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Review

Operational Risk Management of Public–Private Partnership Infrastructure Projects: A Bibliometric Literature Review

by
Weiling Jiang
1,*,
Qianying Yang
1,
Jie Jiang
1,
Igor Martek
2 and
Fanjie Gao
1
1
School of Architecture and Urban-Rural Planning, Sichuan Agricultural University, Dujiangyan 611830, China
2
School of Architecture and Built Environment, Waterfront Campus, Deakin University, Geelong 3220, Australia
*
Author to whom correspondence should be addressed.
Buildings 2022, 12(11), 1905; https://doi.org/10.3390/buildings12111905
Submission received: 1 October 2022 / Revised: 16 October 2022 / Accepted: 27 October 2022 / Published: 7 November 2022
(This article belongs to the Section Construction Management, and Computers & Digitization)
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Abstract

:
Public–private partnerships (PPPs) are widely applied in the procurement of capital infrastructure, encompassing phases such as financing, design, construction, operation, and transfer. Of these, the operational phase of PPPs is particularly critical to project success given this is when revenues are generated, and costs recouped. However, the revenue stream will be exposed to numerous risks over the relatively long period of infrastructure operation. Management of PPP operational risk is therefore critical. Despite this importance, research dedicated to PPP operational risk management remains limited. Thus, this paper addresses this deficiency by systematically reviewing related studies and proposing an operational risk management framework. A qualitative bibliometric literature review is conducted on 60 papers pertinent to operational risk management, published across 12 peer review journals. Findings reveal that the industry lacks a systematic operational risk factor list, while the impacts of risks are rarely considered when allocating operational risk factors, and moreover that the research on the selection and efficacy of operational risk management strategies remains undeveloped. This study reveals where further efforts in the research of operational risk management of PPP infrastructure projects could be more fruitfully applied.

1. Introduction

Infrastructure is considered foundational to national economic development and consequently to poverty alleviation [1,2,3]. However, national governments, particularly in the developing world, typically face major shortages of the capital and technology needed to satisfy current demands for infrastructure development. Given this familiar dilemma, the public–private partnership (PPP), where the investor provides both the capital and management of a projects construction in return for the rights to extract operational revenues for a fixed concession period, has emerged as the ubiquitous means by which much of the world’s infrastructure is being procured since 1970s [4,5]. PPP infrastructure projects generally proceed in five phases: feasibility, procurement, construction, operation and transfer [6]. It is during the operation phase, however, which runs over the longest period, that the revenues needed to cover project costs and extract profits are generated. However, given this long operational period, during which PPPs are prone to encounter dynamic political, economic, and other environmental conditions, many uncertainties and risks enter into the operations, which can result in low operational efficiency and even project failure [7,8], especially in the current situation of COVID and the tense situation because of the war between Russia and Ukraine. For example, the British and French PPP Chunnel Project ultimately proved unprofitable, while the revenues of the Shandong China power generation PPP project collapsed due to changes in government credit terms.
Clearly, operational risk is critical to PPP projects, yet research on risk management tends to emphasize whole-of-life cycle [9], which has resulted in a lack of specific interest in finding ways to deal effectively with the specifics of operational risks, involving the identification of comprehensive operational risk factors and specific strategies, effective risk allocation, and response in accordance with risk management process [10]. In regards to risk identification, the list of risk factors for the whole-of-life cycle in PPP projects has been identified by a mature body of research [9,11]. However, importantly, this is not the case for operational risk factors in PPP projects, and these remain to be comprehensively identified, such as a lack of mention of government expropriation which is specific to the operation phase in a study of risk factors identified for PPPs [12]. As to risk allocation, most related studies take the risk-taking willingness, risk management ability, and risk tolerance into consideration [13,14], while regardless of the risk generator and the connection of risk generators and risk factors, especially in operational risk allocation. In fact, the operational risk generators have more control in dealing with risk factors created by themselves, which should be taken into account when allocating risks. Additionally, a review of related studies makes it apparent that PPP risk response is typically considered from a single perspective only, such as by the government, the investor, the financial institution, the insurer, and so on. However, effective operational risk management depends on all stakeholders taking on and sharing risk, as well as sharing appropriately in mitigating and responding to risk [6]. Of the stakeholders, the government and the investor are seen as both the major risk-takers and risk generators due to the parallel cooperative and competitive nature of their relationship. This conflicted relationship in which the “other party” is necessary to the success of the project, but whose actions may harm one’s position within the project has been described in principal–agent theory (PAT) as the principal–agent relationship [15]. Additionally, while other studies do specifically explore risk allocations between the government and investors in PPPs, these have not been conducted for operational risk [16,17]. In addition, the risk management strategies that have been proposed tend to emphasize the perspective of investors while underestimating the response of the government. Nevertheless, it is both the investor and government that are needed in the successful operation of PPP projects.
For these reasons, there needs to be a comprehensive consideration of the roles both need to play if there is to be an optimal outcome in the management of operational risk in PPP projects.
Simply, research into the risk management of the operation phase in PPP projects is limited, with apparent deficiencies in studies that do broach the subject. Therefore, given the importance of PPP operations, this study provides a review of extant literature in the field, drawn from the twelve top-tiered construction management journals, over the period 2005 to 2022. This study aims to achieve the following research goals:
(1)
Analyze the current status of research and identify specific deficiencies in PPP operational risk;
(2)
Develop a risk management framework for PPP operations that recognize risk generators.
This study provides researchers with a better theoretical understanding of the state-of-the-art operational risk management in PPP infrastructure projects, while also indicating research directions in the field. It also supports practitioners to more effectively engage with the challenges of managing PPP infrastructure operational risk.
The rest of this paper is organized as follows. Firstly, a review of the background of operational risk management in PPPs is offered. Next, the research methodology is detailed, followed by a quantitative and qualitative analysis of results. A discussion is provided. Finally, the conclusion is presented.

2. Background of Operational Risk Management in PPP Projects

Infrastructure is defined as transport (airports, roads, ports, railways), energy (electricity, natural gas), water and sewerage (water utilities, treatment plants), and information and communication technology [18]. PPP has been widely implemented across the infrastructure industry and especially in developing countries [19]. Successful PPP projects can bring significant benefits to the public sector, private sector, and consumers alike [20]. Additionally, PPP projects involve different stages, the key being financing, construction, operation, and transfer. Typically, PPP infrastructure projects are faced with long operation periods averaging 10–30 years, during which the revenue stream is generated in order to recoup costs and extract a reasonable rate of profit to justify the investment. However, due to the nature of a long operation phase, multiple project participants, and the complex and changeable external environment, various risks inevitably emerge over this period, threatening the viability and success of the project and ultimately eroding the income stream [21]. Clearly then, operational risk management is indispensable to a full understanding of PPP risk management studies.
In accordance with vulnerability theory, the risk is generally defined as the risk of direct or indirect loss due to internal processes, personnel, systems deficiencies, or external events [22,23]. This definition has also been adopted in regard to the operational risk in PPPs, originating from the internal system vulnerability of PPP projects and threats from the external environment. Yet even though the operational risk is considered essential to PPP success, most related studies simply focus on risk management for the whole-of-life cycle of PPP projects. This is problematic in leading to a reduction of the effectiveness of risk management at specific phases of PPP projects [24,25]. Indeed, awareness of this deficiency has led to a call for more emphasis to be allotted to risk management in the operation phase of PPP projects, which remains limited [26,27].
What limited studies there are on operational risk management tend to be conducted from a single parameter, such as from the perspective of investors or government [28,29]. In accordance with principal–agent theory (PAT) [30], and its application in risk management in PPPs [15,31,32], the project operation period can be regarded as the phase in which government entrusts the franchising authority of the PPP project to the investor while supporting the investor to achieve the government’s desired goals through a series of incentive and supervision measures. Hence, operational risk management is closely associated with both the investor and government managing their mutual relationship in combination with independent goals over the PPP operation. This cooperative as well as competitive interdependency is explained by PAT, which describes the rights, responsibilities, and interest distribution between the main project participants [33]. Viewed in this way, PAT can also indicate a risk management framework, in which risk sharing can be allocated optimally to the benefit of the PPP infrastructure project success, as well as to the satisfaction of all stakeholders.
Against this background, this study would systematically review the literature on operational risk in PPP on the basis of principal–agent theory with following the process of general risk management in PPP.

