Research on the Formation Mechanism of Multiple Subjects’ Collaborative Governance in Chinese Old Urban Residential Area Renovation

Abstract

The renovation of old urban residential areas is and will continue to be an important part of urban renewal in China. The renovation of existing old urban residential areas focuses more on the physical level of renovation and pays insufficient attention to the improvement of collaborative community governance. However, collaborative community governance is the key to sustainable renovation. This study aims to explore the formation mechanism of multiple subjects’ collaborative governance in the renovation of old urban residential areas. A general collaborative governance theoretical framework was adopted and adjusted by innovatively introducing the improvement of collaborative community governance in old urban residential areas as an important variable in collaborative results. Data were collected through 853 questionnaires in 16 provinces across China and analyzed using Structural Equation Modeling. Data analysis reveals the following conclusions: (1) institution design and the collaborative process have significant positive impacts on collaborative results, while facilitative leadership has a negative impact; (2) the collaborative process is an important mediating variable on collaborative results; (3) government departments’ and residents’ self-governing organizations play important roles in improving collaborative community governance. Face-to-face dialogue and consultation, information disclosure and transparency, and reaching an intermediate consensus are important mediator variables. The research results provide theoretical support and practical suggestions for promoting the improvement of multiple-subject collaboration through old urban residential area renovation.

1. Introduction

The renovation of old urban residential areas (OURAs) is an important aspect of urban renewal. The renovation of OURAs is a major project concerning people’s livelihood and life quality and is of great strategic importance for expanding domestic consumption. China’s OURAs are generally plagued by problems such as inadequate supporting facilities, backward safety facilities, and insufficient environments for elderly people [1]. In 2020, the Ministry of Housing and Urban-Rural Development of China (MoHURD), together with the State Council, issued the Guiding Opinions on Comprehensively Promoting the Renovation of Old Urban Residential Areas, which required all provinces to renovate OURAs. According to MoHURD statistics, 258,579 OURAs have been renovated in China. Currently, in China, OURAs usually refer to residential areas built before 2000. However, the number of OURAs is expected to continue to increase over time. According to the National Bureau of Statistics, residential buildings built before 2000 account for 31.22% of the total number of existing residential buildings. A total of 1.64 billion square meters of residential space were built between 2000 and 2009, accounting for 32.16% of the total number of existing residential buildings, and 1.8669 billion square meters of residential space has been built since 2010, accounting for 36.61% of the total number of existing residential buildings. With the passage of time, residential buildings built before 2010 and residential buildings built before 2020 will gradually become old residential buildings. Therefore, the renovation of OURAs will become regular urban renewal work in the future and is in great demand.

The renovation of OURAs involves highly complex subjects and has changed from the initial single government-led style to government–market cooperation and evolved towards the trend of collaborative governance by multiple subjects, such as the government, market subjects, authority subjects, and the public. Buildings and all public infrastructure in OURAs are public physical spaces, which are non-exclusive, non-competitive, and public goods in the broad sense of the term [2]. Therefore, the renovation of OURAs requires joint decision-making by the subjects involved in the process. The participation of governments, social investment firms, social organizations, and professional firms (including planning, engineering, procurement and construction, and property management) has been valued. Moreover, residents’ role in the governance process of the renovation of OURAs has become increasingly prominent, especially after China began advocating for a social governance pattern of “joint contribution, shared benefits and collaborative governance,” and constantly emphasizing public participation in the management of public affairs [3]. Therefore, it is necessary to put the renovation of OURAs in the context of the modernization of the country’s governance capacity, guiding multiple subjects to balance their interests and play a role in the formation of governance vitality and the effectiveness of co-governance. The participation of multiple subjects in the governance of OURAs is not only limited to the renovation process but also includes sustained operation and subsequent re-renovation after the completion of the renovation. As an important part of urban community governance, OURAs are an important vehicle for shifting the center of gravity of governance downwards [4]. Through the renovation of OURAs, while improving the living conditions of residents, it is also necessary to promote the construction and upgrading of urban grassroots community governance systems.

In recent years, the role of humans in urban renewal has been highlighted in China and worldwide. This trend also echoes China’s urban renewal, which has shifted from large-scale demolition and construction to the organic renewal and transformation of old neighborhoods [5]. Collaborative governance has gradually become a research hotspot in the field of urban renewal, and scholars have studied the formation mechanism of collaborative governance in urban renewal from various aspects. However, they have only explored the relationship between a small number of individual elements and lack systematic and comprehensive studies. Individual studies using normative collaborative governance theories have analyzed the case of OURA renovation from qualitative perspectives and have lacked quantitative analysis. To bridge this research gap, this study adopts a general collaborative governance theoretical framework and revises it according to the context of the renovation of OURAs. Meanwhile, the improvement of the community governance of OURAs is innovatively introduced as an important variable in collaborative results. This study aims to identify the key factors influencing the collaborative governance of OURA renovation and explore their influencing paths in order to provide relevant policy recommendations.

The paper is structured as follows: The second part reviews collaborative urban renewal governance. The third part presents the general collaborative governance theoretical framework, specifies the variable selection, and lists the relevant hypotheses. The fourth section elaborates on the data collection, processing, and analysis methods. The results of the data analysis are presented and discussed. Finally, the main conclusions of the study and the corresponding policy recommendations are summarized.

2. Literature Review

2.1. Collaborative Governance

The concept of collaborative governance originated in the 1970s and was used to describe the management structure of centers of in-service education and teaching in education systems [6]. Since then, the study of “collaborative governance” has evolved in the context of how public and private institutions work together in education. In recent years, it has been gradually extended to a number of areas of public affairs, such as natural resource management and community management, in which governance cannot be accomplished by the government alone and requires the participation of the private sector.

In the current body of research, a concrete definition of “collaborative governance” is still lacking, though a specific sense (such as Ansell and Gash [7]) and general sense of collaborative governance have been given (such as by Emerson et al. [8] and the Commission on Global Governance). Although the scope of definitions varies, scholars in the field generally agree that collaborative governance emphasizes the interaction and cooperation of multiple subjects, such as citizens, governments, markets, and social organizations, within the governance space [9]. The essence of governance is the process of interaction among subjects. As Stoker stated, “in the end, governance seeks ultimately to create the conditions for social order and collective action, and therefore the results of governance are no different from domination, and if there is any difference, it is only in the process” [10].

The rise of collaborative governance research has been deeply influenced by the changing times. “We live in turbulent times. No doubt that has always been the case, but the magnitude of stress and turbulence in the twenty-first century is greater than ever before”, Donahue and Zeckhasuser, leading scholars in the field of collaborative governance, explain regarding the macro-context of the rise of collaborative governance research [11]. The traditional system of the government acting as a single governing subject faces enormous challenges in a time of turbulence. In many cases, the government finds that it lacks the funds and capacity to solve increasingly complex public affairs on its own, and that it needs to bring in private enterprises, social organizations, and other subjects to participate in governance. Similarly, private enterprises and social organizations are constrained in solving complex public affairs independently by their own resources. The interdependence of various types of governance subjects is gradually increasing, and they need to cooperate with each other and integrate their strengths to effectively solve complex affairs and achieve common goals.

The rise of collaborative governance research in China focuses on the context of the transition period of the social management model. Over the past three decades, China has gradually begun to transfer its social management model, gradually introducing the participation of social enterprises, the public, social organizations, and many other subjects in social governance. The goal of constructing a “social governance pattern of joint contribution and shared benefits for all people” has been proposed, as well as “strengthening primary-level governance system and transferring the focus of social governance to the grassroots”. Research on collaborative governance has gradually expanded from macro-institutional issues to micro-social issues and has begun to be widely applied to more micro-areas of social governance, such as community governance.

2.2. Urban Renewal and Collaborative Governance

2.2.1. Evolving Urban Renewal

Urban renewal is an important issue for countries worldwide which derives from academia’s and industries’ reconsideration of the purpose of urban development and the proper ways of urban planning and design. After World War II, Western countries carried out large-scale urban redevelopment and clearance–reconstruction-style renewal, theoretically influenced by industrial modernist planning, emphasizing functional zoning and large-scale renovation. The Hague, The Netherlands, held the first conference on the transformation of old cities in 1958, proposing three key aspects in the transformation and construction of aging urban areas: redevelopment, restoration, and protection. Since then, old city renewal in Western countries can be divided into four development stages: slum clearance, welfare-colored community renewal, market-oriented old city redevelopment, and comprehensive community revitalization. Theoretical and practical research on urban regeneration is very mature, and research areas include gentrification [12,13], creative cities [14,15], sustainability [16,17,18], and community regeneration [19] from different perspectives at the two different scales of the city and community. After the initial large-scale redevelopment of urban renewal, Western countries realized that redevelopment could not solve urban problems and gradually paid more attention to small-scale and progressive urban renewal [20]. Researchers such as Jane Jacobs and Christopher Alexander criticized the industrial model of city development for damaging diversity and previous social life and called for small-scale, incremental urban renewal [21,22,23,24].

