The Governance of PPP Project Resilience: A Hybrid DMATEL-ISM Approach

Abstract

Considering the inherent characteristics of long-term agreements, public–private partnership (PPP) projects are confronted with diverse uncertainties and external challenges. However, existing research has devoted limited attention to the resilience of PPP projects. This study seeks to identify governance factors influencing PPP project resilience and analyze the interconnections among these factors in fostering such resilience. A governance framework for PPP project resilience is proposed, comprising thirteen governance factors across four dimensions: institutional, organizational, contractual, and managerial factors. The interpretive structural modeling (ISM) and decision-making trial and evaluation laboratory (DEMATEL) techniques are adopted to explore the hierarchical relationships and interactive mechanisms among these governance factors in a systematic view. The findings reveal that strategic alliances, risk allocation and transfer, flexible contracting, and long-term relationship management represent core governance factors critical to enhancing project resilience. Institutional factors are identified as the most foundational determinants within the governance system, while contractual and managerial factors act as mediating elements facilitating the translation of institutional foundations into operational resilience. This study deepened the understanding of the practitioners with regard to the key governance factors and their inter-relationships, which can help systematically enhance the resilience of PPP projects.

1. Introduction

Public–private partnerships (PPPs) have received considerable attention over the past 40 years as an innovative approach to involving private sector resources in public infrastructure investment and delivering sustainable public services [1]. PPPs enhance innovation through the private sector’s flexibility and technological capabilities, resulting in improved service quality and cost-effectiveness as compared to traditional procurement invested by public spending [2]. The innovative arrangements in the PPP model have completely changed public administration and project management in many countries [3]. Hence, PPP has been used to improve the efficiency of project financing and the long-term performance of public facilities, serving as an alternative to traditional infrastructure procurement [4,5].

Due to the long life cycle and extended operational services, PPP projects face more significant uncertainties, such as complex relationships between external stakeholders, information asymmetry, and extensive risk [6]. According to World Bank data, from 1990 to 2023, 2500 PPP projects were terminated and cancelled worldwide [7]. The increasingly uncertain environments pose significant challenges for PPP project control and risk management methods, necessitating more flexible, adaptable, and forward-thinking strategies [6,8]. Project resilience in the PPP context refers to a project’s ability to anticipate, adapt, and recover in the face of unexpected challenges. Therefore, identifying and evaluating the governance factors for PPP project resilience is essential for ensuring long-term success and sustainable operations.

The current literature is abundant with studies that focus on identifying uncertainties in governance factors of PPPs. These studies have highlighted various governance strategies, such as flexible contracts, negotiations, partnerships, long-term trust, and risk allocation [9,10,11]. However, few studies have investigated the relationships between these governance factors of PPP project resilience. Moreover, merely listing governance factors without embedding them in a coherent theoretical framework diminishes the ability to fully explain how they influence PPP project resilience. Prior studies only focus on descriptive qualitative research and lack investigations into the interdependencies and transmission patterns among governance factors [12]. This gap in knowledge results in a fragmented comprehension of governance factors for PPP project resilience, and it is difficult to guide the execution of these governance factors.

To fill the research gap, we propose a framework and a quantitative evaluation method to enhance the understanding of governance factors for PPP project resilience. The governance theory provides a proper theoretical perspective to establish such a framework. Specifically, four dimensions of the PPP governance framework are proposed according to Xiong et al. [13], and thirteen governance factors are summarized based on the literature review. This study employed a combination of Interpretive Structural Modelling (ISM) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods to enhance the assessment of governance factors for PPP project resilience. The approach gathers collective expert knowledge to visualize the structure of complicated casual relationships among different governance factors [12,14]. This study makes significant additions to the field of PPP in three aspects. First, this research examines governance factors for PPP project resilience, aiming to develop a unified framework for enhancing the understanding of PPP project resilience. Second, this study identifies and categorizes the key governance factors of PPP project resilience, offering a structured framework for understanding their interrelationships. Third, by applying a combined DEMATEL and ISM approach, this study explores the interrelationships describing their governance factors. These findings provide an insight for project managers and policymakers to enhance resilience in PPP projects.

2. Literature Review

2.1. Project Resilience in PPPs

Project resilience has garnered increasing attention in recent years, reflecting the need for projects to not only withstand disruptions but also adapt and thrive in the uncertainties [15]. Some researchers have systematically examined multilevel determinants of resilience, with particular emphasis on project governance or across organizational boundary activities. Liu and Wang [16] demonstrated that emerging digital technologies positively influence construction project resilience across the dimensions of anticipation, coping, and adaptation capabilities. Shen et al. [17] also argued that partnership can enhance a project’s capacity to adapt and recover from unexpected challenges. Wang et al. [18] emphasized the need for contractual governance and examined the mediating role of resource reconfiguration based on dynamic capability theory. Han and Bogus [19] explored the resilience of highway project delivery, identifying key criteria for resistance, recovery, and adaptation phases using principal component analysis, and emphasized the need for resilience assessment during planning, design, and construction. Zou et al. [20] developed a resilience measurement model for project portfolio networks using complex network theory to evaluate and enhance project portfolio resilience, ultimately improving the success probability of the entire network.