3. Methods

Literature reviews are a well-recognized, effective means to systematically grasp the extent of knowledge available within a specified field [10]. For this reason, the method is here employed to review the studies related to infrastructure operational risk. Target journals and relevant papers are selected as the first stage, followed by a quantitative analysis of the selected papers, with a qualitative analysis from perspectives of investors and governments following. See Figure 1.

3.1. The Materials

3.1.1. Data Acquisition

In order to retrieve a comprehensive range of studies related to operational risk management for PPPs, the Scopus database was employed. The efficacy of Scopus to cover a wide range of research collections is well documented [9]. The keywords of “operation risk”, “risk management”, “PPP”, “infrastructure” and “infrastructure operation risk” were used for the search. To improve relevance, the research fields were limited to: social science, economics, econometrics and finance, business, management and accounting, engineering, and decision science. The research period was set from 2005 to 2021. As of 31 December 2021, a total of 2176 records were retrieved.

3.1.2. Selection of Target Journals

Even though numerous papers were retrieved, not all the records were related to the topic. Screening papers from selected journals is necessary in order to exclude any irrelevant studies [9,34]. Hence, in order to obtain highly relevant papers from those initially obtained papers, manual screening was adopted. The screened criteria for articles are as follows:
  • Either the journal contains at least 0.37% of the total papers found in the initial research. Such benchmark percentages have been set by others. Hong, et al. [35] adopted a benchmark of 1% of the total papers in their study on partnering research in construction journals, while 0.25% was set in a study reviewing PPP literature [9].
  • Additionally, the main sources of research on PPP were recognized outlets such as: Journal of Construction Management and Engineering, Journal of Operations Management, Production and Operations Management, International Journal of Project Management, and Journal of infrastructure systems as identified by researchers in the field [36,37].
After the screening process, some 12 journals capturing 359 papers were selected. See Table 1.

3.1.3. Selection of Papers

Even within targeted journals and with keyword matches, certain papers were deemed through manual screening to be off-topic. Thus, from the original 359 papers, only a total of 62 highly relevant papers were selected for further analysis. The distribution of the papers can be seen in Table 1.

3.2. Techniques

Bibliometric analysis has been applied in many fields to determine the main research trends as well as the relationship between different demographics within a knowledge domain [38,39]. Network analysis is the principal technique used to conduct bibliometric analysis [40].
A wide range of tools is provided for bibliometric network analysis [10]. In accordance with similar studies, the tools of VOSviewer, CiteSpace, and Gephi were selected [10]. These tools can extract information from studies to uncover patterns by visualizing bibliometric networks [40,41,42]. Through the network map, clusters and their connections are presented, where highly centralized nodes indicate theme concentrations and research focus. Centrality is an important influencing factor for measuring network nodes [43], which reflects the number of node-to-node connections by calculating the degree of centrality without considering the direction and number of connections [44].
Measuring the centrality of nodes is the simplest and most reliable method for revealing important content and topics taking place within the network. Meanwhile, the size of the circles represents the word frequency while the connecting lines represent the individual and symbiotic relationships between them [45,46].
The degree center is calculated as shown in Equation (1):
D i = ∑ i = 1 n X ij
where D i is the degree centroid value of node i; X ij presents the sum of all existing connections between node i and node j (binary); n is the number of nodes in the network.

4. Quantitative Analysis

4.1. The Annual Publications on Operational Risk Management in PPP from 2005 to 2022

The distribution of publications between the years 2005 and 2022 is presented in Figure 2. The number of papers highly associated with operational risk on PPP have been on the rise since 2005. Though fluctuations are evident since 2010, the number of publications has been two or more per year. The peak year of the research period is 2019 with 10 papers, followed by 8 papers in 2015, and 6 papers in 2017. Overall, it can be observed that research interest in operational risk management in PPP infrastructure has been on the rise over the past 10 years, which parallels the rise in interest in PPP projects, evident especially in developing countries [47,48].

4.2. Major Research Themes on Operational Risk Management in PPP

The research theme network is achieved using the keyword co-occurrence network with a timeline in CiteSpace. See Figure 3. The evidence shows that the research on risk management in PPP infrastructure favors risk identification and assessment, project performance management, financing strategy, risk sharing, risk allocation, operational risk, and operation technology. While operational risk has been accorded attention since 2007, the research on specific operational risk management in PPP is relatively sparse and unsystematic. Therefore, it is safe to conclude that systematic operational risk management for PPP infrastructure ought to be prioritized in any further study.

4.3. Scientific Collaboration Networks in Operational Risk Management of PPPs

Collaboration in research is generally considered an effective means by which to obtain high-quality discovery while also reducing siloed research isolation [10]. Co-authorship analysis is used to develop a collaboration network for exploring authors’ collaboration. The authority score is applied to rank the authors by deploying hyperlink-induced topics, with higher authority scores presented by larger nodes and connection strength indicated by the thickness of connecting edges [49]. The co-author network is presented in Figure 4 and displays the collaboration clusters and the strength of association in operational risk management in PPP infrastructure projects. As can be seen, there are multiple unrelated small clusters, indicating that the cooperation between authors is mostly concentrated within small groups. Obviously, a wider range of research collaboration on operational risk management is needed.

4.4. Sector Analysis of Operational Risk Management in PPP Studies

Infrastructure encompasses a variety of sectors, including transport, energy, water and sewerage, and ICT. Certain studies have focused on the risk management of specific infrastructure sectors. On the other hand, there are also studies that approach the infrastructure industry in broad generalizations. The distribution of publications on risk management from the perspective of specific sectors and the general infrastructure industry can be seen in Figure 5. It can be observed that over half of the 62 publications approach risk management of infrastructure in general terms, regardless of the specifics of sector engagement. However, risk factors and their impacts can be various due to the different characteristics evident between sectors. It appears that further work across sector-specific applications of operational risk management in infrastructure is warranted.

5. Qualitative Analysis

According to traditional risk management theory, risk management usually involves the process of risk identification, assessment, allocation, and response, which is also widely adopted in the field of PPP [20]. Given this precedent, this study also follows this process in classifying the studies related to operational risk management. This section starts by identifying operational risk factors in PPP in respect of risk source. Next, an evaluation of operational risk is presented. On this basis, an operational risk allocation framework is developed both from the perspective of investors and governments, based on principal–agent theory (PAT). Finally, the existing body of operational risk management strategies is reviewed.