China’s urban renewal has also shifted from large-scale demolition and construction to the organic renewal and transformation of old neighborhoods [5]. China has experienced a long period of the large-scale demolition and reconstruction of old buildings and facilities. Such an industrial model of city development has led to the deconstruction of historical features and the intensification of social conflicts, pollution, and resource wastage [25]. Since the 2010s, the reuse of old industrial areas, protective improvement, and the renewal of shantytowns and urban villages with goals to improve the living environments of disadvantaged groups have started to increase. During this period, a discussion on the purpose of the city and sustainable city development took place, as well as one on whether to demolish and rebuild or partially update and renovate in order to achieve further urban development [26]. In 2020, China’s 14th Five-Year Plan clearly favored urban renewal and announced a five-year action plan for OURAs. In the plan, building renovation is suggested and building demolition is required to be treated with caution.

2.2.2. Increasing Emphasis on Collaborative Governance

In recent years humans’ role in urban renewal has been highlighted (such as by Xie et al. [27]). Collaborative governance has gradually become a research hotspot in the field of urban renewal, and scholars have studied the formation mechanism of collaborative governance in urban renewal from different perspectives. In the current research on collaborative governance for urban renewal, the term “collaborative governance” is used in four different approaches.

The first is to examine it as a desired state of governance using other theoretical perspectives. For instance, Liu et al. used a Bayesian network to analyze the mechanism of collaborative governance in city-level urban renewal in Chongqing as an example [28]. Lin et al. study the mechanism of collaborative governance of multiple subjects in urban renewal and take Shenzhen as an example to analyze how each subject participates and has counterbalance in each stage of urban renewal projects [3]. Li and Wang used three projects of renovation of OURAs in Beijing as case supports to study the mechanism of collaborative governance in these renovations, and analyzed the organizations and structures involved in governance, the division and cooperation among the subjects in the cases in terms of the dimensions of the structure of the stakeholders, and the dynamic order of action according to complex network theory [29]. Du et al. provided a correspondence analysis of how governance subjects in urban renewal position their powers, duties, and benefits from a power perspective [30]. Shen et al. devised a collaborative governance mechanism supported by critical success factors by analyzing nine stakeholders and 28 critical success factors involved in the renovation of OURAs [31].

The second approach is to adopt several elements of collaborative governance theory and study the interactions between them. For instance, Kim et al. investigated whether the level of residents’ participation and perceived collaborative governance in a cultural heritage renewal project in Mokpo, South Korea, affected their policy support for urban renewal projects, focusing on the impact of conflict management, intermediary organizations, and community revitalization on residents’ policy support [32].

The third is the use of social network analysis to study the interactive relationships and structures of multiple subjects in urban renewal. Zhang et al. conducted a social network analysis of the various levels and sectors of government organizations involved in urban renewal projects in Shenzhen and Chongqing, analyzing the density, cohesive subgroups, structural holes, and location centrality of the network of interactive relationships between the various levels and sectors of government organizations [33]. Qu used two-mode network analysis in social network analysis to analyze the stakeholders and conflicts involved in the collaborative governance of multiple subjects in urban renewal [34].

The fourth approach is to use the collaborative governance model as a theoretical framework to study the key elements of the formation of collaborative governance mechanisms. For instance, Zhu and Gao used the starting conditions–facilitative leadership–institutional design–collaborative process (SFIC) model proposed by Ansell and Gash to conduct a detailed study of the collaborative governance mechanism of urban renewal in Shanghai at the city level [7,35]. The SFIC model is a popular trend because it helps open the institutional black box of the formation of collaborative governance mechanisms.

2.3. Collaborative Governance of Urban Renewal from a Functional Performance Sequential Perspective

In recent years, a growing number of scholars have adopted a more standardized theoretical framework of collaborative governance to conduct exploratory research on the formation of collaborative governance mechanisms in urban renewal projects. The various contingency models are the most applied theoretical frameworks. Widely recognized frameworks include the “starting conditions—interactive process—outcomes” framework proposed by Wood and Gray [36], the “starting conditions—collaborative process—outcomes” contingency model (SFIC) proposed by Ansell and Gash [7], and the “system context—collaborative dynamics—collaborative outcomes” model proposed by Emerson et al. [8]. Some scholars have proposed a theoretical framework for collaborative governance, taking into account the characteristics of public affairs governance in China [6,37]. Although the detailed elements of the components differ, each model views collaborative governance as a dynamic process that is systematic and constantly undergoing cyclical processes. The above models of collaborative governance mechanisms provide solid research foundations for the systematic study of the key elements affecting collaborative governance and its causal relationship with collaborative performance.

The SFIC model proposed by Ansell and Gash is being increasingly used in urban renewal studies [7]. In the model, staring conditions, institutional design, facilitative leadership, and collaborative processes are critical factors influencing collaborative outcomes. Zhu and Gao used the SFIC model to qualitatively analyze in detail and elaborate on the collaborative governance mechanism of urban renewal in Shanghai in terms of its starting conditions, institutional design, facilitative leadership, and collaborative process at the city level [35]. The analysis emphasizes the need to improve the relevant governing arrangements, strengthen the collaborative relationship between levels and sectors of government, establish channels for social enterprises to participate through, and increase the level of substantive participation of residents as the path to realizing collaborative governance of urban renewal. Yao and Li adjusted the SFIC model by attributing starting conditions, leadership, and institutional design as collaborative elements, refining the collaborative process into the negotiation and communication process, the trust-building process, and the process of reaching consensus [38]. The outcomes of collaboration in the context of the renovation of OURAs have been refined into spatial orientation, governance balance, and community orientation. The adjusted SFIC model was used as a theoretical framework to conduct a comparative case study of collaborative governance mechanisms for two renovations of OURAs in Shanghai’s Zhaoyuan District and Lane 669 Xinhua Road. The study found that residents’ participation was symbolic and postulated, and that the leading subjects of the collaborative governance of different rehabilitation projects were different, reflecting the different power relations between “governments—communities—social organizations” formed under different empowerment and administrative resources. The above two studies demonstrate the applicability of the SFIC model in the study of collaboration among multiple subjects in urban renewal and the renovation of OURAs from a qualitative perspective.

However, current research is mostly based on qualitative analysis, and there is a lack of systematic analysis of the critical elements of collaborative governance and the causal relationship between these critical elements and collaborative performance from a quantitative perspective. Furthermore, existing studies on collaborative performance focus only on the effect of physical space renovation and lack consideration of the effect of collaborative governance enhancement in public affairs for the renovation of OURAs. This study aims to bridge this research gap. This paper applies the SFIC model to construct a collaborative governance model of multiple subjects in the renovation of OURAs, explores the institutional black box of collaborative outcomes through Structural Equation Modeling, and identifies the impacts and paths of critical elements, such as starting conditions, facilitative leadership, institutional design, and collaborative processes, on collaborative outcomes. An enhancement method to improve the degree of collaborative governance in the renovation of OURAs is proposed, with the aim of providing a reference for the subsequent renovation of OURAs.

3. The SFIC Theoretical Framework for Collaborative Governance and Research Hypotheses

3.1. Theoretical Framework

Ansell and Gash summarized and refined a generic theoretical framework for collaborative governance based on numerous cases of collaborative governance in different fields [7]. The theoretical framework includes four variables—starting conditions, institutional design, collaborative process, and facilitative leadership—which are considered to determine the outcomes of collaborative governance, as shown in Figure 1 [7,39]. Each variable can be divided into multiple detailed variables. The starting conditions determine the conditions under which collaborative governance begins, determining whether the governance initially encourages or discourages the cooperation of multiple subjects. The starting conditions include a prehistory of cooperation or conflict, levels of trust, incentives for and constraints on participation, power–resource–knowledge asymmetries, and other related conditions. Facilitative leadership focuses on exercising leadership in collaborative governance processes and facilitating consensus building, which is critical to increasing trust, especially in contexts where there is a power–resource asymmetry or a prehistory of conflict between subjects. Institutional design refers to the basic processes and ground rules for cooperation among subjects, and relevant institutional frameworks must embody inclusiveness and foster participatory engagement from multiple subjects. It also ensures clear ground rules and the transparency of the process. Collaborative process is seen as central to collaborative governance as a whole, mainly because governance is seen as an interactive process rather than a linear development. In the process, face-to-face dialogue, trust building, commitment to the process, shared understandings, and intermediate outcomes are critical factors that influence the outcome of collaborative governance.