PPP projects provide a unique context for resilience research due to their long-term cooperation and high-risk characteristics [21]. Tariq and Zhang [22] identified 60 failure drivers of water PPP projects and evaluated their relative importance. Zhang and Soomro [23] developed a PPP failure mechanism prediction model to describe the vulnerability of transportation PPP projects. Sun et al. [24] identified 19 key influencing factors for early termination of PPP projects based on grounded theory and analyzed the hierarchical structure among these influencing factors using the ISM model. Song et al. [9] identified 11 early termination factors affecting PPP projects based on 23 Chinese PPP projects. Liu et al. [12] developed a collaborative governance framework to systematically investigate the obstacles to the sustainable operation of PPP projects. However, existing studies focus primarily on failure factors, with no clear framework for PPP project resilience. Thus, a theoretical framework is needed to determine governance factors of PPP resilience.

2.2. Governance Factors for PPP Project Resilience

To explore PPP project resilience, it is essential to distinguish between traditional risk management and resilience management in the PPP context. Resilience management recognizes that risks may be ambiguous or unforeseen [25]. Current studies on PPP project resilience primarily concentrate on managing uncertainty. Integrating governance strategies to manage these uncertainties is essential to the governance framework for PPP project resilience. Indeed, project governance is often a critical process for managing these emerging uncertainties [26]. Prior studies have highlighted the importance of governance mechanisms in PPP projects. The governance in PPPs plays a critical role in aligning the interests of public and private partners, managing risks, and ensuring the long-term success of the project [6]. Scholars have identified various governance factors that influence the uncertainty of PPP projects, including risk allocation, contractual arrangements, and relational governance [9,11,27]. Specifically, the design of the contract and the way in which risks are distributed between partners have been identified as key determinants of project success [28]. Xiong et al. [13] indicated effective mechanisms for uncertainty governance in PPP projects, emphasizing the importance of flexibility and cooperation in managing complexity. Similarly, Cruz and Marques [29] explored contractual governance to address uncertainty in the project lifecycle and proposed dynamically adjusting contract terms to cope with unforeseeable changes. Song et al. [9] focused on the role of risk allocation in uncertainty governance, arguing that reasonable risk sharing can effectively reduce uncertainty and enhance the willingness of all parties to cooperate.

Furthermore, a growing body of research focuses on the role of relational governance in PPPs. Studies have shown that strong relational governance can enhance cooperation and flexibility, which are critical for addressing uncertainties and achieving project objectives [18,21]. For example, Wang et al. [30] highlighted trust and communication as key to managing PPP uncertainties, enabling transparency and collaborative problem-solving during unexpected changes. Additionally, Zou et al. [27] indicated long-term relationships in PPPs, fostering flexibility and mutual adaptation to risks like demand variability or technological shifts. Sharafi et al. [31] emphasized relational governance in creating joint conflict resolution frameworks, ensuring smooth renegotiation during financial or operational uncertainties. Institutional frameworks also play a pivotal role. The role of institutional and regulatory frameworks in achieving governance structures has been widely discussed. Government policies, regulations, and legal frameworks significantly affect the governance of PPP projects [32]. These factors can influence how contracts are structured, how risks are allocated, and how accountability is managed. For instance, in some developing countries, weak legal systems and regulatory uncertainty may increase the complexity of governance in PPPs [33]. Conversely, the robust institutional frameworks can support the creation of clear and transparent governance mechanisms that align the interests of stakeholders [12].

While existing studies have extensively examined contractual, relational and institutional governance factors in PPP projects, a systematic framework integrating these dimensions remains underdeveloped. To address this gap, we conducted a literature review to identify governance factors influencing PPP project resilience. Utilizing the Web of Science (WOS) database, we performed a comprehensive search with the following keywords: “uncertainties” OR “resilience” OR “sustainable operations” OR “flexibility” OR “vulnerability” OR “adaptation”, combined with “public-private partnership” OR “private finance initiative” OR “build-operate-transfer”. This search yielded a total of 243 relevant articles. To refine the selection, we carefully reviewed the abstracts of these articles, including 116 studies for further analysis. Subsequently, we employed a content analysis approach to categorize and code the identified governance factors. This process involved extracting key themes and patterns from the selected literature, which were then systematically organized to highlight the most critical governance factors for enhancing PPP project resilience. Additionally, we employed a content analysis approach to categorize the identified governance factors based on established governance theory. The factors were systematically classified into four main dimensions: institutional, organizational, contractual, and managerial. Institutional factors encompassed regulatory frameworks, policy support, and legal environments that shape the governance of PPP projects. Organizational factors included the structure and culture of the entities involved in the partnership. Contractual factors focused on the design, flexibility, and enforcement of agreements between public and private stakeholders. Finally, managerial factors addressed capabilities, decision-making processes, and adaptive strategies employed during project implementation. This study developed a governance framework of PPP project resilience in four dimensions: institutional factors, organizational factors, contractual factors, and managerial factors. Consequently, thirteen governance factors in four dimensions are identified in

Table 1. Identification of governance factors for PPP project resilience.

