteria are presented in Table 9. Risk allocation criteria and barrier rankings could be applied in the optimal risk allocation mechanism.
Successful implementation of public private partnership projects depends highly on optimal allocation of risk among the interested PPP parties. Identification and weight determination of optimal risk allocation barriers and criteria in Malaysia PPP projects was investigated in this study. The 11 significant barriers and 15 significant criteria were identified through literature review and questionnaire survey. In order to weigh barriers and criteria of optimal risk allocation, the problem has been viewed as multi-criteria decision making with dependence and feedback. ANP has been adopted as a decision making tool. With the aid of super decisions software, weights of each decision element were obtained. The result shows that Different sets of information about project risk, "Lack of efficient risk allocation mechanisms" and Lack of understanding of the benefits of optimal allocation" are placed among the top three optimal risk allocation barriers in Malaysia PPP projects. On the other hand, the top three of optimal risk allocation criteria were identified as "Bear the risk at lowest price", "Control the chance of risk" and "Risk attitude. Identifying and ranking these barriers and criteria could help PPP projects overcome these barriers and criteria to achieve optimal risk allocation easier and faster.
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