Identifying Measures of Effective Risk Management for Public–Private Partnership Infrastructure Projects in Developing Countries (original) (raw)

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Khwaja Mateen Mazher

1,*,

Albert P. C. Chan

2,

Rafiq M. Choudhry

3,

Hafiz Zahoor

4,

David J. Edwards

5,6,

Ahmed M. Ghaithan

1,

Awsan Mohammed

1 and

Mubashir Aziz

7,8

1

Department of Construction Engineering and Management, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia

2

Department of Building and Real Estate, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China

3

Construction Engineering and Management, Civil Engineering Department, College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia

4

College of Civil Engineering, National University of Sciences and Technology, Risalpur Campus, Nowshera 24080, Pakistan

5

School of Engineering and the Built Environment, Birmingham City University, Birmingham B4 7BD, UK

6

Faculty of Engineering and the Built Environment, University of Johannesburg, Doornfontein 2028, South Africa

7

Department of Civil and Environmental Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia

8

Interdisciplinary Research Center for Construction and Building Materials, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia

*

Author to whom correspondence should be addressed.

Submission received: 23 August 2022 /Revised: 19 October 2022 /Accepted: 24 October 2022 /Published: 29 October 2022

Abstract

:

The inadequate risk management of public–private partnership (PPP) projects is a principal cause of project distress or failure. This research seeks to identify and empirically validate measures of effective risk management (ERM) in the context of PPPs in a developing country, a subject that has received scant attention in the extant literature. The research is based on a comprehensive literature review, expert interviews and a questionnaire survey. Mean score ranking and factor analysis were employed to rank and group the identified measures, respectively. Tests were performed to determine the respondents’ agreement and establish the reliability and validity of the survey instrument. Analysis results indicate that all identified measures are important, are distributed over the entire project’s life cycle and exhibit a multi-organizational focus. The most significant measures focus on PPP-specific artifacts and procurement activities that are vital for ERM. Factor analysis established six critical underlying dimensions for the ERM of PPP projects. The extracted factors generally acknowledge the need for expert public- and private-sector project stakeholders with mature organizational structures, business processes and relevant experience to successfully handle and deliver PPP projects. Furthermore, a comprehensive PPP policy and sound legal and regulatory frameworks are essential for supporting the ERM of PPP projects. The findings will enable a better understanding of factors that influence the quality and outcomes of risk management efforts and promote sustainable infrastructure development via PPPs, where the success of a project strongly relies on positively managing a project’s risks in the economic and the social domains.

1. Introduction

Risk is defined as an uncertain event or condition, the effect of which manifests as either benefit or loss to project objectives (e.g., scope, quality, cost and schedule) and to specific individual, group or organizational objectives [1,2]. Construction projects are inherently complex and involve significant risks [3]. However, when compared with traditional procurement methods, PPP projects are riskier due to long concession periods, high capital investment, the complexity of contracts, the diversity of motives and interests of various project participants and nonrecourse financing arrangements [4,5]. Additionally, traditional risk management faces greater challenges due to the longer contract periods associated with long-term PPP projects in contrast with the short-term contract periods of traditional projects [6].

Existing literature specifies a systematic approach to implementing risk management and prescribes a range of guidelines, standard processes, tools and techniques to be adopted [2,7,8,9]. Yet despite all this existing knowledge, PPP projects have occasionally suffered failure due to poor risk management [10,11]. Inefficiencies leading to such outcomes can generally be traced back to individual risk management process (RMP) components and may be generated as a result of: the inadequate specification of risk within the contract; the lack of the identification of risks [12,13]; the poor assessment and allocation of risks [11,12,13]; re-allocation upon default of a party to shoulder a risk; the lack of contractually allocated risk enforcement in the event of the crystallization of a risk; and high transaction costs in determining the allocation of risks following a risk event [12]. Therefore, effective risk management is a significant driver of PPP project success [2,14,15]. Chapman and Ward [16] contended that ERM involves “… doing the right things with respect to the risk management process (RMP) so that the project is risk efficient in the corporate sense and all other project objectives are achieved”.