Dimensions and Categories	Descriptions	Themes	Source
D1—Institutional factors
C1—Regulatory and accountability	Systematically monitor and enforce accountability for compliance, performance	C1.1—Strategic supervision and monitoring	[11,33]
		C1.2—Transparency management	[13,34]
C2—Government effectiveness	The comprehensive ability of government agencies to ensure project objectives	C2.1—Existence of sound investment environment	[35,36]
		C2.2—Defined roles and responsibilities	[21]
C3—Clear legal framework	Effectively maintain a stable legal and institutional system	C3.1—Policy stability	[32,37]
		C3.2—Procedural fairness	[21]
D2—Organizational factors
C4—Cross- organizational collaboration	Integrating multiple organizational resources, capabilities, and stakeholders	C4.1—Special purpose vehicle team	[4,8]
		C4.2—Professional consulting agency	[38]
		C4.3—Public participation	[13,21]
C5—Strategic alliance	Strategic partnership between public and private sectors based on deep collaboration	C5.1—Mutual trust	[36,39]
		C5.2—Long-term cooperation	[40]
		C5.3—Common goal and shared understanding	[21]
C6—Private financing stability	The private sector continues to provide funds steadily during the project cycle	C6.1—Selecting multiple financial institutions or financial services	[36,41]
		C6.2—Purchasing insurance	[35]
		C6.3—Asset portfolio diversification	[42]
D3—Contractual factors
C7—Risk allocation and transfer	Reasonably allocate and transfer various risks that may be faced in the process of project implementation	C7.1—Fair/equitable risk sharing or allocation	[11,43]
		C7.2—Risk reappraisal mechanism	[43,44]
		C7.3—Effective risk allocation and transfer protocols	[8,45]
C8—Flexible contract	A contract that presupposes an adaptive clause and gives the parties to the contract the right and obligation to adjust under specific conditions	C8.1—Early termination after breach of contract	[9,29]
		C8.2—Mechanism for renegotiation arrangements	[10,46]
		C8.3—Procedures for resolving claims and disputes	[31,47]
		C8.4—Clear contract change procedure	[30,35]
C9—Financial planning design	Systematic and forward-looking financial planning for the whole life cycle of the project	C9.1—Equitable revenue guarantee structure	[48,49]
		C9.2—Optimum financial computation	[43,50]
		C9.3—Strategic financial planning and package	[41,51]
D4—Managerial factors
C10—Long-term relationship management	A partnership of sustainability, collaboration, and mutual trust throughout the life cycle of the project	C10.1—Long-term commitment	[52,53]
		C10.2—Frequent interactions or communication	[21,47]
		C10.3—Strategic conflict resolution and co-ordination	[54]
C11—Whole life-cycle assessment	Evaluate and manage the economic, technical, social, and environmental values of the project from planning to handover	C11.1—Value for money assessment	[33,55]
		C11.2—Service quality assessment	[56]
		C11.3—Operational performance assessment	[12,33]
C12—Management capability development	Systematically integrate resources and improve team knowledge and skills	C12.1—Technical innovation development	[21]
		C12.2—Development of integrative dynamic capabilities	[5,13]
C13—Information and resource sharing	Mechanism for systematic sharing of knowledge, resources, and benefits	C13.1—Knowledge sharing	[6,8]
		C13.2—Exchange of resources	[6,21]
		C13.3—Sharing profit-making for the project	[57]

.

3. Research Methods

3.1. Research Design

This study employs an integrated approach to explore and evaluate the governance factors influencing PPP project resilience. A literature review in Section 2 is conducted to identify the key governance factors, which are then organized into a comprehensive governance framework. This framework serves as the foundation for further analysis. Then, the ISM method is utilized to analyze the hierarchical relationships and interdependencies among these factors, providing a structured understanding of their influence on PPP project resilience. Following this, the DEMATEL technique is applied to assess the causal relationships and the relative importance of each governance factor. This dual-method approach not only highlights the critical factors that significantly impact resilience but also elucidates the complex interplay between them. By integrating ISM and DEMATEL, the study offers a nuanced perspective on how governance mechanisms can be optimized to enhance the resilience of PPP projects, thereby contributing to more robust and sustainable infrastructure development. The research process of this study is shown in Figure 1.