3.2. Variable Selection and Research Hypotheses

Guided by the SFIC theoretical framework, this study identified the critical variables, including potential, observed, dependent, and control variables, for collaborative governance in the renovation of OURAs by synthesizing and analyzing the related literature within the field of urban renewal.

3.2.1. Dependent Variable

The dependent variable in this study is the outcome of collaborative governance in the renovation of OURAs. The result of the renovation of OURAs should contain two aspects: one is the effect of physical space renovation and the other is the effect of collaborative governance on the improvement of public affairs in the renovation of the OURA. Yao and Li pointed that the results of the renovation of OURAs need to be analyzed in terms of both spatial and community governance dimensions [38]. Most previous studies have only considered residents’ satisfaction with spatial materiality and have given less consideration to satisfaction with community governance. Although community participation in the adaptive reuse of old buildings and its advantages for future social well-being have been long-discussed, a governance perspective is not common. OURAs are an important carriers for primary-level governance; therefore, their renovation is an important opportunity to enhance community governance capacity and improve long-term management mechanisms [4]. Therefore, the improvement of collaborative community governance after OURA renovation should also be an important outcome of collaborative renovation.

The spatial material renovation of OURAs focuses on the body of the buildings, the public space, and the service facilities (such as stores, sanitary facilities, etc.); the three aspects are measured separately, and the results represent the degree of satisfaction with the effect of the spatial material renovation on the community after the renovation as a whole. These results can indicate “the renovation of the building body is very satisfactory”, “the renovation of the public space is very satisfactory”, and “the renovation of the service facilities is very satisfactory”.

At present, there are no comprehensive measurement indexes for the collaborative community governance of public affairs in urban communities, so this study selected relevant indexes from the two dimensions of participating subjects and mechanisms of collaboration in urban community governance. The participation of multiple subjects is a source of motivation for community governance, but there is now the problem of the unbalanced and weak participation of subjects in community governance [40]. In particular, community residents, as the direct beneficiaries of participation in community governance, should be the main implementers of the development of community governance of public affairs, and neighborhood committees, social organizations, property companies, and other subjects need to be involved in entering the management of public affairs in the community. Therefore, the degree of participation of residents and other subjects in the management of public affairs in the community can be examined to reflect the degree of improvement in the participation of multiple subjects in community governance. Hence, the improvement of collaborative community governance is measured by “the increase in residents’ participation in the management of public affairs in the community after the renovation”, “the increase in multiple subjects’ participation in public community affairs after the renovation”, “the rational division of power and duties of each subject participating in public community affairs management after the renovation”, “the effectiveness of the demands expression channels after the renovation”, “the effectiveness of the deliberative and consultative platform after the renovation” and “the openness and transparency of information on public affairs after the renovation”. “The openness and transparency of information on public affairs” refers to residents being well-informed about the formulation and implementation of the decision-making process of public affairs [41].

3.2.2. Independent Variables

The independent variables were divided into latent and observational variables. Latent variables cannot be observed or measured directly and need to be represented indirectly using observable variables. Observable variables are variables that can be directly observed and measured. Based on the SFIC model, the study selected starting conditions, institutional design, facilitative leadership, and collaborative process as four latent variables and proposed corresponding theoretical hypotheses. Corresponding observable variables were selected for the measurement of each latent variable.

In the initial SFIC model, the starting conditions include a prehistory of cooperation or conflict, levels of trust, incentives for and constraints on participation, power–resource–knowledge asymmetries, and other related conditions. In China’s renovation of OURAs, there is a common phenomenon of right–resource–knowledge asymmetry, in which the government holds the necessary resources for renovation, such as housing and planning indexes, while the residents have limited knowledge and an insufficient ability to participate [35]. The above asymmetry hinders the joint participation of multiple subjects in renovation governance. Resident participation capacity, which is widely recognized as having much room for improvement, is crucial for the effective participation of residents in the governance of the renovation of OURAs [38]. Past experiences of cooperation and conflict among subjects can affect the initial level of trust between subjects, which in turn affects their participation in collaborative renovation, so a detailed study of past cooperation or conflict among the participants is necessary. Policies related to the renovation of OURAs have an important impact on the participation of subjects in the collaborative governance of renovation, so it is necessary to examine the impact of the degree of policy incentives for all subjects to participate in collaborative renovation and collaborative governance.

Based on the above conclusions, the study selected four observation variables: the degree of asymmetry in subjects’ renovation capability, knowledge, and resources; the degree of policy incentives for subjects’ collaborative governance of the renovation; the complexity degree of property rights; and the subjects’ past experiences of cooperation and conflict. Hypothesis and sub-hypotheses about starting conditions can be found in Table 1.

Institutional design refers to the basic processes and ground rules for cooperation among subjects; relevant institutional frameworks must embody inclusiveness and foster participatory engagement from multiple subjects [7,39]. During OURA renovation, institutional design revolves around how to ensure the participation of residents, the public, and enterprises [42]. The participation of residents as owners not only helps to ensure the legitimacy of the government’s provision of public services for OURA renovation but is also crucial to the smooth promotion of the renovation of OURAs. At present, residents’ participation in the renovation of OURAs is mostly in the process of collecting opinions on renovation wishes, but participation channels in pre-planning, project approval, the selection of cooperative enterprises, and process supervision have not yet been fully established. Establishing and improving flexible and broad financing participation channels for social enterprises is also essential because it can effectively alleviate the financial pressure on government departments [35]. The social enterprise participation mechanism needs to clarify the mode of cooperation, entry and exit mechanisms, operation processes, risk sharing, and benefit distribution for social enterprises. At the same time, non-profit organizations, planners and other experts and scholars, and other members of the public (via social media) should also have clear channels for participation, such as hearings, attendance, spectatorship, and other approaches. Their participation is conducive to the prevention of over-reliance on market mechanisms which may lead to social injustice. Therefore, it is necessary to establish an inclusive mechanism for various subjects to participate in the collaborative governance of the renovation of OURAs.

Subjects involved in OURA renovation often have differentiated interests, with a high probability of triggering complex conflicts of interest. Therefore, it is necessary to establish effective conflict management and emergency response mechanisms [28,30]. Effective conflict management mechanisms should identify potential conflicts and develop avoidance measures and conflict response plans in advance [43].

In order to ensure that all subjects in the OURA renovation process can participate in the governance of public affairs and express their demands, it is necessary to build a deliberative platform in which all subjects can participate. The more common deliberative platforms used in the current stage of OURA renovation include hearings, coordination meetings, and councils, which are often convened by street offices or community neighborhood committees. Such deliberative platforms are characterized by a certain degree of administrative intervention in the process. In addition, owners’ associations, owners’ representative assemblies, building committees, and various types of local mediation groups, help groups, councils, and workshops can also be effective platforms for deliberation. These deliberative platforms are relatively more friendly to residents and social organizations and can reduce a certain degree of administrative reliance. The construction of a deliberative platform is a crucial condition for the realization of democratic consultation in community governance, which requires precise and pragmatic consultation topics, reasonable consultation subjects, standardized consultation procedures, and effective consultation results [44].

Based on the above conclusions, this study selected four observational variables: the establishment of an inclusive participatory mechanism for collaborative renovation, the construction of an effective deliberative platform, the establishment of a conflict management and emergency response mechanism, and the establishment of a reasonable cost- and benefit-sharing mechanism. Hypothesis and sub-hypotheses about institutional design can be found in Table 2.

Facilitative leadership focuses on exercising leadership in collaborative governance processes and facilitating consensus building, which is critical to increasing trust, especially in contexts where there is a power–resource asymmetry or a prehistory of conflict between subjects [7,39]. In the context of urban renewal in China, government departments are often the main guides and organizers. Therefore, it is crucial for government departments to effectively exercise leadership and coordinate the active participation of all subjects in governance. In some cases, government departments authorize consulting companies, such as project management companies, property development companies, or community building consulting companies, to lead and coordinate the renovation process. In addition, in some regions, there has been a gradual emergence of autonomous renewal, in which case self-governing organizations play leading and coordinating roles.

Based on the above conclusions, this study selected four observational variables: the extent to which government departments play a leading and coordinating role, the extent to which social enterprises play a leading and coordinating role, the extent to which residents’ self-governing organizations play a leading and coordinating role, and the extent to which social organizations play a leading and coordinating role. Hypothesis and sub-hypotheses about facilitative leadership is as Table 3 shows.