Extant literature has identified several factors that may be significant for the ERM of PPP projects, such as: the risk management maturity of project stakeholders; experience delivering and managing projects under PPP arrangements; access to suitable risk mitigation resources; adequate dispute-resolution frameworks; and collaborative risk management [17,18,19,20,21,22,23,24]. These factors represent important environmental, organizational and project parameters and conditions that if absent in the context of a given PPP project can negatively influence the success of risk management efforts. Moreover, these and similar factors have either been reported individually or in clusters in separate studies. Nevertheless, such factors have not been studied comprehensively with the aim of suggesting significant factors that influence ERM in the context of PPPs. Furthermore, extant literature lacks detailed quantitative analysis and does not provide insights into the significance and grouping of factors to achieve ERM, especially in the context of developing countries and emerging markets for PPP infrastructure projects. Given this knowledge gap, this research aims to identify factors and underlying relationships between the factors that influence ERM (henceforth, the measures of ERM), i.e., enable the adequate deployment of the RMP, achieve both PPP stakeholders’ and project objectives and promote sustainable infrastructure development.

2. PPP Risk Management Research

Existing literature reveals that PPP risk management has attracted substantial academic attention, where most research conducted focuses upon singular aspects of the generic risk management process including: risk identification and/or analysis [15,25,26,27,28,29,30,31,32,33] and response planning including risk allocation and mitigation [24,34,35,36,37,38,39]. A significant focus has been on the identification of risks, mitigation strategies and the development of models for estimating and prioritizing risks and for the assessment of response strategies to select the most efficient response. Fischer et al. [18] argued that in addition to the technical aspects of risk management in PPPs, managerial aspects of risk management also require greater consideration.

Beyond the traditional streams of research on risk management, as alluded to above, various sources have approached the so-called concept of ERM under various alternative themes. Choudhry and Iqbal [40] and Chileshe and Kikwasi [41] explored barriers to ERM and barriers to the implementation of risk assessment and management practices in the construction industries in developing countries, respectively. The practice standard for project risk management by the project management institute (PMI) enlists various critical success factors (CSFs) for project risk management and each of its component processes [8]. Chileshe and Kikwasi [42] also investigated the CSFs for the deployment of risk assessment and management practices in the construction industry from the perspective of a developing country. Chinyio and Fergusson [43] explored various difficulties in risk analysis and management in private finance initiative (PFI) projects in the UK by interviewing industry experts and presented solutions. Ke et al. [44], while investigating the poor record of risk management on PPP projects in China, identified an absence of a risk management culture as a significant underlying factor. Loosemore and Cheung [11] criticized the traditional reductionist and linear risk management approaches to projects and discussed multiple failed PPP cases. Wibowo and Taufik [19] and Zhao et al. [45] worked towards developing models for the assessment of organizational risk management maturity in different settings. Jin and Zhang [36] studied critical uncertainty factors that influence efficient risk allocation on PPP projects. Marques and Berg [46] stressed efficient risk allocation for regulation by contracts in PPP projects, whereas Lee and Schaufelberger [47] identified main causes and consequences of risk mitigation failure in five case study PPP projects and suggested individual risk mitigation measures in the conclusion.

It is apparent from this review that few studies, if any, have explicitly addressed the issue of ERM holistically in the context of infrastructure PPPs while focusing on developing countries and emerging markets for PPP infrastructure projects. Thus, there is a need to uniquely identify the measures of ERM and assess their relative importance to determine the most significant measures. Furthermore, these measures need to be grouped in a systematic way to understand the principal dimensions of ERM for PPPs.

3. Measures of Effective Risk Management

A comprehensive literature review (and the content analysis of such) sought to understand and identify significant measures that may influence risk management outcomes on PPP projects, for which a diverse range of literature was scrutinized and synthesized (Table 1). The review revealed that substantial support was given to aspects of stakeholders’ experience, capacity and maturity that can significantly influence the project’s risk profile. In addition, collaboration among stakeholders to augment risk management has received noteworthy attention. Intra- and inter-organization risk communication and reporting are also considered critical for risk management to function optimally. Similarly, continuous commitment by all stakeholders to the risk management function has been advocated as essential. Because risks must be investigated from a life-cycle perspective in PPP projects, which are inextricably linked to projects’ and stakeholders’ objectives and requirements, a comprehensive risks and requirements evaluation is necessary where the adequate assessment of these risks is possible only by the application of appropriate tools and methods. Scholars have also emphasized the comprehensiveness and quality of project feasibility studies and the financial model. Multiple studies documented the importance of developing and maintaining a project risk management plan and adopting good project management practices. Risk management is also inextricably linked with the development and administration of a sound and clear contract document that protects the associated interests, which should be supported by an efficient negotiation process for incorporating all key stakeholders’ perspectives. Reliable risk assessment and mitigation require multiple resources such as historical data, specialist consultants and advisors and risk mitigation instruments. Both the availability and reliability of these aforementioned resources may influence the prospects of ERM for projects. Learning from risks is an important aspect of improving risk management outcomes. Third-party/gateway reviews are also suggested to be valuable for curbing various potential biases (cognitive/motivational) and/or probable errors in project estimates that may undermine risk management outcomes for projects. Based on the review and semi-structured interviews (discussed later), a total of 30 measures for ERM were obtained (Table 2). A brief review of the extracted measures reveals that the attributes are distributed over the entire project’s life cycle and exhibit a multi-organizational focus.