Second, we employed purposive sampling to select experts, contacting over 50 organizations within China specializing in PPP projects, including government agencies, consulting firms, and academic institutions. Thirty potential collaborators were identified from this group. After introducing the research objectives via email, we received positive responses from 12 institutions. Due to scheduling conflicts, two experts could not participate, resulting in a final group of eight experts, each with more than 10 years of experience in the PPP field (

Table 2. The basic profile of experts.

ID	Role	Gender	Role/Position	Experience
No. 1	Government	Male	Officer	Over 10 years
No. 2	Government	Male	Vice Director	Over 20 years
No. 3	Private sector	Female	Manager	Over 15 years
No. 4	Private sector	Male	Engineer	Over 20 years
No. 5	Private sector	Male	Manager	Over 15 years
No. 6	Consultant	Female	Professor	Over 15 years
No. 7	Consultant	Male	Professor	Over 20 years
No. 8	Consultant	Male	Manager	Over 15 years
No. 9	Financial institution	Female	Manager	Over 15 years
No. 10	Financial institution	Male	Stuff	Over 10 years

). The purposive sampling criteria focused on individuals (1) with extensive practical experience (minimum 10 years), (2) holding leadership roles (e.g., professors, senior consultants, or executives) in PPP-related organizations, and (3) demonstrating academic contributions to PPP governance research. These experts not only possessed deep industry knowledge but also a strong academic background in infrastructure and governance. The data collection period spanned from 1 June to 30 October 2024, primarily utilizing email communication and online survey platforms. A mixed-method approach was adopted, combining online surveys with follow-up telephone or video interviews to ensure both breadth and depth in the data collected. Initially, the survey questionnaires were distributed to the experts via email, allowing them to respond at their convenience. All ten experts completed the surveys within the designated timeframe. To gain deeper insights, we conducted five telephone or video interviews with three experts, while the remaining seven provided detailed responses through email or online platforms. Although face-to-face interviews were initially considered, some challenges, such as geographical dispersion and time constraints, made remote methods more practical. The integration of surveys and interviews enabled the collection of both quantitative and qualitative data, enhancing the overall analysis and ensuring a comprehensive understanding of the research topic. Thus, this study employed a hybrid approach, leveraging online surveys and remote interviews to achieve a flexible, thorough, and insightful data collection process.

3.2. ISM

ISM is a systematic approach developed by Warfield [58] to analyze and structure complex systems by identifying relationships among elements. The method transforms unclear systems into well-defined hierarchical models using expert judgments to establish contextual relationships [59]. ISM breaks down intricate problems into manageable levels, helping decision-makers visualize dependencies and interactions [60] by creating a reachability matrix and hierarchical structure, ISM identifies key drivers and outcomes, making it effective for understanding multifaceted systems [12].

Step 1: Identification of governance factors for PPP project resilience

This study adopted a literature review to identify governance factors for PPP project resilience. Data triangulation was conducted by searching and collecting relevant documents, and continuous screening and filtering were conducted through subject and abstract review, followed by a full-text review. These governance factors are validated through consultations with 10 experts from academia, government agencies, and private sector stakeholders, ensuring relevance to PPP contexts. Only governance factors unanimously approved by experts are retained.

Step 2: Development of structural self-interaction matrix

The governance factors’ interaction matrix uses four symbols: V, A, X, and O. Expert-derived relationships populate the matrix. Influence strength is scored (0–4): 0 means no impact, while 1–4 indicate increasing direct influence. This framework systematically maps and quantifies directional relationships between governance factors, enabling structured analysis of their interdependencies through both symbolic notation and numerical scoring.

Step 3: Establish an adjacency matrix

Establish the adjacency matrix of the structural self-interaction matrix based on hindering factors, that is, convert the symbols “V, A, X, and O” in the structural self-interaction matrix into binary elements 0 and 1.

Step 4: Establish a reachability matrix

R(C_i) (Reachable Set): All factors in row j of the matrix where C_i can directly influence (marked by “1”). Q(C_i) (Antecedent Set): All factors in column i of the matrix that directly influence C_i (marked by “1”). F = R(C_i) ∩ Q(C_i): The overlap between these two sets, showing factors that both influence and are influenced by C_i.

Step 5: Classification of hierarchical relationships

Then, the matrix P′ is obtained by deleting the rows and columns corresponding to the elements in L from P. The same operation is performed on P′ to find L₁, L₂, …, L_n is used to assign each element to the corresponding level. Finally, it represents the hierarchy of the system in the form of a directed graph based on reachability matrix P.

Step 6: MICMAC analysis

The cross-influence matrix multiplication MICMAC is mainly used to analyze the influence and dependence relationships between various factors in the system. The results can be represented by coordinate axes, where dependence is represented by the horizontal axis and driving force is represented by the vertical axis.