5.1. Identification of Operational Risk

When considering overall risks impacting infrastructure PPPs, it is evident that at least some of the identified risks can be expected to impact the operations phase of the project. Some studies identify risks from a whole-of-life cycle perspective, which will include operational risks. Examples of whole-of-project risks that impact operations include: inflation [50], changes in market demand [4], government instability [25,51], low maintenance frequency [12], and natural disasters [14], amongst others. There are also studies identifying operational risks from the perspective of specific PPP infrastructure sectors, such as operating cost overruns in the operation of China’s water PPP projects [50].
However, most of these identified risk factors do not significantly distinguish between the risk source and risk events for PPPs. Generally, a risk source is defined as an initial adverse change or accident that causes damage to the PPP project [52]. Risk events are the direct causes or conditions of accidents or losses [53], which may materialize as a consequence of one or more risk sources [54]. Risk result refers to the reduction of economic value or the destruction of physical projects that can be directly observed [52,55]. For example, operating cost overruns are considered one of the main operational risk factors in PPPs [50,56]. However, overruns are a risk result that may in fact be caused by many risk events, such as low technology, bad management, increase in material prices, as well as inflation [7]. Thus, it is necessary to distinguish between risk source and risk result if the operational risk is indeed to be effectively managed [57]. Given this understanding, this study identifies and classifies operational risk factors from the perspective of risk source. Moreover, in accordance with vulnerability theory in risk management, the risk is caused by a combination of the internal system vulnerability and external environment threats [56]. Thus, the operational risk factors are segregated into categories of economic, market, political, financial, financing, contract, technology, relationship, and natural environment. See Table 2.
Even so, major research deficiencies still exist in the field of operational risk in PPPs, as follows:
  • Systematic and comprehensive operational risk factors for PPP projects remain to be identified. Studies such as the existing ones tend to identify the risk factors from the perspective of the whole-of-life cycle of PPP projects [6], while specific research on operational risk remains wanting;
  • The link between the operational risk source and operational risk generator is not described or understood. This is despite risk sources being appreciated as necessary for effective risk management. In fact, most of the studies on risk source place emphasis on specific risk events while overlooking risk generators. Actually, the majority of the risk sources and events are closely associated with risk generators due to activities in the operation phase [58,59]. Hence, the identification of operational risk generators does concern the effective implementation of risk management in PPPs [57].
Table
Table 2. Identified operational risk factors for PPP infrastructure projects.
Table 2. Identified operational risk factors for PPP infrastructure projects.
NO.Operational Risk FactorsReference
123456789101112
Economic risks
1Inflation✓✓✓✓✓✓✓✓
2Interest rate changing✓✓✓✓ ✓✓✓✓✓
3Currency✓ ✓ ✓ ✓✓
Market risk
4Changes in market demand✓ ✓✓✓ ✓ ✓✓ ✓
5Faulty demand forecasting ✓ ✓
6Increased or unfair competition✓✓ ✓ ✓✓✓
7Lacking supporting infrastructure✓✓ ✓ ✓
8Inflexible PPP product or service prices ✓
9Rising raw material prices ✓ ✓✓ ✓
Political risk
10Government expropriation✓✓✓✓✓✓✓✓ ✓
11Government intervention✓✓✓✓✓ ✓ ✓
12Government corruption✓ ✓✓✓ ✓ ✓✓
13Government instability ✓ ✓✓✓✓ ✓
14Opaque policies ✓✓
15Terrorism ✓ ✓
16Public opposition✓ ✓✓✓✓✓✓ ✓ ✓
17Changes in laws and policies✓✓✓✓✓✓✓✓
18Imperfect supervision system✓ ✓✓ ✓ ✓✓✓
19Imperfect law and frameworks✓✓ ✓✓✓✓
20Tax increment✓ ✓ ✓✓ ✓
Financial risk
21Information asymmetry ✓
22Poor fund management ✓
23Low solvency ✓
Contract risk
26Conflicting or imperfect contract✓✓✓✓ ✓
27Misinterpretation of contract
Technology risk
28Low maintenance frequency ✓ ✓
29Technical obsolescence ✓ ✓✓ ✓✓
30Excessive maintenance ✓ ✓ ✓
31Lacking PPP experience✓ ✓ ✓ ✓ ✓✓✓
Relationship risk
32Poor staff management ✓
33Staff conflict during cooperation ✓ ✓✓✓
Natural environment risk
35Unforeseen weather/geotechnical conditions✓ ✓ ✓ ✓✓
36Environmental problems✓✓✓ ✓✓ ✓✓✓✓
37Natural disaster ✓ ✓ ✓
Note: 1—Chan, Lam, Wen, Ameyaw, Wang and Ke [50]; 2—Shrestha, Chan, Aibinu, Chen, Martek and Management [6]; 3—Chan, et al. [60]; 4—Ameyaw and Chan [61]; 5—Zhang, Tsai and Liao [14]; 6—Bing, Akintoye, Edwards and Hardcastle [56]; 7—Li, et al. [62]; 8—Ke, Wang and Chan [51]; 9—Yu, Darko, Chan, Chen and Bao [25]; 10—Song, Hu and Feng [4]; 11—Choi, et al. [63]; 12—Ameyaw and Chan [12].

5.2. Operational Risk Evaluation

Risk evaluation has been studied widely within PPP risk management. The majority of studies evaluate the risks in PPPs based on data collected from questionnaires [64], case studies [12,59], and interviews [50,65,66]. Mature evaluation techniques are applied to such collected data to calculate the likelihood and the severity of the risk, and then to rank the risk factors. These techniques include: the means score method [6], data envelopment analysis [16], fuzzy synthetic [25,57,67], and so on. However, certain insufficiencies underlying the evaluation of operational risk remain, as follows:
  • Given that research into risks in the operation phase of PPPs remains neglected, there is still a lack of specific studies on operational risk evaluation;
  • Those existing studies related to risk evaluation were carried out on the basis of subjective data collected from questionnaires and interviews. Hence, more objective collection methods for operational risk are needed in order to decrease evaluation error;
  • The impact of operational risk factors on the operation phase or the whole-of-life cycle project is given subjective scores for the PPP project as a whole. Thus, there is still a lack of study on the impacts of operational risk in terms of specific quantifiable loss amounts attributable to risk generators. Quantification is necessary if more effective operational risk management strategies are to be developed.

5.3. Allocation of Operational Risk

Risk allocation is a key step in PPP risk management [17]. Generally, the risk is allocated to the party best able to intervene in managing and controlling risk. It is they who should bear the consequences of risk as it is they who are in the strongest position to mitigate the risk, and must be incentivized to do so [68,69]. The willingness and ability of the relevant parties to bear the consequences are also taken into account in a risk-allocation model developed for the Tehran–Chalus Toll Road project, Iran [70]. Additionally, there are also studies proposing the risk allocation plan in accordance with the source, probability, severity, and impacts of risk factors [63,64]. Hence, risk-taking willingness, risk management ability, and risk tolerance are considered to be the main basis for risk allocation. Regardless of the basis for risk allocation, however, the allocation is generally partitioned between the government and the investor [13,14].
Generally, the government and investors are considered the main players in PPP projects, acting as clients (government) and agents (investor), and are the main parties taking risks [51]. This is the typical scenario described in principal–agent theory (PAT), which describes that not only will the government and investor share risks arising from the PPP proper, but their individual behaviors and activities will also create further risks for each other [14]. Risk mitigation, therefore, is also closely associated with the capability of controlling risks generated by other participants in PPPs [14]. Simply, the principal–agent relationship exists between the government and investors through the PPP operation phase [15,32]. Government and investors act therefore both as the main operational risk-takers as well as operational risk generators [54,71,72]. As a result, research deficiencies in operational risk allocation are evident as follows:
  • While studies do explore the risk allocation for the whole-of-life cycle of PPP projects, little has been completed focusing on specific operational risk allocations;
  • The specific impacts of operational risk on the various participants in the project are still unknown, which remain prerequisites for an efficient allocation of operational risk;
  • There is a lack of research on operational risk allocation that considers the connection between risk generators and risk factors. In fact, the operational risk generators have more control in dealing with risk factors created by themselves, and this ability should be taken into account when allocating operational risks to stakeholder parties.