A collaborative process is seen as central to collaborative governance as a whole, mainly because governance is seen as an interactive process rather than a linear development. Face-to-face dialogue, trust building, commitment to the process, shared understandings, and intermediate outcomes are critical factors that influence the outcomes of collaborative governance [7,39]. The establishment of the rule of procedure and channels for dialogue and consultations facilitates the realization of face-to-face dialogue. Face-to-face dialogues are conducive to fostering confidence and promoting cooperation among subjects. Reaching intermediate outcomes in the OURA renovation process, such as feasible design, financing, and cost-sharing programs, plays a crucial role in collaborative governance. Renovation projects are difficult to promote if the above issues make it difficult to form intermediate outcomes [31]. Consultations and consensus building in the OURA renovation process are important for stakeholders to remain satisfied [35]. The timely disclosure and transparency of project-related information form the basis for understanding, feedback, and ultimately consensus among stakeholders [31].

Based on the above conclusions, this study selected six observational variables: conducting effective conflict management, building mutual trust among subjects, face-to-face dialogue and consultation, reaching an intermediate consensus, information disclosure and transparency, and the level of awareness of interdependence among subjects. Hypothesis and sub-hypotheses about collaborative processes can be found in Table 4.

3.2.3. Control Variables

In addition to the above latent variables, demographic information from respondents, such as age, gender, institutional affiliation, province and city, and education level, were selected as control variables.

3.2.4. Construction of Theoretical Models

Based on the selected influencing elements and hypotheses, this section proposes a theoretical model of multiple subjects’ collaborative governance of OURA renovation, as shown in Figure 2. The model reveals how the interaction of critical elements, such as starting conditions, institutional design, facilitative leadership, and collaborative processes, can work together to promote effective collaborative governance in OURA renovation.

4. Methodology

4.1. Structural Equation Modeling (SEM)

Structural Equation Modeling (SEM) was used to test the proposed hypotheses. SEM is a comprehensive statistical technique that combines the features of factor analysis and path analysis to test causal relationships among variables and build structural models [45]. SEM can consider causal relationships between multiple variables simultaneously and is suitable for validating complex theoretical frameworks. SEM is divided into two parts: measurement modeling, which reflects the latent variables with observed variables, and structural modeling, which represents the causal relationship between latent variables. The measurement model consists of latent and observed variables, and the mathematical expression is as follows:

(1)$X=A_X\xi +\delta$

(2)$Y=A_Y\mathsf{\eta }+\mathsf{\epsilon }$

$X$ represents the exogenous observed variable, Y represents the endogenous observed variable, A_X represents the Coefficient Matrix between X and ξ, A_Y represents the Coefficient Matrix between Y and η, ξ represents the exogenous latent variable, η represents the endogenous latent variable, δ represents the X variable measurement error, and ε represents the Y variable measurement error.

The structural modeling defines the relationships between latent variables and is usually presented in the form of path diagrams that represent the causal relationships between variables. The mathematical expression is as follows:

(3)$\eta =B\eta +C\xi +\mathsf{\zeta }$

η represents the endogenous latent variable, ξ represents the exogenous latent variable, B represents the Coefficient Matrix among endogenous latent variables, C represents the Coefficient Matrix between ζ and η, and ζ represents the residual.

Four steps were used to analyze the data: The first step was the reliability and validity assessment of the model. Structural modeling was constructed afterwards and its goodness-of-fit between the theoretical model and collected data was tested using CFI, TLI, RMSEA, and other metrics. The structural model was adjusted so that the collected data could be best explained.

4.2. Data Collection

4.2.1. Questionnaire Design

The primary data was collected through questionnaire surveys. The latent variables, such as starting conditions, institutional design, collaborative processes, and collaborative outcomes, selected for this study are difficult to describe through objective data in the process of OURA renovation; therefore, subjective measures needed to be set up to describe them. Observational variables such as the degree of asymmetry in the subjects’ renovation capacity, knowledge, and resources, and the degree of incentives provided by policies for the subjects to participate in collaborative renovation are still difficult to characterize using objective data, and required the further selection of observational variables [7,39]. Hence, this study further selected more than three measures for each variable, and these multiple measures helped provide a comprehensive view of the variables and reduce measurement error. Measurement indicators were prioritized for those that had been tested for reliability and validity in the literature. For individual variables that were difficult to search for in the literature, measurement indicators were selected based on the project team’s understanding of OURA renovation.

Three experts were invited to discuss the variables and adjust them. To ensure that the questionnaire was easy to understand, 25 people representing the different subjects involved in OURA renovation were invited to conduct a pre-survey. The questionnaire was adjusted based on feedback from the pre-survey, and the adjusted final version was used for data collection.

The questionnaire was divided into six sections: (1) demographic information of respondents, (2) starting condition variables, (3) institutional design variables, (4) facilitative leadership variables, (5) collaborative process variables, (6) collaborative outcomes. The questionnaire was formulated using a Likert scale (taking values 1–5). The five measurement levels were strongly disagree, disagree, slightly agree, agree, and strongly agree. All questionnaire respondents were anonymized to protect their information. The selection of variables and the setting of specific questions are presented in Table 5.

4.2.2. Questionnaire Distribution and Collection

This study used purposive sampling for sample selection. Samples were selected from representatives of the participating subjects of OURA renovation best practice cases selected by the MoHURD. These cases were typical OURA renovation projects which were usually successfully completed and achieved better outcomes, thus representing successful collaborative governance. The questionnaire was distributed through WJX.cn, an online survey platform in China. WJX.cn users can upload questionnaires and generate unique QR codes. Respondents can conveniently fill out the questionnaire using their mobile phones by scanning the QR code. The questionnaire was distributed to all relevant subjects of the renovations of OURAs through the Provincial Department of Housing and Urban-Rural Development from 1 November 2024 to 31 November 2024. A total of 1091 questionnaires were collected, of which 853 were valid and met the data requirements for the study.

4.2.3. Sample Descriptive Analysis

The details of the respondents are shown in Table 6. The gender, age, education, and subject composition of the current sample showed a certain regularity, which represented the overall sample characteristics more comprehensively and was suitable for subsequent in-depth analysis.

5. Findings and Analysis

5.1. Reliability and Validity Assessment

5.1.1. Reliability Assessment

Reliability assessments are often used to measure the reliability of results, and Cronbach’s α reliability coefficient method was used to test the reliability of the questionnaire. In this study, reliability assessment was conducted using SPSS 27.0, as shown in Table 7 and Table 8. The overall Cronbach’s α value of the questionnaire is greater than 0.8, and Cronbach’s α for each variable is greater than 0.8, which meets the criteria and indicates that the reliability assessment is qualified and there is no need to adjust the questionnaire.

5.1.2. Validity Assessment

Validity assessments are used to evaluate the validity of the results measured using a measurement instrument. Validity is divided into content validity and construct validity. Content validity refers to the extent to which the content of the questionnaire conforms to the topic of the study and whether the questions are designed to be representative. Content validity is typically evaluated using qualitative analysis. In this study, each variable was given a clear definition, and the research hypotheses and questionnaire design were supported by the literature; therefore, it can be considered that the content validity met the requirements.

Construct validity refers to the extent to which variables conform to the structure of theoretical assumptions. Construct validity is usually tested using confirmatory factor analysis (CFA), which serves to test the fit of the hypothesized model to the data. Before the CFA, KMO and Bartlett’s test of sphericity are needed to determine whether the analysis requirements are satisfied. KMO and Bartlett’s test of sphericity were performed by SPSS 27.0 to determine whether the analysis validity requirements were satisfied. The results are shown in Table 9. The KMO coefficient should generally be greater than 0.7, and the results of Bartlett’s test of sphericity should be significant. It can be seen in the results that KMO coefficient = 0.976 > 0.7 and Bartlett’s test of sphericity is significant (p < 0.001).

CFA includes convergent validity, discriminant validity, and model fit validity. Convergent validity refers to the degree of correlation between a set of observed variables. It is generally measured by the average variance extracted value (AVE) and combined reliability (CR). Typically, when the factor loading value is greater than 0.6, the AVE is greater than 0.5, and the CR is greater than 0.8, this indicates ideal convergent validity between the variables. In this paper, CFA was conducted for five factors and 70 analyzed items. The results show that the AVE values of H1a, H1c, H2a~H2d, H3a, H3c, and H4a~H4e are all greater than 0.5 and the CR values of the combined reliabilities are all higher than 0.8. The remaining variables (H1b, H1d, H3b, H3d, and H4f) did not meet the requirements and were excluded from the analysis.