3.3. DEMATEL

The DEMATEL method is a structured analytical approach designed to address complex systems characterized by interdependent factors [26]. By transforming qualitative expert judgments into a quantitative framework, DEMATEL identifies key drivers and receivers within a system, distinguishing between factors that exert influence and those that are influenced [61]. A significant advantage of DEMATEL lies in its ability to handle high levels of complexity and interdependence, providing a clear visualization of system structures through impact-relation maps [62]. Researchers and practitioners can prioritize factors, particularly when understanding the interplay between factors is critical. DEMATEL has been widely applied across various disciplines, including supply chain management [63], strategic management [62], and risk assessment [61].

Step 1: Construct the direct-influence matrix

Use the output results of the ISM method as inputs for the DEMATEL method to construct an average direct impact matrix of hindering factors, i.e., only consider variables with interrelationships in the ISM model to collect data from experts. Gather expert opinions to create a direct-influence matrix D = [d_ij]. The scale typically ranges from 0 (no influence) to 4 (very high influence), where d_ij represents the influence of factor i on factor j.

Step 2: Normalize the direct-influence matrix

Convert the direct-influence matrix into a normalized matrix N by using the following formula:

$$N_{ij}={\displaystyle \frac{d_{ij}}{{\displaystyle \sum _{j=1}^n{d}_{ij}}}}$$

(1)

where N_ij is the normalized value and N is the total number of factors.

Step 3: Calculate the total influence matrix (T)

The total influence matrix T is obtained by

$$T=N{(I-N)}^{-1}$$

(2)

where I is the identity matrix; this matrix represents direct and indirect influences among factors.

Step 4: Calculate the prominence and relation values

Determine the prominence (P) and relation (R) values for each factor:

$$P_i={\displaystyle \sum _{j=1}^n{t}_{ij}}\hspace{1em}( sum of row i)$$

(3)

$$R_i={\displaystyle \sum _{j=1}^n{t}_{ij}}\hspace{1em}( sum of column i)$$

(4)

The horizontal axis vector position factors are presented in a causal diagram, visually representing their relationships in order to interpret and utilize [61]. The degree of causality can be divided into prominence factors and relation factors based on positive or negative values. (D + R) is the prominence factor, reflecting the significant impact of this factor on other factors and systems; (D − R) is the relation factor, reflecting that other factors easily influence this factor. Based on the calculation results, a causal result graph can be drawn using centrality as the horizontal axis and causality as the vertical axis.

4. Results and Analysis

4.1. ISM Results Analysis

The ISM model was constructed to explore the governance factors of hierarchical structure and transmission paths. The 13 main categories of governance factors are presented in a six-level system in Figure 2. C7—Risk allocation and transfer, C4—Cross organizational collaboration, C5—Strategic alliance, and C6—Private financing stability are at the top of the hierarchy in Level I and Level Ⅱ. The prerequisite for addressing these factors is first governing some relevant factors in the middle and bottom of the hierarchy. There are enabler factors located in the middle hierarchy (Level Ⅲ and Level Ⅳ), including C3—Clear legal framework, C9—Financial planning design, C10—Long relationship management, C13—Information and resource sharing, C8—Flexible contract, C11—Whole life-cycle assessment, and C12—Management capability development. These governance factors mediate the influencing process, affecting the top-level governance factors for the hierarchy. C1—Regulatory and accountability and C2—Government effectiveness are the two most direct governance factors at the bottom of the hierarchy (Level Ⅴ and Level Ⅵ).

The fifth and sixth level consists of C1—Regulatory and accountability and C2—Government effectiveness. They are critical to ensuring project compliance, transparency, and accountability, forming the bedrock upon which other layers are built. Regulatory and accountability establishes the legal and regulatory framework, which contributes to the effectiveness of government actions in managing the PPP project [32]. Government effectiveness measures how well the government can execute its policies, coordinate stakeholders, and ensure efficient project management [23]. These bottom-level governance factors create a stable environment for the project, enabling PPP project resilience by laying down clear rules, frameworks, and governance systems. Without strong regulation and government oversight, the higher-level strategies and operational factors may falter due to a lack of institutional support or enforcement mechanisms [12]. Therefore, C1—Regulatory and accountability and C2—Government effectiveness have an indirect but crucial influence on PPP project resilience by facilitating the operational conditions required for higher-level success.