5.4. Strategies for Managing Operational Risks

Given the limited research conducted on specific operational risk management, operational risk management strategies remain disparate and unsystematic. This study analyzes the specific operational risk management strategies identified from the studies on risk management from the perspective of the whole-of-life cycle of PPP projects, including the development, evaluation, and selection of strategies.
Current operational risk management strategies have developed from a range of perspectives. Some studies have proposed strategies to alleviate PPP risks in accordance with risk categories, such as market risk, political risk, financial risk, financing risk, natural risk, technology risk, and so on [63,73,74,75]. At the same time, other studies have proposed risk management strategies from the perspective of management procedures, which include: risk control, risk transfer, risk retention, risk avoidance, and risk utilization [76]. Moreover, some strategies have been developed with a theoretical lens in mind, which involves including resource capability theory that espouses increasing capability by increasing the resources needed to reduce the impacts of risks. A summary of the various management strategies drawn from the research on operational risk is summarized in Table 3.
As for the evaluation of operational risk management strategies, questionnaires are the method used in those few studies that exist. A majority of studies evaluate the effectiveness of strategies for different risk categories with one only considering specific risk factors [77,78]. The effectiveness and feasibility of the strategies have also been evaluated by category, i.e., risk elimination, risk transfer, and risk absorption [79].
The selection of operational risk management strategies is important for effective risk management. Many methods are employed for selecting strategies, such as the zonal-based method [80,81], the trade-off method [82], and the optimization model method [83]. With the application of these approaches, many factors are taken into consideration, including the interactions of risk events [84], the impacts of risk factors on project objectives [81], and the preferences of decision-makers [85]. In reference to existing studies, omissions with regard to the strategies are listed as follows:
  • There is still a lack of implementable strategies specifically relevant to operational risk management. Those that exist take the perspective of a whole-of-life cycle approach to PPP projects and are therefore broad and general in effect;
  • Most strategies are developed for the benefit of investors while overlooking the needs of the government. However, the government is clearly the main risk generator while also considered to have potent leverage over the risks it itself generates [14]. Hence, this deficiency calls for the development of operational risk management strategies with consideration to all risk generators;
  • Research on the evaluation of the effectiveness of strategies on operational risk management remains lacking. This is especially true when considering the impacts of every specific risk factor from the different perspectives of risk generators;
  • The selection of operational risk management strategies is based on the impacts of risk factors combined with the preference of decision makers. However, the capability of risk-takers is rarely considered, which needs to be considered if the operational risk is to be managed efficiently at the lowest cost.
Table
Table 3. Operational risk management strategies in PPP infrastructure projects.
Table 3. Operational risk management strategies in PPP infrastructure projects.
Strategies for Managing Operational RiskReference
1Create a good investment environment.Zhang, Tsai and Liao [14,34]
2Obtain suggestions from industry professionals and advisors.Choi, Chung and Lee [63,86]
3Establish a central coordinating PPP authority.Li and Wang [87]
4Formulate a favorable legal framework for local governments.Li and Wang [87], Brass and Sowell [88]
5Determine suitable and fair concession period.Chan, Lam, Wen, Ameyaw, Wang and Ke [50], Carbonara, et al. [89], Zou, et al. [90]
6Establish a price adjustment mechanism.Chan, Lam, Wen, Ameyaw, Wang and Ke [50], Carbonara, Costantino, Gunnigan and Pellegrino [89]
7Purchase political risk insurance.Jandhyala [91], Hashim, et al. [92]
8Develop long-term and appropriate financing strategy.Zhang, et al. [93], Soecipto and Verhoest [94]
9Select investor with experience in PPP projects and learn lessons from previous PPP projects.Wu, Song, Li and Xu [74], Weiermair, et al. [95]
10Estimate reasonably the operation and maintenance cost.Hastak and Baim [96]
11Adopt an appropriate sharing principle.Bing, Akintoye, Edwards and Hardcastle [56], Zou, Wang and Fang [90]
12Offer enough freedom for both partners and determine incentives and rules for collaboration.Rybnicek, et al. [97]
13Develop adequate revenue guarantee mechanism.Carbonara, Costantino, Gunnigan and Pellegrino [89]
14Embed renegotiation in the contract and establish the renegotiation framework in advance.Chan and Levitt [98], Zheng, et al. [99], Domingues and Zlatkovic [100]
15Provide transparent information amongst stakeholders.Ward and Development [101]
16Strengthen personnel management and optimize management structure.Kwofie, et al. [102]
17Increase penalties for breach of contract.Sachs, et al. [103]
18Establish an external exchange group.Auzzir, et al. [104]
19Select advanced production technologies, equipment and working procedures that are appropriate to market conditions.Ye-Lin and Management [105]
20Refine the project plan over time so that costs can be better estimated.Cantarelli, et al. [106]
21Improve the supervision system.Zhang, Tsai and Liao [14], Zhang, Chan, Feng, Duan and Ke [34], Domingues and Zlatkovic [100]
22Choose appropriate payment methods.Turner and Simister [107]
23Implement strict operation management and staff technical training.Ye-Lin and Management [105]
24Reserve funding for increased operating costs.Carbonara, Costantino, Gunnigan and Pellegrino [89], Pellegrino, et al. [108]
25Maintain good relations with local residents.Kwofie, Aigbavboa and Thwala [102]
26Maintain equipment with strict rules.Ye-Lin and Management [105]
27Separate ownership and management rights through entrusted agents.Shrestha, et al. [109]

5.5. Development of Operational Risk Management Framework

Based on the studies considered here, there is only a limited fledgling understanding of specific operational risk management in infrastructure PPPs. Of the studies conducted to date, operational risk identification pays less attention to risk generators, despite these being considered to have more control over risks than other non-risk generators [58,59]. Furthermore, the management strategies for operational risk have been principally proposed from the perspective of the investor, while the selection of the strategies rarely considers their own effectiveness in alleviating the impacts of operational risk and the capability of risk-takers. Hence, there is still a lack of a specific and systematic management framework for operational risk management in PPPs that accounts for risk generators. In order to address these research weaknesses, this study develops a systematic operational risk management flow from the perspective of risk generators in accordance with principal–agent theory (PAT), as shown in Figure 6. This proposal could provide a path for effective operational risk management. In the flow, PAT is employed to identify the main risk generators in the PPP operation phase, i.e., government and investor. On this basis, identified operational risk factors are categorized according to risk generators. Next, the risk factors generated by the government and investors are mainly allocated to a single risk generator which is considered to have more capability of controlling risk. However, the risk factors generated from other related parties are considered to be undertaken by both sides of government and investors with consideration of the capability and willingness of risk-takers. Furthermore, the management strategies for operational risk are developed based on the identified strategies in Table 3, and the effectiveness of different risk factors from the perspective of all risk generators is evaluated in line with the risk allocation. Finally, these strategies are selected for governments and investors alike, with consideration of their effectiveness.