4. Research Methodology

An exploratory, sequential, and mixed-methods design was adopted for this research [95]. Qualitative methods were first employed for the development of measures of ERM from the in-depth literature review and semi-structured interviews. This was followed by a quantitative questionnaire-based data collection approach in order to: determine the relative importance of the measures and establish underlying relationships, to reduce the number of measures [96,97].

4.1. Questionnaire and Sample

Semi-structured interviews were conducted with eight experts in Pakistan to identify factors that significantly influence risk management on projects, the ambition being to complement the literature review findings with expert opinion. These experts came from the public (5) and private (3) sectors, had 5–15 years’ experience handling PPP power and transport infrastructure projects, and had undertaken various roles within the industry such as: deputy director; director; financial analyst; infrastructure specialist and chief operating officer. Keeping in view the experience of the interviewees in having managed or currently managing multiple projects and their representation of both public- and private-sector interests from multiple infrastructure sectors, the responses obtained were deemed sufficient. Due to restrictions on time and an inability to solicit the commitment of more experts, the interviews were limited to eight only. The interviewees suggested ten factors including: proper planning and joint risk management; experience and institutional capacity of the public/private sector in managing PPP projects; expertise of foreign financial institutions; public sector’s contract administration skills (concession agreements); characteristics of the project sponsor (foreign/local, experience, risk attitude, capacity to absorb risks, etc.); the quality of feasibility studies; the availability of risk mitigation instruments; the availability of reliable historical data on projects; the development and use of comprehensive risk management plans; and the availability of reliable specialist consultants and advisors, as reported by Mazher et al. [98]. These identified factors concurred with the findings from the literature review. The draft questionnaire developed was piloted with and reviewed by five experts from the interview panel in order to ensure the comprehensiveness, suitability and adequacy of the questionnaire. Two other experts, one senior academic from Hong Kong with experience in PPP research and one industry expert representing a large-transaction advisory firm in Australia with 25 years of experience working on PPP projects, were invited to review and comment on the identified measures of ERM. The respondents broadly agreed with the relevance of the factors identified and suggested only minor revisions. The finalized questionnaire comprised multiple sections and included definitions for all identified measures of ERM to facilitate consistent understanding by the respondents. It was then distributed to PPP infrastructure experts in Pakistan for completion. Purposive sampling and semi-snowballing [99] were adopted to ensure that respondents had sufficient working experience (implementation and/or execution) on at least one PPP infrastructure project and possessed relevant exposure to dealing with PPP-specific transactions and risks incurred. This combined sampling approach suited the local context well as there were no comprehensive directories listing PPP experts and their attributes; therefore, referrals from purposively identified experts were used to expand the data collection envelope [14]. All the experts who participated in the interviews and those who responded to the survey did so voluntarily. Following ethical considerations, it was explicitly communicated to the experts that any data collected for the purpose of this research would be used for academic purposes only and that the identities of the participating experts would be kept anonymous.

4.2. Data Analysis

The software tool Statistical Package for Social Science (SPSS) v 23.0 was employed for various analyses such as mean score ranking, agreement analysis, tests for reliability and validity and factor analysis.

4.2.1. Mean Score Ranking

Mean score ranking (MSR) was employed to compute the relative importance of the measures of ERM. A 7-point Likert scale (where one is not important and seven is extremely important) was used for all items on the questionnaire [100].

4.2.2. Agreement Analysis

Since the total number of attributes being evaluated was more than seven, chi-square was used instead of Kendall’s coefficient of concordance to determine the agreement between respondents [101]. Furthermore, in order to check the agreement in rankings between respondents from different sectors (public or private), Spearman’s rank correlation coefficient was determined [23,25,42,97]. If the chi-square and test (rs) coefficients are significant at or above critical values at a predetermined significance level (0.05), then there is no significant disagreement between the respondents both within a group and between the groups [101].