Discriminant validity refers to the statistical demonstration in a test that an indicator that is not theoretically correlated with a predetermined variable construct is indeed uncorrelated with that variable construct. The discriminant validity is generally characterized by the AVE square root value. As shown in Table 10, the square root of the AVE of the starting condition, institutional design, facilitative leadership, and collaborative process variables are higher than their respective maximum values for the absolute values of the inter-factor correlation coefficients. This means that the data in this analysis have significant discriminant validity.

Model fit validity refers to the extent to which the sample statistics match the model hypotheses and requires validation by importing the observed data into Structural Equation Modeling. AMOS 27.0 was used to test the model fit by obtaining the fit index and judging the match between the model and the actual data, so as to verify the reasonableness and validity of the theoretical hypotheses. As shown in Table 11, the CMIN/DF is 4.216, which satisfies the fitting criterion of less than 5; the RMSEA is 0.061, which satisfies the fitting criterion of the interval of 0.05–0.08; and the five indicators of CFI, TFI, IFI, RFI, and NFI are greater than 0.90, which satisfies the corresponding criteria. Thus, the model was well-fitted.

The validity analysis showed that this questionnaire was well designed and that the data obtained accurately reflected the variables that needed to be measured and satisfied the requirements of the theoretical model that needed to be validated.

5.2. Hypothesis Tests

Based on the SEM, the significance of each path was tested to confirm whether the hypotheses were valid. The direct and indirect effects between the latent variables and their significance were assessed by analyzing path coefficients. The direct effects between the variables were assessed using standardized path coefficients. The path coefficients of the action of each critical success factor and their significance are shown in Table 12. The standardized path coefficients of institutional design, facilitative leadership, and collaborative process on collaborative outcomes are 0.356, −0.276, and 0.788, while the p-values are all less than 0.05, which suggests that institutional design and collaborative process have a significant positive effect on collaborative outcomes and facilitative leadership has a negative effect on collaborative outcomes. The starting conditions p-value is greater than 0.05, meaning that the result is not significant and the hypothesis is not valid. The model path analysis is illustrated in Figure 3.

5.3. Mediation Analysis

The mediation coefficient indicates the strength and direction of the effect of an independent variable on the dependent variable (collaborative outcomes) through a mediating variable. In this study, the Bootstrap method was applied to test the mediating effect. It is generally believed that when the Bootstrap confidence interval does not include 0, this indicates the existence of mediation effects. The test results are shown in Table 13.

As can be seen from Table 13, several paths show significant mediation effects, while the mediation effect of the last path is not significant. The specific analyses are as follows:

The collaborative process is an important mediating variable on the impact of starting conditions, institutional design, and facilitative leadership on collaborative outcomes. Institutional design and facilitative leadership had a significant positive mediating effect on collaborative outcomes through the collaborative process. Specifically, the mediation coefficient of institutional design on collaborative outcomes through the collaborative process was 0.558 (confidence interval: [0.389, 0.724]; p = 0.01). The mediation coefficient of facilitative leadership on collaborative outcomes through the collaborative process was 0.852 (confidence interval: [0.564, 1.154]; p = 0.01). The mediating effects of both paths were positive and significant, indicating that institutional design and facilitative leadership contributed to improved collaborative outcomes through the collaborative process. The starting conditions had a significant negative mediating effect on collaborative outcomes through the collaborative process. The mediation coefficient of starting conditions on collaborative outcomes through the collaborative process was 0.852 (confidence interval: [0.564, 1.154]; p = 0.01), indicating that starting conditions inhibited improved collaborative outcomes through the collaborative process.

The starting conditions had a significant negative mediating effect on collaborative outcomes through collaborative processes, facilitative leadership, and institutional design. Specifically, the mediation coefficient of the starting conditions on the collaborative outcomes through the collaborative process was −0.119 (confidence interval: [−0.184, −0.062]; p = 0.01); the mediation coefficient of the starting conditions on the collaborative outcomes through facilitative leadership was −0.120 (confidence interval: [−0.183, −0.068]; p = 0.01); and the mediation coefficient of the starting conditions on the collaborative outcomes through institutional design was −0.127 (confidence interval: [−0.192, −0.0075]; p = 0.01).

The mediating effect of institutional design on collaborative outcomes through facilitative leadership was not significant. In this path, the mediation coefficient of institutional design on collaborative outcomes through facilitative leadership was 0.188 (confidence interval: [−0.129, 0.617]; p = 0.225). The confidence interval crosses 0, and the p-value is greater than 0.05, indicating that the mediating effect of this path is not statistically significant.

The above results indicate that starting conditions, institutional design, and facilitative leadership play important roles in the collaborative governance process. Starting conditions negatively affect collaborative outcomes through multiple mediating variables, whereas institutional design and facilitative leadership positively affect collaborative outcomes through the collaborative process.

This study also tested the mediating effects between the observed variables of each latent variable. As the results show in Table 14, the confidence intervals for the mediating effects of all the paths do not contain 0, which indicates that the mediating effects of all the paths are statistically significant. The p-values for all the paths were less than 0.05, further confirming the statistical significance of these mediating effects. These results demonstrate the validity and reliability of the model, revealing the intrinsic linkages and influence mechanisms among the observed variables.

The results in Table 14 show that H4e (information disclosure and transparency) is a significant mediating variable for the collaborative outcomes of H3a (government departments play a leading and coordinating role), H3c (residents’ self-governing organizations play a leading and coordinating role), H2b (construction of an effective deliberative platform), and H2a (establishment of an inclusive participatory mechanism for collaborative renovation), with mediation effect coefficients of 0.673, 0.526, 0.555, and 0.528, respectively.

H4b (building mutual trust among subjects) is a significant mediating variable for the collaborative outcomes of H3a (government departments play a leading and coordinating role), with a mediation effect coefficient of 0.555. H4c (face-to-face dialogue and consultation) is a significant mediating variable for the collaborative outcomes of H3a (government departments play a leading and coordinating role), with a mediation effect coefficient of 0.612. H4d (reaching an intermediate of consensus) is a significant mediating variable for the collaborative outcomes of H3a (government departments play a leading and coordinating role), with a mediation effect coefficient of 0.528. The results suggest that if government departments play a facilitative leadership role in OURA renovation, it is necessary to ensure that the subjects build mutual trust, establish face-to-face dialogues and consultations, and reach an intermediate consensus so that collaborative outcomes can be improved.

5.4. Analysis of Factors Influencing Collaborative Community Governance Improvement

This study found that the establishment of an inclusive participatory mechanism for collaborative renovation (H2a), residents’ enhanced collaborative community governance through face-to-face dialog and consultation (H4c), and information disclosure and transparency (H4e) influenced collaborative governance. The constructs enhancing an effective deliberative platform (H2b) and H2c (the establishment of a conflict management and emergency response mechanism) significantly enhanced collaborative community governance through face-to-face dialogue and consultation (H4c) and information disclosure and transparency (H4e). Government departments play a leading and coordinating role (H3a) in significantly enhancing collaborative community governance through conducting effective conflict management (H4a), building mutual trust among subjects (H4b), and face-to-face dialogue and consultation (H4c). The residents’ self-governing organizations play a leading and coordinating role (H3c) and the social organizations play a leading and coordinating role (H3d) in significantly enhancing collaborative community governance through face-to-face dialogue and consultation (H4c) and information disclosure and transparency (H4e).

This study analyzes the mediating effects of the variables affecting collaborative community governance improvement (see Table 15). Face-to-face dialogue and consultation (H4c) is a significant mediating variable for improving collaborative community governance by establishing an inclusive participatory mechanism for collaborative renovation (H2a), constructing an effective deliberative platform (H2b), government departments playing a leading and coordinating role (H3a), and residents’ self-governing organizations playing a leading and coordinating role (H3c), with mediation effect coefficients of 0.563, 0.555, 0.741, and 0.559, respectively. Information disclosure and transparency (H4e) is a significant mediating variable for collaborative community governance improvement through the establishment of an inclusive participatory mechanism for collaborative renovation (H2a), the construction of an effective deliberative platform (H2b), the establishment of a conflict management and emergency response mechanism (H2c), government departments playing a leading and coordinating role (H3a), and residents’ self-governing organizations playing a leading and coordinating role (H3c), with mediation effect coefficients of 0.637, 0.673, 0.591, 0.818, and 0.626, respectively. The results suggest that in order to improve collaborative community governance in the renovation of OURAs, face-to-face dialogues and consultations and information disclosure and transparency play very important mediating roles.

5.5. Model Adjustment

In the proposed theoretical model of the influence mechanism of multiple subjects’ collaborative governance, 18 hypotheses are valid and 4 hypotheses are not valid, as shown in Table 16. The model was adjusted based on the results of hypothesis validation, and the adjusted model is shown in Figure 4.