6. Conclusions

PPP operations have attracted a lot of attention due to their novel ability to provide both infrastructure procurement and the necessary funding for the many infrastructure projects demanded by countries eager to find a catalyst for economic development. The catch for providers is that they must become investors with a financial stake in the viability of the project outcomes. As such, they act not only as builders and managers, but as investors, with project profitability linked to the reliability of the revenue stream generated over the lengthy concession operation period.
However, operational revenue can be disrupted by any number of foreseen and unforeseen risks eventuating over the operation period, especially faced with the global situation of COVID. Thus, operational risk management is integral to the success of PPP infrastructure projects. Yet, very little literature focused on the specific risk management of the PPP operation phase has been produced. As a result, this study aims to systematically review the current state of research on operational risk management in PPP infrastructure projects while also offering an effective operational risk management framework developed through both quantitative and qualitative analysis of related publications drawn from twelve target journals over the period from 2005 to 2022. Based on quantitative analysis, this study finds that the current body of research is scattered, piecemeal and unsystematic, and lacking in an overall sense of the underlying concerns that need to be addressed. Partly, this may be due to a lack of any wide-ranging research coordination or collaboration.
This study found 62 relevant studies which were selected for quantitative and qualitative analysis. Their strengths and weaknesses have been discussed and clear research gaps and opportunities identified. In conclusion, therefore, a future research agenda for operational risk management on PPP infrastructure projects are proposed as follows:
  • To publish a “special issue” on the operational risk management in PPP projects with a view to draw attention to this field and to facilitate the development of a systematic research regime for this topic;
  • To employ objective methods to identify and evaluate operational risk in PPP infrastructure projects with regard to specific loss value with consideration of the capability of risk generators;
  • To build connections between risk generators and the allocation of operational risks on the basis of principal–agent relationships in PPPs;
  • To develop an effective model for selecting mitigation strategies for operational risk management in PPP infrastructure projects from the comprehensive perspectives of risk generators.
This paper builds the connection between operational risk management in PPPs and risk generators based on principal–agent theory. Out of this, researchers will be directed to focus on specific operational risk management areas in an effort to contribute practically to the existing body of PPP knowledge. PPP practitioners will also benefit from this study by better understanding the management of operational risk through the lens of principal–agent relationships in PPPs.
This study does, however, have drawbacks. Firstly, all the studies evaluated arise from only twelve journals, meaning that not all highly valuable PPP risk-related publications may be captured. Secondly, the content analysis of studies provides merely an overview of operational risk management in the light of principal–agent theory, while other related theories in this field may provide an augmented perspective. Moreover, the differences and similarities of the operational risk management process in specific infrastructure sectors are not discussed, which remains to be explored for further research.

Author Contributions

Conceptualization, W.J.; methodology, J.J. and F.G.; software, W.J. and J.J.; validation, W.J. and Q.Y.; formal analysis, W.J. and J.J.; Investigation, Q.Y.; resources, W.J.; data curation, W.J.; writing—original draft preparation, W.J., Q.Y. and J.J.; writing—review and editing, I.M.; visualization, F.G.; supervision, W.J.; project administration, W.J.; funding acquisition, W.J. All authors have read and agreed to the published version of the manuscript.