4.2.3. Factor Analysis

Factor analysis (FA) assists in identifying a smaller number of factors that can explain most of the variances observed by simplifying a larger matrix of correlations [102]. The appropriateness of applying FA for the extraction of factors was determined by evaluating multiple indices including: correlation coefficients; Bartlett’s test of sphericity; an anti-image correlation matrix; and the Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy (MSA) [103].

4.2.4. Reliability and Validity

It is important to establish the reliability and validity of a questionnaire instrument in research driven by questionnaire-based data collection. For internal consistency and reliability, Cronbach’s coefficient test was applied [104]. According to Wong and Aspinwall [105], content validity cannot be judged numerically and can only be subjectively assessed by the researchers. Construct validity was established by testing the extracted factors for unifactoriality [106]. These approaches to testing reliability and validity were also adopted by Yang et al. [97].

5. Data Analysis and Results

5.1. Questionnaire Survey Results

In total, 140 questionnaires were distributed to experts who agreed to participate upon initial contact, and responses were collected via mail (post), e-mail and in-person. Some investigator-administered questionnaire sessions were also conducted to improve the response rate and obtain contextual details on how and why certain perceptions exist. In total, 90 completed questionnaires were received, giving a response rate of 64.3%. The response rate was deemed acceptable and in line with previous studies [23,25]. Table 3 reproduces respondent characteristics including designation, sector affiliation and years of experience. The participating experts belonged to a vast array of organizations including: PPP units (federal/provincial); public authorities; lending institutions; investors; consultants and project sponsors/companies. Nearly half, 47.8%, of experts had more than 5 years of working experience on PPP projects, while nearly 36% had processed 10 or more projects during their career. Given the inherent limitations of questionnaire surveys, diverse participation from an array of key PPP stakeholders, an acceptable response rate and the sufficient working experience of participants cumulatively support the authenticity and reliability of the survey responses.

5.2. Descriptive Statistics and Agreement Analysis for Measures of ERM

The data collected on rankings of the measures of ERM was subjected to MSR analysis to obtain the relative importance of the measures and determine the most significant measures. Table 4 illustrates that all of the identified measures were ranked from moderately to extremely important (on average), while no measure was rated less important (on average). Quality of the project’s financial model (MERM_9) was ranked as the most significant measure for ERM, whereas a flexible and collaboration supportive contract (MERM_22) received the lowest rating of 4.87. The adequate administration/management of the contract between the public and private sectors (concession agreement) (MERM_7), a comprehensive project risk management plan (MERM_3), the identification of the project’s and key stakeholders’ objectives and requirements (MERM_1), careful bid evaluation by the public sector (MERM_26) and efficient contract negotiations (MERM_6) are other measures that received an average rating of at least very important (6). Comparisons of chi-square (442.441) and Spearman’s rank correlation (0.827) coefficients (at 0.05 significance), with critical values of 42.557 and 0.306, respectively (at 29 degrees of freedom), indicated consistency among the respondents and a consensus among the public- and private-sector respondents on the rankings and thus the significance of the measures of ERM.

5.3. Factor Analysis for Measures of ERM

To reduce the large number of measures into fewer independent factor groups or components, FA was performed. Correlation coefficients for most of the measures were found to be above 0.3, ensuring sufficient interrelationships [103]. Bartlett’s test of sphericity returned a large value of 1553.67 (at p = 0.000), and the KMO measure of sampling adequacy was 0.753, which is considered acceptable and provides evidence of factorability [107]. The MSA values on the diagonal of the anti-image correlation matrix were also found to be higher than 0.5 and ranged from 0.544 to 0.903, thus obviating the need to remove any factors. A clean solution was obtained with a 6-factor model that had a low number of cross-loadings, individual factor loadings above 0.3 and factor groups containing at least 3 items. The factor loading cut-off point is usually set at 0.4; however, for more significant factors, a cut-off at 0.5 was set. The extracted factor model explained 62.471% of total variance. Table 5 reports upon the six factor groups along with their component factors, factor loadings, eigenvalues and other attributes.

5.4. Reliability and Validity Test for Factor Analysis

The overall Cronbach’s alpha was 0.926, indicating the good internal consistency and reliability of the instrument since values above 0.7 are regarded as sufficient [104]. Content validity was confirmed by conducting a detailed literature review, semi-structured interviews and a pilot study in order to merge expert experience with the information extracted from the published literature. Construct validity was established by subjecting each extracted component to FA individually. If all the variables form a single factor again, then the factor is valid as a construct [106]. All six extracted factors were demonstrated to be unifactorial with satisfactory KMO values and a significant percentage of variance explained. In addition, internal consistencies of the extracted factors were also evaluated using Cronbach’s alpha, and all the values exceeded 0.7 (Table 6).