6. Discussion

This paper adopts the adjusted general collaborative governance theoretical framework to explore the critical elements and formation mechanism of collaborative governance by multiple subjects in OURA renovation. This study found that institutional design, facilitative leadership, and collaborative processes all have a positive impact on collaborative outcomes, and that collaborative processes are an important mediating variable on collaborative outcomes. Meanwhile, this study found that the establishment of an inclusive participatory mechanism for collaborative renovation, the construction of an effective deliberative platform, the establishment of conflict management and emergency response mechanisms, government departments playing a leading and coordinating role, and residents’ self-governing organizations playing a leading and coordinating role are important influences on collaborative community governance improvement. Face-to-face dialogue, consultation, information disclosure, and transparency are mediating variables that affect collaborative community governance improvement.

6.1. The Mixture of a Top-Down Approach and a Bottom-Up Approach in Chinese OURA Renewal

This round of OURA renovation in China has the characteristics of both top-down and bottom-up approaches long-discussed in academia. Specifically, the current round of OURA renovation is mainly driven by the government. The overall work plan and implementation are led by the government, which is the most important feature of a top-down approach. However, renovation differs from the conventional adaptive reuse (top-down approach) proposed by Yung et al [41]. in several aspects. The most important point is that this round of OURA renovation does not demolish old buildings but makes minor renovations to existing ones. Renovating and updating old residential buildings means that the original residents do not have to leave their original living community, and the original community and lifestyle can be preserved [45].

This round of OURA renewal mainly relies on government funds, and the government’s financial pressure is relatively high. Although some social enterprises have entered this market to invest, their proportion is not high. The dilemma of enterprises participating in OURA renewal leads to the suspicion that OURA renovation in China cannot continue to be sustainable [47]. Real estate enterprises have found that the previous business model of demolition, rebuilding, and sale is no longer effective. Most enterprises find it difficult to obtain appropriate investment returns from investing in the renovation of old residential areas, so they lack the motivation to participate.

The role of residents in the OURA renovation process has been addressed to a certain degree. Residents are invited to participate in renovation design, and their agreement with the renovation plan is of great significance. The residents’ consent rate of the renovation plan must reach more than two-thirds, otherwise the OURA renovation is not allowed. In some cities, the proportion requirement may be even higher. In this way, residents become an important subject in the OURA renewal process. Collaborative governance involving these subjects has become increasingly crucial.

6.2. Collaborative Process Deserves More Attention During OURA Renovation

The collaborative process has been found to be an important mediating variable on the impact of starting conditions, institutional design, and facilitative leadership on collaborative outcomes. Institutional design and facilitative leadership had a significant positive mediating effect on collaborative outcomes through the collaborative process. This is consistent with Ansell and Gash’s emphasis on the collaborative process in their original theoretical model of collaborative governance [7]. The collaborative process is argued to be the central aspect of collaborative governance and should be viewed as an interactive process rather than a linear development. In the collaborative governance process for OURA renovation, emphasis should be placed on information disclosure and transparency, face-to-face dialogues and consultations, and helping subjects build mutual trust and reach an intermediate consensus. Information management should be strengthened during OURA renovation to ensure that project information is disclosed in a timely and accurate manner to project stakeholders such as property owners and the public. This not only protects their right to know, but also builds a foundation for their participation in the renovation and improves the efficiency of the renovation [30,31]. Face-to-face dialogues and consultations can facilitate communication between the subjects, build social networks between them, enhance trust between them, and strengthen the collaborative process of OURA renovation [49]. Therefore, in subsequent OURA renovation processes, there is a need to focus on information disclosure and transparency and to realize face-to-face dialogue and consultation. The subjects involved in the renovation process need to reach an intermediate consensus, including feasible financing options, feasible design options, and other decision-making elements that are critical to the advancement of the renovation, directly affecting the success of collaborative governance [32].

6.3. Multi-Dimensional Promotions of Collaborative Community Governance Long-Term Improvement

The establishment of inclusive participatory mechanisms, effective deliberative platforms, conflict management and emergency response mechanisms, and facilitative leadership by the government and residents’ self-governing organizations all have a significant impact on public affairs governance. The participation of multiple subjects, including street offices, community neighborhood committees, community residents, and property companies, is a source of strength in the dynamics of community governance [40]. The need for residents to participate in community governance as an important community subject has been widely recognized by the academic community. However, the governance capacity, knowledge, and resources of resident subjects are still insufficient, so the establishment of an inclusive participatory mechanism is important.

The establishment of an effective deliberative platform is the key to resolving the current problem of heavy dependence on administrative means to promote OURA renovation. These include more formal deliberative platforms, such as owners’ associations, owners’ councils, and building committees, as well as informal voluntary groups in which various types of residents participate on their own initiative. Informal groups will play a greater role in future OURA renovation, helping to cultivate collaborative community governance [38]. There is currently a more pronounced asymmetry in the capacity–knowledge–resources of the subjects, and residents’ governance capacity is especially weak [40]. Therefore, at the initial stage of cultivation, existing street offices and community neighborhood committees still need to take the initiative to play a role and actively participate in the cultivation of various types of deliberation platforms, provide venues and financial support to promote the long-term operation of deliberation platforms, and cultivate the endogenous momentum of community governance.

Effective conflict management and emergency responses are critical factors in collaborative governance [28,30]. Because the values and interests of multiple subjects are different and change during renovation processes, it is not uncommon for contradictions and conflicts to emerge among subjects. Therefore, it is necessary to identify possible conflicts in advance during the renovation process and develop corresponding avoidance or response programs [43]. In order to effectively mitigate or resolve conflicts, it is important to choose appropriate methods in the process and try to make the subjects feel that it is fair.

It should be noted that information disclosure, transparency, face-to-face dialogue, and negotiation are important mediating variables that enhance collaborative community governance. Negotiation in public community affairs should focus on public space, authorized space, communication, accountability, meta-negotiation, and decision-making power [56]. To ensure the quality of the consultative platform, a comprehensive consideration of the various components is required. Fishkin [58] proposes to measure the quality of consultation in terms of five dimensions: the adequacy of information, substantive balance among subjects, diversity of participation, conscientiousness of participation, and fairness. The gradual development from mandatory to mobilized consultation and even autonomous consultation in the process of the governance of public affairs in China’s communities requires a long period of experimentation and work [57].

6.4. Embracing New Technologies to Facilitate Collaborative Governance

It is time to embrace new technologies, such as virtual reality and 3D modeling, to facilitate the improvement of inclusive participatory mechanisms, effective deliberative platforms, and conflict management. Recent research has revealed that new technologies, such as virtual reality and 3D modeling, have a positive effect on improving public engagement in urban renewal [59,60,61,62]. For example, VR has been found to have a positive effect on enhancing understanding of designs and providing immersive environments that help residents understand proposed renovation plans [63]. Three-dimensional modeling technologies can visualize existing neighborhood conditions and enable side-by-side comparisons with future renovation scenarios [64]. Simulation software can demonstrate changes in the wind environment of buildings [65]. Hence, further OURA renovation could consider utilizing these technologies to facilitate collaborative governance.

7. Conclusions and Limitations

7.1. Conclusions

This paper is dedicated to exploring the critical elements and formation mechanism of the collaborative governance by multiple subjects in OURA renovation. Multiple subjects’ collaborative governance in OURA renovation is not only very important to improving the physical material and space of communities, but also more importantly to promoting the enhancement of collaborative community governance capacity. This study bridges the gap in the existing literature concerning the lack of systematic quantitative research on the formation mechanism of collaborative governance by multiple subjects in OURA renovation.

This paper adopts the general collaborative governance theoretical model proposed by Ansell and Gash as its theoretical basis, which can open the “black box” of multiple subjects’ collaborative governance in OURA renovation [7]. The general collaborative governance theoretical model was adjusted according to the OURA renovation context, and the improvement of collaborative community governance was introduced as an important variable of collaborative outcomes. Then we collected 853 questionnaires that were analyzed by SEM. The empirical results demonstrate the effects and paths of starting conditions, institutional design, facilitative leadership, and collaborative processes on collaborative governance outcomes in OURA renovation.

This study found that the starting conditions, such as the degree of asymmetry in the subjects’ renovation capabilities, knowledge, and resources, and the complexity of property rights, have a significant negative impact on the collaborative governance of OURA renovation, indicating that resource asymmetry and property rights issues are important hindrances to collaborative governance. Hence, in order to reduce the asymmetry in subjects’ renovation capabilities, knowledge, and resources, local government agencies such as sub-district offices and neighborhood committee should provide more opportunities for residentials to practice their knowledge and capabilities on participatory regeneration. New technologies, such as VR and simulation software, can be used to provide a transformative approach for residential buildings to improve their renovation capabilities and knowledge.