Funding

The authors acknowledge research funding from the National Natural Science Foundation of China (72201185) and the Sichuan Federation of Social Science Associations (SC21C048).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Brueckner, M. Infrastructure and Economic Growth. J. Risk Financ. Manag. 2021, 14, 543. [Google Scholar] [CrossRef]
  2. Sun, Y.; Cui, Y. Analyzing urban infrastructure economic benefit using an integrated approach. Cities 2018, 79, 124–133. [Google Scholar] [CrossRef]
  3. Wang, Y.; Lee, H.W.; Tang, W.; Whittington, J.; Qiang, M. Structural Equation Modeling for the Determinants of International Infrastructure Investment: Evidence from Chinese Contractors. J. Manag. Eng. 2021, 37, 04021033. [Google Scholar] [CrossRef]
  4. Song, J.B.; Hu, Y.B.; Feng, Z. Factors Influencing Early Termination of PPP Projects in China. J. Manag. Eng. 2018, 34, 05017008. [Google Scholar] [CrossRef]
  5. Šovran, S.; Hadžić, M. Forms of international movement of capital with special emphasis on the ppp and concessions. Spatium 2016, 1, 55–60. [Google Scholar] [CrossRef]
  6. Shrestha, A.; Chan, T.-K.; Aibinu, A.A.; Chen, C.; Martek, I. Management. Risks in PPP water projects in China: Perspective of local governments. J. Constr. Eng. Manag. 2017, 143, 05017006. [Google Scholar] [CrossRef]
  7. Doloi, H. Understanding impacts of time and cost related construction risks on operational performance of PPP projects. Int. J. Strateg. Prop. Manag. 2012, 16, 316–337. [Google Scholar] [CrossRef]
  8. Allport, R.J.; Ward, S. Operational risk: The focus for major infrastructure? Proc. Inst. Civ. Eng. Manag. Procure. Law 2010, 163, 121–127. [Google Scholar] [CrossRef]
  9. Bao, F.; Chan, A.P.; Chen, C.; Darko, A. Review of Public–Private Partnership Literature from a Project Lifecycle Perspective. J. Infrastruct. Syst. 2018, 24, 04018008. [Google Scholar] [CrossRef]
  10. Jiang, W.; Martek, I.; Hosseini, M.R.; Chen, C. Political risk management of foreign direct investment in infrastructure projects: Bibliometric-qualitative analyses of research in developing countries. Eng. Constr. Archit. Manag. 2019, 28, 125–153. [Google Scholar] [CrossRef]
  11. Zhang, X.; Tariq, S. Failure mechanisms in international water PPP projects: A public sector perspective. J. Constr. Eng. Manag. 2020, 146, 04020055. [Google Scholar] [CrossRef]
  12. Ameyaw, E.E.; Chan, A.P.C. Identifying public-private partnership (PPP) risks in managing water supply projects in Ghana. J. Facil. Manag. 2013, 11, 152–182. [Google Scholar] [CrossRef]
  13. Ng, A.; Loosemore, M. Risk allocation in the private provision of public infrastructure. Int. J. Proj. Manag. 2007, 25, 66–76. [Google Scholar] [CrossRef]
  14. Zhang, Y.; Tsai, C.-H.; Liao, P.-C. Rethinking risk propagation mechanism in public–private partnership projects: Network perspective. J. Infrastruct. Syst. 2020, 26, 04020011. [Google Scholar] [CrossRef]
  15. Wang, Y.; Cui, P.; Liu, J. Analysis of the risk-sharing ratio in PPP projects based on government minimum revenue guarantees. Int. J. Proj. Manag. 2018, 36, 899–909. [Google Scholar] [CrossRef]
  16. Xu, L.; Liu, N.; Zhang, S.; Qiu, H.; Chen, L.; Wang, Z. Efficiency and determinants analysis of Chinese infrastructure PPP projects in the construction and operation stages. Int. J. Strateg. Prop. Manag. 2019, 23, 156–170. [Google Scholar] [CrossRef] [Green Version]
  17. Wang, Y.; Liu, J. Evaluation of the excess revenue sharing ratio in PPP projects using principal–agent models. Int. J. Proj. Manag. 2015, 33, 1317–1324. [Google Scholar] [CrossRef]
  18. World Bank. Private Participation in Infrastructure Database. 2018. Available online: https://ppi.worldbank.org/ (accessed on 20 December 2019).
  19. Cheng, Z.; Wang, H.; Xiong, W.; Zhu, D.; Cheng, L. Public–private partnership as a driver of sustainable development: Toward a conceptual framework of sustainability-oriented PPP. Environ. Dev. Sustain. 2021, 23, 1043–1063. [Google Scholar] [CrossRef]
  20. Yuan, J.; Guang, M.; Wang, X.; Li, Q.; Skibniewski, M.J. Quantitative SWOT analysis of public housing delivery by public–private partnerships in China based on the perspective of the public sector. J. Manag. Eng. 2012, 28, 407–420. [Google Scholar] [CrossRef]
  21. Hu, Z.; Li, Q.; Liu, T.; Wang, L.; Cheng, Z. Government equity investment, effective communication and public private partnership (PPP) performance: Evidence from China. Eng. Constr. Archit. Manag. 2020, 28, 2811–2827. [Google Scholar] [CrossRef]
  22. Frachot, A.; Georges, P.; Roncalli, T. Loss Distribution Approach for Operational Risk. Available online: http://dx.doi.org/10.2139/ssrn.1032523 (accessed on 20 December 2019).
  23. Moosa, I.A. Operational risk: A survey. Financ. Mark. Inst. Instrum. 2007, 16, 167–200. [Google Scholar] [CrossRef]
  24. Bao, F.; Chen, C.; Chan, A.P.; Martek, I.; Shrestha, A. Dynamic framework transfer model for public–private partnerships: Lessons from a China water sector case study. Eng. Constr. Archit. Manag. 2019, 26, 1218–1239. [Google Scholar] [CrossRef]
  25. Yu, Y.; Darko, A.; Chan, A.P.C.; Chen, C.; Bao, F.Y. Evaluation and Ranking of Risk Factors in Transnational Public-Private Partnerships Projects: Case Study Based on the Intuitionistic Fuzzy Analytic Hierarchy Process. J. Infrastruct. Syst. 2018, 24, 04018028. [Google Scholar] [CrossRef]
  26. Jarrow, R.A. Operational risk. J. Bank. Financ. 2008, 32, 870–879. [Google Scholar] [CrossRef]
  27. Bao, F.; Martek, I.; Chen, C.; Wu, Q.; Chan, A.P. Critical Risks Inherent to the Transfer Phase of Public–Private Partnership Water Projects in China. J. Manag. Eng. 2022, 38, 04022006. [Google Scholar] [CrossRef]
  28. Hwang, H.; Kim, H. Demand risk transfer and government’s cost efficiency: Focusing on Korean waste treatment PPP cases. Waste Manag. 2022, 137, 31–38. [Google Scholar] [CrossRef]
  29. Jin, N.; Yang, N.; Gao, J.J.S.S. The risk analysis of the PFI model in the project regional investment. Soft Sci. 2007, 21, 10–13. [Google Scholar]
  30. Laffont, J.-J.; Martimort, D. The Theory of Incentives; Princeton University Press: Princeton, NJ, USA, 2009. [Google Scholar]
  31. Schmidt, E.K. Research management and policy: Incentives and obstacles to a better public-private interaction. Int. J. Public Sect. Manag. 2008, 21, 623–636. [Google Scholar] [CrossRef]
  32. Shrestha, A.; Aibinu, A.; Chan, T.; Chen, C.J.W.R.M.V. Risk allocation in public private partnerships in China’s water projects: A principal agent approach. In Water Resources Management VII; Brebbia, C.A., Ed.; WIT Press: South Hampton, NH, USA, 2013; Volume 171, pp. 85–96. [Google Scholar]
  33. Paez-Perez, D.; Sanchez-Silva, M. A dynamic principal-agent framework for modeling the performance of infrastructure. Eur. J. Oper. Res. 2016, 254, 576–594. [Google Scholar] [CrossRef]
  34. Zhang, S.; Chan, A.P.C.; Feng, Y.B.; Duan, H.X.; Ke, Y.J. Critical review on PPP Research-A search from the Chinese and International Journals. Int. J. Proj. Manag. 2016, 34, 597–612. [Google Scholar] [CrossRef]
  35. Hong, Y.; Chan, D.W.; Chan, A.P.; Yeung, J.F. Critical analysis of partnering research trend in construction journals. J. Manag. Eng. 2012, 28, 82–95. [Google Scholar] [CrossRef]
  36. Ke, Y.; Wang, S.; Chan, A.P.; Cheung, E. Research trend of public-private partnership in construction journals. J. Constr. Eng. Manag. 2009, 135, 1076–1086. [Google Scholar] [CrossRef]
  37. Cui, C.; Liu, Y.; Hope, A.; Wang, J. Review of studies on the public–private partnerships (PPP) for infrastructure projects. Int. J. Proj. Manag. 2018, 36, 773–794. [Google Scholar] [CrossRef]
  38. Bonilla, C.A.; Merigó, J.M.; Torres-Abad, C. Economics in Latin America: A bibliometric analysis. Scientometrics 2015, 105, 1239–1252. [Google Scholar] [CrossRef]
  39. Barth, M.; Haustein, S.; Scheidt, B. The life sciences in German-Chinese cooperation: An institutional-level co-publication analysis. Scientometrics 2014, 98, 99–117. [Google Scholar] [CrossRef] [Green Version]
  40. Wang, W.; Lu, C. Visualization analysis of big data research based on Citespace. Soft Comput. 2020, 24, 8173–8186. [Google Scholar] [CrossRef]
  41. Van Eck, N.J.; Waltman, L. Text mining and visualization using VOS viewer. arXiv 2011, arXiv:1109.2058. [Google Scholar]