6. Discussion

The MSR results show a strong perception of Pakistani PPP experts towards the importance of measures of ERM. All the identified measures were ranked from moderate to extremely important (on average) for the ERM of PPP infrastructure projects. The Pakistani PPP market is dominated with projects in the power generation and highway infrastructure sectors [108]. The knowledge, experience and maturity of public- and private-sector stakeholders to sustainably implement and manage PPP projects vary considerably across different regions and different infrastructure sectors (economic and social) and subsectors (energy, municipal solid waste, transport, water and sewerage, etc.). Similarly, there may be difficulties in accessing essential resources for ERM in terms of historical performance data on PPP projects, reliable specialist consultants/external advisors, essential regulations and institutional frameworks, and risk mitigation tools/instruments (guarantees, insurances, hedges/swaps, etc.). This may be an issue for the ERM of PPP projects in Pakistan because ERM measures that pertain to the knowledge, experience and maturity of public- and private-sector stakeholders and the availability of essential resources all rank high for enabling ERM. The Infrascope index [109,110,111], which evaluates the capability of countries to implement efficient and sustainable infrastructure PPPs, ranks many developing countries in the low-maturity performance categories, including Pakistan. The index is based on the evaluation of several indicators in five key domains including an assessment of enabling laws and regulations, institutional frameworks, transparency and accountability and the maturity and experience of governments with PPPs and finance, among others. Issues with any shortfalls in these domains/indicators are now known to be impediments to the ERM of PPPs. This conclusion is based on the findings from the reviewed literature and the survey conducted for this research. It can be argued that many of these indicators overlap with ERM measures identified in this research; therefore, by extension, it can be safely assumed that similar perceptions of the importance of the measures of ERM will exist in other developing countries as well. For mature countries/markets, the perceptions of PPP experts of the importance of the ERM measures are expected to be different. This may be attributable to the differences in the nature of challenges faced in the implementation of efficient and sustainable infrastructure PPPs in developed countries/markets.

The FA resulted in identifying six critical underlying dimensions for the ERM of PPP projects. It is clear from the results that the implementation of risk management processes alone by each stakeholder may not maintain a project that is well shielded from the effects of risks. In the absence of: deep knowledge of critical project aspects, the comprehensive understanding of stakeholder requirements, a mature public-sector client, the availability of resources for high-quality risk assessments, adequate mechanisms for post-contract risk management and mature business processes of project stakeholders, the superficial risk management application by key stakeholders will lead to suboptimal decisions and leave the project exposed to the effects of risks over its life cycle. The underlying dimensions originating from the FA are prescriptive in nature (explained later), as these dimensions suggest essential requirements for the ERM of PPPs. Therefore, the outcomes of the FA may be generalized in a broader sense and may be applicable and interpreted beyond the confines of any specific country/PPP market boundaries.

6.1. ERM Factor Group 1: Knowledge Driven Risk Management

This factor group explains 32.723 percent of the total variance in the FA and consists of 4 factors. Knowledge of various aspects of the project is the key to achieving ERM outcomes. The requisite knowledge may be either tacit or explicit in nature, and it may be leveraged from different sources. Longer contract periods associated with long-term PPP projects, usually spanning several decades, lead to complications in developing a structured and accessible memory of all project events. Knowledge pertaining to identified risks and formally approved risk management strategies resides in written contracts, risk registers and other forms of formal project documentation. However, the backend inter- and intra-stakeholder negotiations (between the public-sector client, equity investors/sponsors, debt financiers, design and/or construction contractors and subcontractors, operators, etc.), meetings, discussions and any short- and long-term commitments made are not always well documented and/or communicated. Moreover, the personal experiences of the project officials and stakeholders and any contextual learning about a project’s issues and circumstances occurs over the life cycle of the project, most of which cannot be effectively documented and/or transferred. All of this knowledge is vital in supporting the critical risk management processes of risk planning and risk monitoring and control. Thus, the continuity of the project team may be the only viable solution.