The middle layer focuses on sustainable operation, financial management, and long-term collaboration. Flexible contracts ensure that contracts can adapt to unforeseen circumstances, enhancing resilience when changes occur [29]. Financial planning design integrates a life-cycle perspective, where both cost management and assessment of the entire project life cycle help maintain economic stability and operational performance [5]. Information and resource sharing encourages long-term relationships between stakeholders and ensures transparent information sharing, which is crucial for managing uncertainties and fostering collaboration in complex PPP projects [8]. The management capability development directly enhances the adaptive capacity of teams, making them better equipped to handle challenges [13]. This middle layer serves as a bridge between the foundational policies and the operational strategies at the top layer, providing the technical, financial, and managerial resources needed to maintain the project resilience over time.

At the top level, these governance factors focus on organizational factors, which are critical for PPP project resilience. Cross-organizational collaboration emphasizes the need for collaboration across organizations and professional disciplines, ensuring that diverse expertise is available for project execution [17]. Governments often rely on specialist agencies to compensate for their lack of capacity [13], which helps identify technical risks in areas with limited knowledge. By establishing SPV, the private sector manages, finances, designs, constructs, and operates projects throughout their life cycle, aligning with client needs. Private financing is essential for ensuring adequate funding is available to support the project, especially since PPP projects typically require large-scale investments [41]. These top-level governance factors are directly responsible for managing the operational complexities and uncertainties of PPP projects. They are closely connected with middle-level governance factors, such as contract design and long-term management, and are influenced by regulatory and government effectiveness.

Finally, the other objective is to analyze the governance factors of driving power and dependence power with the help of MICMAC analysis. According to the reachable matrix, each driving force value and dependence value indicator is analyzed as a driver group, linkage group, autonomous group, and dependent group in the MICMAC map, as shown in Figure 3. In the study, C1—Regulatory and accountability, C2—Government effectiveness, C8—Flexible contract, C11—Whole life-cycle assessment, and C12—Management capability development fall into the independence cluster. Independent clusters are characterized by high driver values and low dependence, indicating that governance factors in this cluster have a wide range of influences and are not easily influenced by other governance factors. The linkage cluster denotes the governance factors with high dependence and driving power. In the study, no governance factors belong to the cluster, which means that governance factors are stable. The dependence cluster has strong dependence but weak driving power and is susceptible to other governance factors. C4—Cross-organizational collaboration teams, C7—Risk allocation and transfer, C5—Strategic alliance, and C6—Private financing stability are dependence clusters at the top levels of the ISM. Autonomous clusters have low driving and dependence power. In this study, C3—Clear legal framework, C9—Financial planning design, C10—Long relationship management, and C13—Information and resource sharing are in the middle level. They can influence the governance factors at the upper level of the hierarchy as well as be influenced by the governance factors at the lower level.

4.2. DEMATEL Results Analysis

From

Table 3. The degree of prominence and net cause/effect values.

Factors	Governance Factors	D	R	D + R	D − R	Rank	Group
C1	Regulatory and accountability	1.734	0	1.734	1.734	6	Cause
C2	Government effectiveness	1.349	0.08	1.429	1.269	9	Cause
C3	Clear legal framework	0.457	0.388	0.845	0.064	13	Cause
C4	Cross-organizational collaboration	0.175	1.594	1.769	−1.419	5	Effect
C5	Strategic alliance	0.444	1.836	2.280	−1.398	2	Effect
C6	Private financing stability	0.456	1.114	1.570	−0.657	8	Effect
C7	Risk allocation and transfer	0.094	2.371	2.465	−2.277	1	Effect
C8	Flexible contract	1.386	0.497	1.883	0.888	4	Cause
C9	Financial planning design	0.529	0.482	1.010	0.047	12	Cause
C10	Long-term relationship management	0.906	1.067	1.974	−0.161	3	Effect
C11	Whole life-cycle assessment	1.421	0.193	1.614	1.228	7	Cause
C12	Management capability development	1.067	0.251	1.317	0.816	10	Cause
C13	Information and resource sharing	0.537	0.680	1.217	−0.142	11	Effect

, D + R as the prominence value represents the total cause and effect influences. The higher the prominence value of governance factors, the stronger the contribution of the governance factors to PPP project resilience. The ranking order is as follows: C7 > C5 > C10 > C8 > C4 > C1 > C11 > C6 > C2 > C2 > C12 > C13 > C3. The top four contributors are the governance factors for PPP project resilience, including C7—Risk allocation and transfer, C5—Strategic alliance, C10—Long-term relationship management, and C8—Flexible contract. Therefore, in order to achieve PPP project resilience, these five governance factors need to be given special attention.

Risk allocation and transfer refers to a new approach to management in the private sector that assumes project risk, which provides the best approach and tools for innovation activities. Risk management tools help optimize project processes, address technical and operational issues, and help the team respond quickly to emergencies in a timely and effective manner [45]. Reducing transaction costs and increasing participation is possible by transferring risks and responsibilities to the private sector [43]. Fair and equitable risk sharing forms the cornerstone of risk response in PPPs [44]. Risk allocation and transfer can provide efficient solutions for agents to design a project, leading to efficient collection of production information and stimulating innovation throughout the life cycle. Therefore, optimal risk allocation and fair sharing enable the public and private to attain a win-win [5].