  42. Hosseini, M.R.; Maghrebi, M.; Akbarnezhad, A.; Martek, I.; Arashpour, M. Analysis of citation networks in building information modeling research. J. Constr. Eng. Manag. 2018, 144, 04018064. [Google Scholar] [CrossRef]
  43. Yang, Y.; Qu, G.; Hua, L. Research Status, Hotspots, and Evolution Trend of Decision-Making in Marine Management Using VOSviewer and CiteSpace. Math. Probl. Eng. 2022, 2022, 8283417. [Google Scholar] [CrossRef]
  44. Hennig, M.; Brandes, U.; Pfeffer, J.; Mergel, I. Studying Social Networks: A Guide to Empirical Research; Campus Verlag: Frankfurt, Germany, 2012. [Google Scholar]
  45. Grandjean, M. Gephi: Introduction to Network Analysis and Visualization. 2015. Available online: http://www.martingrandjean.ch/gephi-introduction/ (accessed on 20 December 2019).
  46. Li, J.; Mao, Y.; Ouyang, J.; Zheng, S. A Review of Urban Microclimate Research Based on CiteSpace and VOSviewer Analysis. Int. J. Environ. Res. Public Health 2022, 19, 4741. [Google Scholar] [CrossRef]
  47. Osei-Kyei, R.; Chan, A.P. Review of studies on the Critical Success Factors for Public–Private Partnership (PPP) projects from 1990 to 2013. Int. J. Proj. Manag. 2015, 33, 1335–1346. [Google Scholar] [CrossRef]
  48. Yu, Y.; Chan, A.P.; Chen, C.; Darko, A. Critical risk factors of transnational public–private partnership projects: Literature review. J. Infrastruct. Syst. 2018, 24, 04017042. [Google Scholar] [CrossRef]
  49. Cherven, K. Mastering Gephi Network Visualization; Packt Publishing Ltd.: Birmingham, UK, 2015. [Google Scholar]
  50. Chan, A.P.; Lam, P.T.; Wen, Y.; Ameyaw, E.E.; Wang, S.; Ke, Y. Cross-sectional analysis of critical risk factors for PPP water projects in China. J. Infrastruct. Syst. 2015, 21, 04014031. [Google Scholar] [CrossRef]
  51. Ke, Y.; Wang, S.; Chan, A.P. Risk allocation in public-private partnership infrastructure projects: Comparative study. J. Infrastruct. Syst. 2010, 16, 343–351. [Google Scholar] [CrossRef]
  52. Yuan, J.; Li, X.; Chen, K.; Skibniewski, M.J. Modelling residual value risk through ontology to address vulnerability of PPP project system. Adv. Eng. Inform. 2018, 38, 776–793. [Google Scholar] [CrossRef]
  53. Zhang, H. A redefinition of the project risk process: Using vulnerability to open up the event-consequence link. Int. J. Proj. Manag. 2007, 25, 694–701. [Google Scholar] [CrossRef]
  54. Xu, Y.L.; Yang, Y.F.; Chan, A.P.C.; Yeung, J.F.Y.; Cheng, H. Identification and Allocation of Risks Associated with PPP Water Projects in China. Int. J. Strateg. Prop. Manag. 2011, 15, 275–294. [Google Scholar] [CrossRef] [Green Version]
  55. Mehr, R.; Cammack, E. Principles of Insurance. J. Insur. 1980, 13, 128–129. [Google Scholar] [CrossRef]
  56. Bing, L.; Akintoye, A.; Edwards, P.J.; Hardcastle, C. The allocation of risk in PPP/PFI construction projects in the UK. Int. J. Proj. Manag. 2005, 23, 25–35. [Google Scholar] [CrossRef]
  57. Xiong, W.; Yuan, J.-F.; Li, Q.; Skibniewski, M.J. Management. Performance objective-based dynamic adjustment model to balance the stakeholders’ satisfaction in PPP projects. J. Civ. Eng. Manag. 2015, 21, 539–547. [Google Scholar] [CrossRef]
  58. Yuan, J.; Skibniewski, M.J.; Li, Q.; Zheng, L. Performance objectives selection model in public-private partnership projects based on the perspective of stakeholders. J. Manag. Eng. 2010, 26, 89–104. [Google Scholar] [CrossRef]
  59. Yang, L.; Lou, J.; Zhao, X. Risk response of complex projects: Risk association network method. J. Manag. Eng. 2021, 37, 05021004. [Google Scholar] [CrossRef]
  60. Chan, A.P.C.; Yeung, J.F.Y.; Yu, C.C.P.; Wang, S.Q.; Ke, Y.J. Empirical Study of Risk Assessment and Allocation of Public-Private Partnership Projects in China. J. Manag. Eng. 2011, 27, 136–148. [Google Scholar] [CrossRef] [Green Version]
  61. Ameyaw, E.E.; Chan, A.P. Evaluating key risk factors for PPP water projects in Ghana: A Delphi study. J. Facil. Manag. 2015, 13, 133–155. [Google Scholar] [CrossRef]
  62. Li, Y.; Wang, X.; Wang, Y. Management. Using bargaining game theory for risk allocation of public-private partnership projects: Insights from different alternating offer sequences of participants. J. Constr. Eng. Manag. 2017, 143, 04016102. [Google Scholar] [CrossRef]
  63. Choi, J.-H.; Chung, J.; Lee, D.-J. Risk perception analysis: Participation in China’s water PPP market. Int. J. Proj. Manag. 2010, 28, 580–592. [Google Scholar] [CrossRef]
  64. El-Sayegh, S.M.; Mansour, M.H. Risk assessment and allocation in highway construction projects in the UAE. J. Manag. Eng. 2015, 31, 04015004. [Google Scholar] [CrossRef]
  65. Cooper, D.F.; Grey, S.; Raymond, G.; Walker, P. Project Risk Management Guidelines: Managing Risk in Large Projects and Complex Procurements; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2021. [Google Scholar]
  66. Liu, T.; Wang, Y.; Wilkinson, S. Identifying critical factors affecting the effectiveness and efficiency of tendering processes in Public–Private Partnerships (PPPs): A comparative analysis of Australia and China. Int. J. Proj. Manag. 2016, 34, 701–716. [Google Scholar] [CrossRef]
  67. Osei-Kyei, R.; Chan, A.P.; Javed, A.A.; Ameyaw, E.E. Critical success criteria for public-private partnership projects: International experts’ opinion. Int. J. Strateg. Prop. Manag. 2017, 21, 87–100. [Google Scholar] [CrossRef] [Green Version]
  68. Daube, D.; Vollrath, S.; Alfen, H.W. A comparison of Project Finance and the Forfeiting Model as financing forms for PPP projects in Germany. Int. J. Proj. Manag. 2008, 26, 376–387. [Google Scholar] [CrossRef]
  69. Lam, K.C.; Wang, D.; Lee, P.T.; Tsang, Y.T. Modelling risk allocation decision in construction contracts. Int. J. Proj. Manag. 2007, 25, 485–493. [Google Scholar] [CrossRef]
  70. Heravi, G.; Hajihosseini, Z. Risk allocation in public–private partnership infrastructure projects in developing countries: Case study of the Tehran–Chalus toll road. J. Infrastruct. Syst. 2012, 18, 210–217. [Google Scholar] [CrossRef]
  71. Medda, F. A game theory approach for the allocation of risks in transport public private partnerships. Int. J. Proj. Manag. 2007, 25, 213–218. [Google Scholar] [CrossRef]
  72. Zhou, Y.; Liu, J. Influence of government credit risk on PPP projects in operation stage. Int. J. Strateg. Prop. Manag. 2021, 25, 216–227. [Google Scholar] [CrossRef]
  73. Müllner, J. From uncertainty to risk—A risk management framework for market entry. J. World Bus. 2016, 51, 800–814. [Google Scholar] [CrossRef]
  74. Wu, Y.; Song, Z.; Li, L.; Xu, R. Risk management of public-private partnership charging infrastructure projects in China based on a three-dimension framework. Energy 2018, 165, 1089–1101. [Google Scholar] [CrossRef]
  75. Barker, K.; Haimes, Y.Y. Assessing uncertainty in extreme events: Applications to risk-based decision making in interdependent infrastructure sectors. Reliab. Eng. Syst. Saf. 2009, 94, 819–829. [Google Scholar] [CrossRef]
  76. Xiong, W.; Zhao, X.; Yuan, J.-F.; Luo, S. Ex post risk management in public-private partnership infrastructure projects. Proj. Manag. J. 2017, 48, 76–89. [Google Scholar] [CrossRef]
  77. Wang, S.Q.; Dulaimi, M.F.; Aguria, M.Y. Risk management framework for construction projects in developing countries. Constr. Manag. Econ. 2004, 22, 237–252. [Google Scholar] [CrossRef]
  78. Noorzai, E. Public–Private Partnership Risks in Conflict Zones and Solutions: Case Study for Afghanistan. J. Infrastruct. Syst. 2021, 27, 05021001. [Google Scholar] [CrossRef]
  79. Trangkanont, S.; Charoenngam, C. Private partner’s risk response in PPP low-cost housing projects. Prop. Manage. 2014, 32, 67–94. [Google Scholar] [CrossRef]
  80. Datta, S.; Mukherjee, S. Developing a risk management matrix for effective project planning—An empirical study. Proj. Manag. J. 2001, 32, 45–57. [Google Scholar] [CrossRef]
  81. Wu, D.; Li, J.; Xia, T.; Bao, C.; Zhao, Y.; Dai, Q. A multiobjective optimization method considering process risk correlation for project risk response planning. Inf. Sci. 2018, 467, 282–295. [Google Scholar] [CrossRef]
  82. Zhang, Y.; Fan, Z.-P. An optimization method for selecting project risk response strategies. Int. J. Proj. Manag. 2014, 32, 412–422. [Google Scholar] [CrossRef]
  83. Fan, M.; Lin, N.-P.; Sheu, C. Choosing a project risk-handling strategy: An analytical model. Int. J. Prod. Econ. 2008, 112, 700–713. [Google Scholar] [CrossRef]