In terms of institutional design, the establishment of an inclusive participatory mechanism for collaborative renovation, construction of an effective deliberative platform, establishment of conflict management and emergency response mechanisms, and establishment of a reasonable cost- and benefit-sharing mechanism all had a significant and positive impact on collaborative governance, highlighting the critical supportive role of a sound institutional system in collaborative governance.

In terms of facilitative leadership, the leading and coordinating role played by government departments, enterprises, residents’ self-governance organizations, and social organizations all contribute positively to collaborative community governance improvement, reflecting the positive effectiveness of the pluralistic leadership model in the renovation process. Hence, enterprises and residents’ self-governance organizations could participate in OURA renovation more actively so that the community governance capability could be improved and sustained after the renovation.

In terms of the collaborative process, elements such as effective conflict management, the build of mutual trust among subjects, face-to-face dialogue and consultation, the achievement of an intermediate consensus, and information disclosure and transparency have significant positive impacts on the collaborative outcomes, indicating that these elements are the core links to guaranteeing the effective promotion of collaborative governance. However, the level of awareness of interdependence among the subjects did not have a significant direct effect. The study further found that the collaborative process played an important mediating role between the starting conditions, institutional design, facilitative leadership, and collaborative outcomes, suggesting that the collaborative process is the critical link between the critical elements and the final collaborative outcomes. Facilitative leadership and institutional design also played mediating roles between the starting conditions and the collaborative outcomes, which further revealed the complexity of the linkages among the elements. Government departments and residents’ self-governing organizations play important roles in enhancing collaborative community governance. Face-to-face dialogue and consultation, information disclosure and transparency, and reaching an intermediate consensus are very important mediator variables, indicating that effective participatory mechanisms, transparency, and trust building are crucial to the collaborative community governance improvement.

7.2. Limitations and Future Directions

This study still has some limitations which could be improved in future studies. First, questionnaires were distributed from the provincial Housing and Urban-Rural Development Department to the municipal Housing and Urban-Rural Development Bureau and then to multiple subjects of OURA renovation projects. A large amount of data was collected effectively using this method. But we also admit that there may be a certain probability that this method may have an impact on the answers of the resident respondents. In order to circumvent this possibility and reduce the degree of influence, the research team emphasized to the staff who helped distribute the questionnaires that this study is only for academic research and does not have any influence on the evaluation of local work. Also, respondents were assured at the beginning of the questionnaire that the questionnaires were only used for academic research and that anonymity had been adopted to protect their information. The likelihood of respondents being subjected to local government interference was minimized by the three above methods.

Second, the sample of this study covers 16 provinces in China, and the starting conditions, governmental governance tendency, and degree of residents’ participation vary from city to city. The data can be further studied by applying Multilevel Structural Equation Modeling or Multi-Group Structural Equation Modeling to explore the formation mechanisms of collaborative governance by multiple subjects in OURA renovation in different cities. Different cities vary in aspects such as socioeconomic status and urban development level, the effects of which on community collaborative governance require further exploration.

Third, although this study innovatively introduced the improvement of collaborative community governance into the collaborative outcomes and analyzed its influencing elements and generating paths, the measurement of the degree of collaborative community governance has not yet matured because research on community governance in China is in its early stages, and more exploration can be performed in this area in the future. The influence of collaborative governance on future renovation institutional design, collaborative processes, and facilitative leadership should be studied further. Also, community collaborative governance dynamics deserve further exploration, particularly the interactions between residents’ experience and governance context. Research methods such as Qualitative Comparative Analysis, realist evaluation, or participatory action research could be mobilized to conduct these studies.

Fourth, the role of new technologies, such as virtual reality and 3D modeling, in improving public engagement and collaborative governance in urban renewal deserves further exploration.

Author Contributions

Conceptualization, B.Q.; methodology, B.Q. and P.W.; software, P.W.; validation, S.H. and Y.L.; formal analysis, S.H. and P.W.; investigation, B.Q. and Y.L.; resources, B.Q.; data curation, P.W.; writing—original draft preparation, B.Q. and S.H.; writing—review and editing, S.H.; visualization, P.W.; supervision, B.Q.; project administration, B.Q.; funding acquisition, B.Q. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

Data is available when required.

Conflicts of Interest

Author Peifeng Wu was employed by the company Beijing Urban Construction Group Co., Ltd. (BUCG). The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Abbreviations

The following abbreviations are used in this manuscript:

OURA	Old Urban Residential Area
SFIC	Starting Conditions–Facilitative Leadership–Institutional Design–Collaborative Process
SEM	Structural Equation Modeling

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figures and Tables

Figure 1 The SFIC theoretical model synergistic process schematic diagram (cite from Ansell and Gash [7]).

Figure 2 A theoretical model of the formation mechanism of multiple subjects’ collaborative governance of OURA renovation.

Figure 3 Model path analysis.

Figure 4 Adjusted model of OURA renovation collaborative governance formation mechanism.

Table 1

Hypothesis and sub-hypotheses about starting conditions.

Main Hypothesis	Sub-Hypotheses
H1: Favorable starting conditions have a positive impact on the collaborative governance of OURA renovation.	H1a: The degree of asymmetry in the subjects’ renovation capacity, knowledge, and resources has a negative impact on the collaborative governance of OURA renovation.
	H1b: The extent to which policies incentivize subjects to participate in collaborative renovation has a positive impact on the collaborative governance of OURA renovation.
	H1c: The complexity of property rights has a negative impact on the collaborative governance of OURA renovation.
	H1d: The subjects’ past experiences of satisfactory cooperation have a positive impact on the collaborative governance of OURA renovation.

Table 2

Hypothesis and sub-hypotheses about institutional design.

Main Hypothesis	Sub-Hypotheses
H2: A comprehensive institutional design has a positive impact on the collaborative governance of OURA renovation.	H2a: The establishment of an inclusive collaborative renovation participation mechanism has a positive impact on the collaborative governance of OURA renovation.
	H2b: The construction of an effective deliberative platform has a positive impact on the collaborative governance of OURA renovation.
	H2c: The establishment of conflict management and emergency response mechanisms has a positive impact on the collaborative governance of OURA renovation.
	H2d: The establishment of a reasonable cost- and benefit-sharing mechanism has a positive impact on the collaborative governance of OURA renovation.

Table 3

Hypothesis and sub-hypotheses about facilitative leadership.

Main Hypothesis	Sub-Hypotheses
H3: Effective leadership has a positive impact on the collaborative governance of OURA renovation.	H3a: The primary leadership and coordination role of government departments has a positive impact on the collaborative governance of OURA renovation.
	H3b: The primary leadership and coordination role of social enterprises has a positive impact on the collaborative governance of OURA renovation.
	H3c: The primary leadership and coordination role of residents’ self-governing organizations has a positive impact on the collaborative governance of OURA renovation.
	H3d: The primary leadership and coordination role of social organizations has a positive impact on the collaborative governance of OURA renovation.

Table 4

Hypothesis and sub-hypotheses about collaborative processes.

Main Hypothesis	Sub-Hypotheses
H4: Cooperative collaborative processes have a positive impact on the collaborative governance of OURA renovation.	H4a: Effective conflict management has a positive impact on the collaborative governance of OURA renovation.
	H4b: Building mutual trust among subjects has a positive impact on the collaborative governance of OURA renovation.
	H4c: Face-to-face dialogue and consultation have a positive impact on the collaborative governance of OURA renovation.
	H4d: Reaching an intermediate of consensus has a positive impact on the collaborative governance of OURA renovation.
	H4e: Information disclosure and transparency have a positive impact on the collaborative governance of OURA renovation.
	H4f: The level of awareness of interdependence among subjects has a positive impact on the collaborative governance of OURA renovation.

Table 5

Variable selection and sources.