Strategic alliance is critical for resilience in a fragmented industry, ensuring all parties achieve collective goals when different actors are interfacing in inter-organizational collaborations. Although PPP contract bundling offers a mechanism for integration, it necessitates strategic alliances exerting robust management control. Governments need specialist agencies to compensate for their lack of capacity [13]. This enables the organization to adjust project plans, resource allocation, and goal setting more quickly to new challenges and opportunities. The finding corresponds with Carbonara and Pellegrino [55], who regard PPP as an organizational innovation that enables all project stakeholders to integrate resources and form a strategic alliance.

Flexible contracts allow contract terms to be adjusted according to actual circumstances during project execution. When the external environment changes, the project can be flexibly adjusted by modifying contract terms to avoid rigid contract structures hindering project progress [30]. This flexibility enhances the adaptability of the project, enabling it to quickly respond to unforeseen risks or changes. Furthermore, flexible contract design typically includes clearly defined dispute resolution mechanisms, such as renegotiation mechanisms and dispute arbitration [29]. Song [9] indicates that renegotiations are invariably required to fit the complexity and uncertainty of the project life cycle.

Long-term relationship management reduces friction and uncertainty between the public and private sectors by establishing and maintaining trust. In PPP projects, trust is the foundation for responding to unexpected issues and promoting cooperation and coordination [52]. When PPP projects encounter risks or challenges, trust helps both parties to jointly find solutions, enhancing the adaptability and resilience of the project [39]. In addition, project parties usually establish effective communication mechanisms based on long-term cooperation to ensure timely information sharing. The information-sharing mechanism not only helps all parties better understand the risks and opportunities but also improves the response speed in emergencies, thereby enhancing anticipation and adaptability capability [21].

In Figure 4, the causal group has a strong initiative and significantly impacts the PPP project resilience. Once the causal group is promoted, it can also promote other governance factors and improve the entire governance factor system. The six causal groups are ranked according to D-R values as follows: C1 > C2 > C8 > C11> C12 > C3 > C9.

5. Discussion

5.1. Theoretical Implications

This study aims to identify and evaluate governance factors influencing PPP project resilience by using the ISM and DEMATEL approaches. The findings of our study contribute to the relevant literature in three aspects. First, the main contribution of this study is to develop a governance framework for PPP project resilience, which includes four dimensions (institutional, organizational, contractual, and managerial factors) and thirteen governance factors. The findings indicate that these governance factors significantly enhance the PPP project resilience, particularly in dealing with the uncertainties and risks associated with the complexity and long life cycle of projects. Previous studies have focused on the role of individual governance factors [10,27,29], whereas this study integrates multiple dimensions and proposes a more comprehensive theoretical framework, emphasizing the interrelationships and combined effects of governance factors. This study extends the comprehensive model of PPP sustainable operation factors through a systematic analysis of the relationships among the factors influencing PPP project resilience [12]. This contribution helps further enrich and develop governance theories in PPP projects, particularly in resilience management.

This study significantly advances our understanding of PPP governance by systematically revealing how various governance factors interact dynamically to enhance project resilience. Building on the ISM and DEMATEL analysis, we demonstrate that resilience in PPP projects emerges not from isolated governance mechanisms but from their complex interplay and mutual reinforcement. The findings establish that contractual flexibility, often highlighted as crucial for resilience [29], fundamentally depends on robust institutional frameworks that provide regulatory stability. This institutional foundation enables effective contract risk allocation, fostering relational governance through partner trust-building. Such relational capital then supports the development of adaptive managerial capabilities when facing disruptions. This cascading effect explains why governance factors indirectly influence resilience through interconnected pathways rather than isolated impacts.

Institutional factors emerge as the critical underpinning that supports and sustains other governance dimensions. Liu et al. [33] indicate that even well-designed contracts and competent management teams struggle to maintain sustainable operations where policy environments are unstable or legal frameworks are weak. A good organizational structure arrangement can mediate this situation, as clear roles and responsibilities are necessary conditions to translate institutional support into effective contract monitoring and implementation. Effective contract design must account for institutional requirements while allowing sufficient flexibility for managerial adaptation. Similarly, organizational structures must facilitate contractual compliance and relational development among partners. When these dimensions collaborate in governance, they create synergies that enhance resilience beyond what any single factor could achieve independently. This systemic understanding moves beyond previous research that examined governance factors in isolation [10,27]. By revealing how institutional, organizational, contractual, and managerial factors interact, the study provides a more comprehensive theoretical framework to strengthen PPP project resilience.