  84. Shoar, S.; Nazari, A. An optimization framework for risk response actions selection using hybrid ACO and FTOPSIS. Sci. Iran. 2019, 26, 1763–1777. [Google Scholar] [CrossRef] [Green Version]
  85. Yan, P.; Liu, J.; Zhao, X.; Skitmore, M. Risk response incorporating risk preferences in international construction projects. Eng. Constr. Archit. Manag. 2021. [Google Scholar] [CrossRef]
  86. Awodele, O.A. Framework for Managing Risk in Privately Financed Market Projects in Nigeria. Ph.D. Thesis, Heriot-Watt University, Edinburgh, UK, 2012. [Google Scholar]
  87. Li, Y.; Wang, X. Risk assessment for public–private partnership projects: Using a fuzzy analytic hierarchical process method and expert opinion in China. J. Risk Res. 2018, 21, 952–973. [Google Scholar] [CrossRef]
  88. Brass, I.; Sowell, J.H. Adaptive governance for the Internet of Things: Coping with emerging security risks. Regul. Gov. 2021, 15, 1092–1110. [Google Scholar] [CrossRef]
  89. Carbonara, N.; Costantino, N.; Gunnigan, L.; Pellegrino, R. Risk management in motorway PPP projects: Empirical-based guidelines. Transp. Rev. 2015, 35, 162–182. [Google Scholar] [CrossRef] [Green Version]
  90. Zou, P.X.; Wang, S.; Fang, D. A life-cycle risk management framework for PPP infrastructure projects. J. Financ. Manag. Prop. Constr. 2008, 13, 123–142. [Google Scholar] [CrossRef]
  91. Jandhyala, S. International Organizations and Political Risk—The Case of Multilateral Development Banks in Infrastructure Projects. 2016. Available online: https://ppi.worldbank.org/content/dam/PPI/resources/ppi_publication/theme/The-case-of-multilateral-development-banks-by-Jandhyala2016.pdf (accessed on 20 December 2019).
  92. Hashim, H.A.; Sapri, M.; Low, S.-T. Public private partnership (PPP) facilities management for healthcare services in Malaysia: The challenges of implementation. J. Facil. Manag. 2016, 14, 350–362. [Google Scholar] [CrossRef]
  93. Zhang, Y.Q.; Hou, W.H.; Qian, Y. A Dynamic Simulation Model for Financing Strategy Management of Infrastructure PPP Projects. Int. J. Strateg. Prop. Manag. 2020, 24, 441–455. [Google Scholar] [CrossRef]
  94. Soecipto, R.M.; Verhoest, K. Contract stability in European road infrastructure PPPs: How does governmental PPP support contribute to preventing contract renegotiation? Public Manag. Rev. 2018, 20, 1145–1164. [Google Scholar] [CrossRef]
  95. Weiermair, K.; Peters, M.; Frehse, J. Success factors for public private partnership: Cases in alpine tourism development. J. Serv. Res. 2008, 7–21. [Google Scholar]
  96. Hastak, M.; Baim, E. Risk factors affecting management and maintenance cost of urban infrastructure. J. Infrastruct. Syst. 2001, 7, 67–76. [Google Scholar] [CrossRef]
  97. Rybnicek, R.; Plakolm, J.; Baumgartner, L. Risks in public–private partnerships: A systematic literature review of risk factors, their impact and risk mitigation strategies. Public Perform. Manag. Rev. 2020, 43, 1174–1208. [Google Scholar] [CrossRef] [Green Version]
  98. Chan, H.; Levitt, R.E. To talk or to fight? Effects of strategic, cultural, and institutional factors on renegotiation approaches in public–private concessions. Glob. Proj. Inst. Political Chall. 2011, 310–348. [Google Scholar]
  99. Zheng, J.; Roehrich, J.K.; Lewis, M.A. The dynamics of contractual and relational governance: Evidence from long-term public–private procurement arrangements. J. Purch. Supply Manag. 2008, 14, 43–54. [Google Scholar] [CrossRef] [Green Version]
  100. Domingues, S.; Zlatkovic, D. Renegotiating ppp contracts: Reinforcing the ‘p’ in partnership. Transp. Rev. 2015, 35, 204–225. [Google Scholar] [CrossRef]
  101. Ward, E.J. Mega infrastructure and strategic risk mitigation: Planning, management and outcomes. J. Mega Infrastruct. Sustain. Dev. 2022, 2, 5–31. [Google Scholar] [CrossRef]
  102. Kwofie, T.E.; Aigbavboa, C.O.; Thwala, W.D. Communication performance challenges in PPP projects: Cases of Ghana and South Africa. Built Environ. Proj. Asset Manag. 2019, 9, 628–641. [Google Scholar] [CrossRef]
  103. Sachs, T.; Tiong, R.; Wang, S.Q. Analysis of political risks and opportunities in public private partnerships (PPP) in China and selected Asian countries: Survey results. Chin. Manag. Stud. 2007, 1, 126–148. [Google Scholar] [CrossRef]
  104. Auzzir, Z.A.; Haigh, R.P.; Amaratunga, D. Public-private partnerships (PPP) in disaster management in developing countries: A conceptual framework. Procedia Econ. Financ. 2014, 18, 807–814. [Google Scholar] [CrossRef]
  105. Ye-Lin, X.U. Identifying Risk Response Measures for PPP Projects in China. D.T.O.E. Bus. Manag. 2017, 2475–8868. [Google Scholar]
  106. Cantarelli, C.C.; Molin, E.J.E.; van Wee, B.; Flyvbjerg, B. Characteristics of cost overruns for Dutch transport infrastructure projects and the importance of the decision to build and project phases. Transp. Policy 2012, 22, 49–56. [Google Scholar] [CrossRef] [Green Version]
  107. Turner, J.R.; Simister, S. Project contract management and a theory of organization. Int. J. Proj. Manag. 2001, 19, 457–464. [Google Scholar] [CrossRef] [Green Version]
  108. Pellegrino, R.; Vajdic, N.; Carbonara, N. Real option theory for risk mitigation in transport PPPs. Built Environ. Proj. Asset Manag. 2013, 3, 199–213. [Google Scholar] [CrossRef]
  109. Shrestha, A.; Tamošaitienė, J.; Martek, I.; Hosseini, M.R.; Edwards, D.J. A principal-agent theory perspective on PPP risk allocation. Sustainability 2019, 11, 6455. [Google Scholar] [CrossRef]
Buildings 12 01905 g001 550
Figure 1. Research route.
Figure 1. Research route.
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Buildings 12 01905 g002 550
Figure 2. The annual number of publications on PPP operational risk from 2001 to 2022.
Figure 2. The annual number of publications on PPP operational risk from 2001 to 2022.
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Buildings 12 01905 g003 550
Figure 3. Main research areas in operational risk of infrastructure projects (co-occurrence network of keywords).
Figure 3. Main research areas in operational risk of infrastructure projects (co-occurrence network of keywords).
Buildings 12 01905 g003
Buildings 12 01905 g004 550
Figure 4. Collaboration network of authors.
Figure 4. Collaboration network of authors.
Buildings 12 01905 g004
Buildings 12 01905 g005 550
Figure 5. The distribution of publications by infrastructure sectors.
Figure 5. The distribution of publications by infrastructure sectors.
Buildings 12 01905 g005
Buildings 12 01905 g006 550
Figure 6. Operational risk management flow.
Figure 6. Operational risk management flow.
Buildings 12 01905 g006
Table
Table 1. Selected journals and papers for PPP operational risk management.
Table 1. Selected journals and papers for PPP operational risk management.
Journal NameNumber of Papers Obtained by Limiting KeywordsNumber of Papers Related to the Topic
International Journal of Project Management6413
Journal of Infrastructure Systems369
Journal of Management in Engineering158
International Journal of Strategic Property Management276
Journal of Facilities Management275
Journal of Construction Engineering and Management595
European Journal of Operational Research154
Risk Analysis234
Production and Operations Management142
Journal of Civil Engineering and Management592
Journal of Operations Management122
Engineering, Construction and Architectural Management82
Total35962
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MDPI and ACS Style

Jiang, W.; Yang, Q.; Jiang, J.; Martek, I.; Gao, F. Operational Risk Management of Public–Private Partnership Infrastructure Projects: A Bibliometric Literature Review. Buildings 2022, 12, 1905. https://doi.org/10.3390/buildings12111905

AMA Style

Jiang W, Yang Q, Jiang J, Martek I, Gao F. Operational Risk Management of Public–Private Partnership Infrastructure Projects: A Bibliometric Literature Review. Buildings. 2022; 12(11):1905. https://doi.org/10.3390/buildings12111905

Chicago/Turabian Style

Jiang, Weiling, Qianying Yang, Jie Jiang, Igor Martek, and Fanjie Gao. 2022. "Operational Risk Management of Public–Private Partnership Infrastructure Projects: A Bibliometric Literature Review" Buildings 12, no. 11: 1905. https://doi.org/10.3390/buildings12111905

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