From an organizational perspective, retaining project procurement officials for project implementation may be important when focusing on the tacit knowledge aspect of the project. From a long-term and explicit knowledge perspective, PPP project organizations including the public-sector client and the consortium members must enable systematic learning from projects to capture and learn from experiences and become effective for risk management on projects. Robinson et al. [112] and Virginia Public–Private Partnerships [9] stressed the importance of knowledge transfer and capturing and feedback lessons learned, respectively, in order to strengthen the risk management function for PFI/PPP projects. A more superior source of knowledge that may be leveraged for ERM is reliable external legal, technical and financial consultants/advisors who can bring their vast experience of working with similar projects. This may be especially beneficial for countries with limited experience with private investment in public infrastructure development. Asenova and Beck [92] contended that financial risk analysis in PFI (or PPP) projects relies heavily on external advisors, but occasionally their lack of experience and/or communication problems led to a lack of satisfaction with the information provided by them.

6.2. ERM Factor Group 2: Comprehensive Requirements and Risks Evaluation

This factor group accounts for 8.409 percent of the total variance in the analysis and comprises 4 factors. PPP projects are composed of a large team of primary stakeholders and influence a vast array of secondary stakeholders because these projects primarily exist for providing public services. Hence, the adequate development of all objectives and requirements by all the primary stakeholders to define and deliver true value is a challenging task. It is also essential because risks are inherently linked to the identified objectives and requirements. Consultation with stakeholders may serve as an important source of information and can assist the government authority as it may potentially improve risk outcomes and assist in risk–response planning and control [9,113]. The realization of these objectives is linked to the RMPs through predefined success criteria [67]. Organizations with a high level of risk management maturity (and concomitant policies and processes) can better identify and assess the requirements and their associated risks effectively.

The careful evaluation of the expression of interest and tenders by the public sector is also necessary for establishing the financial and technical capabilities of the consortium along with the level of understanding of the client’s requirements and to assess the consortium’s risk management capabilities [67,114]. The financial model is used for preliminary due diligence by lenders and also assists relevant stakeholders in: analyzing the impact of risks; assessing a project’s returns, cash flows and financial robustness; negotiating risk allocation among the parties and monitoring the PPP project over the concession period [85,115].

6.3. ERM Factor Group 3: Public Sector Risk Management

This factor group explains 6.799 percent of the total variance with 3 factors. The public-sector client, being the main stakeholder in PPP projects, significantly controls the risk management performance on PPP projects because risk management starts with them. It is the client that lays the foundation of the project risk management framework in the project contract. At the time of structuring contracts for PPP projects, it is decided which risks will be retained by the public sector. The public-sector client can effectively decide on risk transfer implications if the private sector can explicitly and separately price risks in their tenders that they consider unsuitable for transfer to them [94]. It is also possible that a lack of experience and knowledge of the public-sector client (in PPP-based project delivery) may result in a poor evaluation of a project’s actual risk exposure and the acceptance of unwanted risks to attract investment, resulting in higher cost to the government and default on payments [23]. Apart from the issue of proper risk structuring, the motivation of a government in pursuing PPP projects may be questionable. Bruzelius et al. [116] and Matsumoto [58] argued that politicians can have an influence in biasing forecasts (in feasibility studies for project selection) to support project approvals. This directly impacts the management of risks. Accountability and transparency can be enhanced by providing detailed audit points at each stage of a PPP project life cycle and by specifying third-party evaluations, “… thereby preventing sloppy risk management and opaque decision-making processes” by concerned government organizations [58]. Experience delivering PPP projects and comprehensive frameworks for accountability and transparency takes time and effort to develop and mature; therefore, these are well-anticipated challenges for emerging PPP markets and developing economies.

6.4. ERM Factor Group 4: Risk Assessment Quality

This factor group explains 5.412 percent of the total variance in the analysis and includes 5 factors. Another important underlying dimension for ERM is the quality of risk assessment, which requires objective and reliable data and trained risk analysts who know what they are doing when it comes to PPP projects. The quality of risk assessments will depend on: the quality of the input data and information; the nature of assumptions made in the analysis; the tools employed; and the availability of knowledge and skills to make the best use of the available resources and methods. Chinyio and Fergusson [43] argued that training programs, conferences and seminars can help organizations to enhance their risk assessment skills and could overcome the limited supply of experts on PFI (or PPP) risk assessment. This may be especially true for PPPs in emerging markets. Another issue, again more applicable to emerging PPP markets, is the lack of availability of historical data on previous projects. This poses a significant hurdle as it leads to the inadequate modeling and analysis of risks [15,43]. Apart from the issue of the lack of historical data, poor and biased technical feasibility, social and environmental sustainability assessments provide a poor basis for risk analysis. Kumaraswamy and Morris [76] and Ng and Loosemore [71] presented multiple case studies of PPP projects whose failure was attributed in part to overly optimistic feasibility studies.