5.2. Practical Implications

The identified transmission pattern provides insight into achieving PPP project resilience and developing a feasible process for different governance mechanisms. First, practitioners need to pay more attention to institutional factors. These governance strategies have the highest driving power and can induce the adoption of other governance strategies, which may lead to different governance mechanisms. The improvement of governance factors at the lower level could promote other governance factors at upper levels, such as regulatory and accountability government effectiveness. The government can regularly monitor and evaluate the performance of projects and compare actual performance with contractual indicators, effectively reducing opportunism. The public sector can also formulate a series of policies and measures to attract private investment, such as providing fiscal incentives, simplifying approval processes, and reducing investment risks to increase the attractiveness of private investment. A stable, transparent, and predictable investment environment is conducive to attracting private investment, including measures to protect investor rights, uphold the rule of law, and combat corruption.

Contractual and managerial factors serve as governance tools at the operational level, providing various fundamental solutions for project governance. These governance strategies are at the intermediate level and critical to dealing with construction and operation uncertainties. The contract design should consider the flexibility and change management of the project, ensuring that reasonable contract adjustments can be made when necessary to adapt to changes in the project and unforeseeable circumstances. Finally, organizational factors are crucial governance factors for PPP project resilience. The public and private sectors should jointly seek common interests in projects and establish strategic alliances to achieve these benefits. The alliance should be based on mutual trust and cooperation, which helps to achieve long-term cooperative relationships. The public and private sectors should promote knowledge sharing and technology transfer to enhance alliances jointly. Additionally, project teams that promote relationship integration are essential to develop and maintain good relationships and performance levels throughout the PPP timeframe.

The practical application of this study’s findings requires consideration of varying environmental conditions that influence governance effectiveness in PPP projects. In stable institutional settings with strong regulatory frameworks, governance mechanisms can be systematically implemented to enhance project resilience. However, in contexts with regulatory uncertainty or weaker institutional support, adaptive governance strategies—such as flexible contracts, strategic alliances, and long-term relationship management—become essential to mitigate risks and ensure project continuity. A transparent legal environment, mature financial markets, and government commitment to long-term collaboration are fundamental for ensuring stable private sector participation. Additionally, socioeconomic factors, such as stakeholder trust and public acceptance, affect the effectiveness of governance mechanisms. In volatile or emerging markets, fostering cross-sector collaboration and developing public sector management capabilities for information transparency can enhance governance adaptability. By aligning governance strategies with these external conditions, PPP stakeholders can better navigate uncertainties and strengthen project resilience in diverse operational environments.

5.3. Limitations and Future Research

This study has some limitations. First, the professionals and the experts are based in China, and the generalizability of the findings to other countries may vary. The results of this study can be validated in developed countries in the future. Secondly, hierarchical structures can illustrate the qualitative interconnections among governance factors for PPP project resilience; however, they do not provide a quantitative measure of the impact. There is a need to identify further the effect of each governance factor on PPP project resilience.

6. Conclusions

This study explored the governance factors that influence the resilience of PPP projects. By proposing a comprehensive framework integrating thirteen governance factors across four distinct dimensions—institutional, organizational, contractual, and managerial—it seeks to enhance theoretical and practical understandings of PPP project resilience. The research employs interpretive structural modeling (ISM) and the decision-making trial and evaluation laboratory (DEMATEL) methodology to systematically analyze the interdependencies and hierarchical architecture among these factors.

According to the results based on the DEMATEL method, strategic alliances, risk allocation and transfer, flexible contract, and long-term relationship management constitute critical governance factors underpinning PPP project resilience. According to the results based on the ISM method, governance factors for PPP resilience are divided into six levels. Among all governance factors, C1—Regulatory and accountability and C2—Government effectiveness are the bottom governance factors of the hierarchy, so they may quickly impact other governance factors. At the intermediate levels, C8—Flexible contract, C11—whole life-cycle assessment, and C12—Management capability development are influenced by higher governance factors while also triggering the emergence of lower governance factors, either directly or indirectly. However, the governance factors at the top level of the hierarchical model, like C4—Cross-organizational collaboration and C7—Risk allocation and transfer, are less likely to lead to other governance factors. These findings make theoretical contributions by delineating a structured framework for identifying and prioritizing key governance factors while offering practical value by enabling practitioners to develop targeted strategies. Specifically, the framework allows stakeholders to systematically implement interventions that strengthen resilience by leveraging the identified critical factors and their relational dynamics within the governance system.

Notably, the practical application of these findings depends on certain external conditions. A stable regulatory environment, government commitment to policy consistency, and well-developed financial markets are essential to ensuring the feasibility of strategic alliances and risk-sharing mechanisms. Moreover, institutional support for transparent governance and stakeholder collaboration facilitates the practical implementation of flexible contracts and long-term relationship management. By considering these external conditions, policymakers and practitioners can more effectively tailor governance strategies to enhance the resilience of PPP projects.