6.5. ERM Factor Group 5: Post-Contract Risk Management

The total variance explained by this factor group amounts to 4.873 percent, and it is composed of 5 factors that are relevant to post-contract risk management. The contract administration of PPP projects spans long periods of time, usually amounting to decades. This long-term nature of PPP contracts calls for special attention to the programming of informal and formal interparty relationships to support joint risk management. Moreover, risk management at the post-contract stage can be more effective if the PPP projects are supported by well-established and transparent legal and regulatory frameworks and assistance from mature financial institutions, both of which can provide cover to contractual parties from excessive and uncertain risk exposure. Changes in a PPP contract may be initiated as a result of modifications in laws and regulations, private-partner-initiated modifications, project enhancements or revisions in service requirements [57]. Therefore, PPP contracts should be flexible with an aim to provide options for adjustments in face of future uncertainty [113,115] and carefully manage the risk exposure of contractual parties. In case of a failure of the contractual mechanisms to address a change, options available for conflict and dispute resolution will aim to redistribute the risks among contractual partners. Here, the comprehensiveness of the applicable legal and regulatory frameworks to a project will ensure fair and equitable resolutions and the fair sharing of risks and rewards. Doloi [83] contended that levels of trust and confidence among parties influence the joint management of risks. Hence, increased confidence, trust and cooperation among parties may go a long way towards enabling ERM on projects.

Risk mitigation instruments such as hedging instruments, credit/export credit guarantees and political risk insurance are used as risk transfer strategies at the post-contract stage; however, their availability and associated costs depend upon a variety of factors that may become an important consideration for ERM [117,118]. This factor could be of particular concern for PPP projects in emerging markets and developing economies.

6.6. ERM Factor Group 6: Well Documented Structured Management Approach

This factor group accommodates four factors and accounts for 4.255 percent of the total variance in FA. This last factor group calls attention to an overall mature management approach by both the public- and the private-sector project stakeholders. This is important because the management and the administrative frameworks of the project stakeholders’ enterprises act as a container for the individual risk management processes. Fischer et al. [18] argued that risk management can only operate effectively as part of a well-established project management scheme. RMPs do not operate in siloes as they interact with other project management processes to obtain inputs and provide outputs. Any strategies made to counter and contain the impacts of risks are documented in the risk management plan and the contracts and later enforced via contracts to ensure protection against risk exposure. For the purpose of establishing these contracts, efficient contract negotiations become important in the context of equitable sharing of risks and rewards. Each party needs to appreciate and understand the interests of and risks to others to conduct efficient negotiations [18]. Not being able to implement an effective contract management strategy is a project risk in itself, and many parties fail at it; hence, it must be managed to avoid failure in meeting contractual obligations [119].

7. Conclusions and Recommendations

PPP projects globally have suffered performance issues and occasionally failure for reasons attributed to ineffective risk management. While existing guidelines and risk management processes, tools and techniques enable the systematic execution of risk management on projects, their optimum deployment is dependent upon many environmental, project and organizational parameters that determine their effectiveness. Given the deficiencies in the existing literature, this research sought to explicitly highlight and quantitatively assess the specific measures that can influence the effectiveness of risk management efforts in the context of PPP projects. The measures identified were validated using a comprehensive research methodology based on literature review, interviews and a survey of industry experts. Based on the MSR, the most critical measures for ERM include: quality of the project’s financial model (MERM_9); the adequate administration/management of the contract between the public and private sectors (concession agreement) (MERM_7); a comprehensive project risk management plan (MERM_3); the identification of the project’s and key stakeholders’ objectives and requirements (MERM_1); careful bid evaluation by the public sector (MERM_26); and efficient contract negotiations (MERM_6)—all of which achieved an average rating of at least very important.

FA revealed six critical underlying dimensions that influence ERM. Out of 62.471% of total variation explained, the factor knowledge-driven risk management accounts for 32.723%, which emphasizes harnessing the potential of acquired experiences, lessons learned and risk management knowledge gained from projects. Other identified factor groups point towards the significance of: a comprehensive evaluation of the stakeholders’ and project’s requirements and the quality of risk assessments in relation to meeting the requirements; elements critical to post-contract risk management; a well-documented and structured management process and the roles of government institutions (and their project execution arms) for managing risks effectively.

The critical measures exhibit multi-organizational characteristics such that both the public- and private-sector stakeholders can contribute to their successful implementation on projects and influence the entire project life cycle. For example, the experience of the stakeholders and their maturity are aspects that would influence risk management outcomes across the project life cycle and are also relevant to all the stakeholders involved whether in the public or the private sector. Therefore, in order to provide a structure, the identified measures were organized based on the life cycle framework, with project phases as defined by European PPP Expertise Centre [120] and further indicated in terms of their relevance to the public and/or private party and the relevant risk management processes (Figure 1). It should be noted from this mapping that some of the measures only benefit the public-sector stakeholder (e.g., the careful evaluation of bids) by enhancing risk management outcomes and perhaps protecting and/or improving value for money and other government objectives. There is not a single measure that applies only to the private sector; most of the measures potentially benefit both the stakeholders. Moreover, focused efforts are required from the very beginning of the project’s life cycle because many of the identified measures are relevant from the beginning of the project-related efforts. For countries with limited experience procuring infrastructure projects using the PPP mode of project delivery, the identified measures highlight aspects that need due consideration.

The findings reflect the perceptions of respondents from a developing country with low maturity in PPP project implementation. Hence, the findings may be generalizable to other similar geographical locations i.e., emerging PPP markets and developing economies. The measures of ERM may be further explored in mature PPP markets to determine any similarities and/or differences. Efforts in this direction may involve a more rigorous research regime that utilizes a larger panel of experts and/or case studies to explore the level of implementation of these measures on actual projects to further validate the findings.

Author Contributions

Conceptualization, K.M.M. and A.P.C.C.; methodology, K.M.M., A.P.C.C., R.M.C. and H.Z.; validation, R.M.C., D.J.E., A.M.G. and A.M.; formal analysis, K.M.M., H.Z. and M.A.; investigation, K.M.M. and A.P.C.C.; resources, K.M.M., A.P.C.C. and D.J.E.; data curation, K.M.M.; writing—original draft preparation, K.M.M. and R.M.C.; writing—review and editing, A.P.C.C., R.M.C., D.J.E., H.Z., A.M.G., A.M. and M.A.; visualization, H.Z. and M.A.; supervision, A.P.C.C.; project administration, K.M.M. and A.P.C.C. funding acquisition, K.M.M. All authors have read and agreed to the published version of the manuscript.

Funding

The APC of the article was funded by the Deanship of Scientific Research (DSR), King Fahd University of Petroleum and Minerals, KFUPM, Saudi Arabia.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The authors wish to acknowledge and appreciate the support of King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Mapping of measures of effective risk management.

Figure 1. Mapping of measures of effective risk management.

Table 1. Reference source/type and frequency.

Table 1. Reference source/type and frequency.

Table 2. Measures of ERM with reference source and frequency.

Table 2. Measures of ERM with reference source and frequency.

Table 3. Experts’ profile.

Table 3. Experts’ profile.

Table 4. Descriptive statistics of the measures of ERM.

Table 4. Descriptive statistics of the measures of ERM.

Table 5. Results of factor analysis.

Table 5. Results of factor analysis.

Table 6. Unifactorial test.

Table 6. Unifactorial test.

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

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Mazher, K.M.; Chan, A.P.C.; Choudhry, R.M.; Zahoor, H.; Edwards, D.J.; Ghaithan, A.M.; Mohammed, A.; Aziz, M. Identifying Measures of Effective Risk Management for Public–Private Partnership Infrastructure Projects in Developing Countries. Sustainability 2022, 14, 14149. https://doi.org/10.3390/su142114149

AMA Style

Mazher KM, Chan APC, Choudhry RM, Zahoor H, Edwards DJ, Ghaithan AM, Mohammed A, Aziz M. Identifying Measures of Effective Risk Management for Public–Private Partnership Infrastructure Projects in Developing Countries. Sustainability. 2022; 14(21):14149. https://doi.org/10.3390/su142114149

Chicago/Turabian Style

Mazher, Khwaja Mateen, Albert P. C. Chan, Rafiq M. Choudhry, Hafiz Zahoor, David J. Edwards, Ahmed M. Ghaithan, Awsan Mohammed, and Mubashir Aziz. 2022. "Identifying Measures of Effective Risk Management for Public–Private Partnership Infrastructure Projects in Developing Countries" Sustainability 14, no. 21: 14149. https://doi.org/10.3390/su142114149

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