Variable	Observed Variable	Code	Questions	References
Starting conditions	Degree of asymmetry in subjects’ ability to renovate, knowledge, and resources	SCKA1	There is a particular asymmetry in the capacity of each subject to renovate (e.g., handling of project approval procedures, hiring of construction and design firms, coordination of the interests of all parties, etc.).	Yao and Li [38]; Zhu and Gao [35].
		SCKA2	There is a particular asymmetry in the resources (e.g., funding, land, etc.) that subjects have for renovation.
		SCKA3	There is a particular asymmetry in the knowledge (e.g., policy utilization, project design, project management, etc.) that subjects have for renovation.
	Degree of policy incentives for concerted renovation of the subjects	SCI1	The government publicizes and helps subjects understand the policies related to the renovation of OURA through a variety of means.	Liu and Zhou [46].
		SCI2	There is government support for the process of the renovation of OURAs.
		SCI3	The government guides the participation of all subjects in the process of renovation of OURAs.
	Degree of complexity of property rights	SCP1	Multiple ownership units are involved in the renovation of the community.	Wang et al. [2].
		SCP2	There has been incomplete transfer of property rights in the common parts of a remodeled community to the residential property owner.
		SCP3	A portion of the housing stock in the rehabilitation area has not been subject to housing reforms.
	Subjects’ past experiences of cooperation and conflict	SCE1	The participants had some positive basis for cooperation prior to the renovation.	Ansell and Gash [7].
		SCE2	The participants had some experience of conflict prior to the renovation.
		SCE3	Prior to the retrofit, we trusted that the other participants would keep their word during the retrofitting process.
Institutional design	Establishment of inclusive participatory mechanism	IDP1	There are clear ways, processes, and rules for residents to participate in the renovation process.	Liu et al. [47]; Zhu and Gao [35]; Liu et al. [28]; Du [30].
		IDP2	There are clear ways, processes, and rules for social organizations to participate in the renovation process.
		IDP3	There are clear ways, processes, and rules for social enterprises to participate in the renovation process.
		IDP4	There are clear ways, processes, and rules for planner and scholar to participate in the renovation process.
	Construction of effective deliberative platform	IDNP1	Precise and pragmatic consultation topics of the deliberative platform in the renovation process	Zheng et al. [48].
		IDNP2	There is a reasonable composition of subjects on the deliberative platform during the renovation process.
		IDNP3	There are clear consultation procedures and processes for the deliberative platform during the renovation process.
		IDNP4	There is efficient implementation of the results of the deliberations in the renovation process.
	Establishment of conflict management and emergency response mechanisms	IDCM1	Potential conflicts are identified in advance of renovation	Wu et al. [49]; Zhu et al. [43].
		IDCM2	Subdivisions are designed to avoid potential conflicts prior to renovation.
		IDCM3	Prior to the renovation, a response plan was developed to address potential conflicts.
	Establishment of reasonable cost- and benefit-sharing mechanism	IDCB1	A clear cost-sharing approach for the renovation of the OURA was developed.	Ding et al. [50].
		IDCB2	A clear benefit-sharing approach for the renovation of the OURA was developed.
		IDCB3	Reasonable proportions of costs and benefits were allocated to the renovation of the OURA.
Facilitative leadership	Government departments play leading and coordinating role	FLG1	Government departments have facilitated the participation of subjects in collaborative renovation.	Vogel and Masal [51]; Muravu [52].
		FLG2	Governmental departments have facilitated dialogic negotiations among the subjects.
		FLG3	Government departments have actively coordinated the needs of all subjects.
		FLG4	Government departments greatly influence the remodeling process.
	Social enterprises play leading and coordinating role	FLE1	The social enterprises have facilitated the participation of subjects in collaborative renovation
		FLE2	Social enterprises have facilitated dialogic negotiations among the subjects.
		FLE3	Social enterprises have actively coordinated the needs of all subjects.
		FLE4	Social enterprises greatly influence the remodeling process.
	Residents’ self-governing organizations play leading and coordinating role	FLRO1	The residents’ self-governing organizations have facilitated the participation of subjects in collaborative renovation
		FLRO2	Residents’ self-governing organizations have facilitated dialogic negotiations among the subjects.
		FLRO3	Residents’ self-governing organizations have actively coordinated the needs of all subjects.
		FLRO4	Residents’ self-governing organizations greatly influence the remodeling process.
	Social organizations play leading and coordinating role	FLSO1	Social organizations have facilitated the participation of subjects in collaborative renovation.
		FLSO2	Social organizations have facilitated dialogic negotiations among the subjects.
		FLSO3	Social organizations have actively coordinated the needs of all subjects.
		FLSO4	Social organizations greatly influence the remodeling process.
Collaborative process	Conduct effective conflict management [49]	CPCM1	Different approaches have been chosen to deal with different conflict events during the renovation.	Wu et al. [49]; Zhu et al. [43].
		CPCM2	Conflict handling during the renovation process was chosen to be as fair as possible.
		CPCM3	Conflicts in the renovation process are mitigated or resolved when addressed.
	Build mutual trust among subjects	CPT1	Participants in the renovation process are able to negotiate at a fair level.	Adobor [53]; McEvily and Tprtoriello [52]; Lann et al. [54].
		CPT2	Participants in the renovation process are able to negotiate honestly.
		CPT3	We trust that the other participants will keep their word during the renovation process.
	Face-to-face dialogue and consultation	CPFD1	There was face-to-face dialogue between subjects encountering problems during the renovation process.	Yao and Li [38]; Zheng et al. [48].
		CPFD2	Face-to-face dialogues during the renovation process helped to eliminate misunderstandings between subjects.
		CPFD3	Face-to-face dialogues among the participants in the renovation process helped to resolve the problems faced.
	Reach intermediate consensus	CP3	Reasonable design solutions were negotiated during the renovation process.	Ding et al. [50].
		CP4	Reasonable cost-sharing programs were negotiated during the renovation process.
		CP5	A reasonable financing program was negotiated during the renovation process.
	Information disclosure and transparency	CPIT1	A platform for the publication of information was established during the renovation process.	Lei and Chen [44]; Cheng and Dong [55].
		CPIT2	Information about the renovation process was updated and released in a timely manner.
		CPIT3	Information sharing during the renovation process has some depth.
		CPIT4	Information sharing during renovation is varied.
	Level of awareness of interdependence among subjects	SCID1	If the relationship with our counterpart were terminated, it would be relatively difficult to find a similar partner.	Adobor [53].
		SCID2	There are not many other firms providing similar resources or services to this partner.
		SCID3	It will take us a lot of time and effort to find a new partner.
Collaborative outcomes	Effect of physical space renovation	COMS1	The renovation of the building body is very satisfactory.	Yao and Li [38].
		COMS2	The renovation of the public space is very satisfactory.
		COMS3	The renovation of the service facilities is very satisfactory.
	Effect of public affairs governance	COCG1	There was an increase in the degree of residents’ participation in the management of public affairs in the community after the renovation.	Dryzek & Niemeyer, [56]; Zhang [57].
		COCG2	There was an increase in the degree of participation of multiple subjects in public affairs in the community after the renovation.
		COCG3	There was a rational division of power and duties between each subject participating in the management of public affairs in the community after the renovation.
		COCG4	There was a smoothness of the channels for the expression of the demands of the subjects after the renovation.
		COCG5	The renovated community deliberative and consultative platform was effectively operated.
		COCG6	There was an openness and transparency about the information on public affairs in the renovated community.

Table 6

Demographic information of respondents.

Characteristics	Options	Numbers	Percentage
Age	19–44 years old	498	58.38%
	45–59 years old	317	37.16%
	60–74 years old	31	3.63%
	Over 75 years old	5	0.59%
	Under 18 years old	2	0.23%
Gender	Man	445	52.17%
	Woman	408	47.83%
Education	Undergraduate	377	44.20%
	Post-secondary	228	26.73%
	High school	127	14.89%
	Below high school	94	11.02%
	Postgraduate and above	27	3.17%
Subject	Resident	538	63.07%
	Social enterprise	166	19.46%
	Social organization	92	10.79%
	Government department	57	6.68%

Table 7

Overall reliability assessment results.

Cronbach’s α	Standardized Cronbach’s α	Item Count	Sample Count
0.976	0.981	70	853

Table 8

Reliability assessment for each variable.

Dimension	Variable	Code	Cronbach’s α	Item Count	Cronbach’s α	Item Count
Starting condition	degree of asymmetry	H1a	0.955	3	0.794	12
	policy incentives	H1b	0.954	3
	complexity of property rights	H1c	0.766	3
	past experiences of cooperation	H1d	0.497	3
Institutional design	establishment of inclusive participatory mechanism	H2a	0.947	4	0.976	14
	construction of effective deliberative platform	H2b	0.968	4
	establishment of conflict management and emergency response mechanisms	H2c	0.941	3
	establishment of reasonable cost- and benefit-sharing mechanism	H2d	0.956	3
Facilitative leadership	government departments	H3a	0.929	4	0.941	16
	social enterprises	H3b	0.961	4
	residents’ self-governing organizations	H3c	0.940	4
	non-profit social organizations	H3d	0.969	4
Collaborative governance	conduct effective conflict management	H4a	0.953	3	0.968	19
	build mutual trust among subjects	H4b	0.964	3
	face-to-face dialogue and consultation	H4c	0.970	3
	reach intermediate consensus	H4d	0.940	3
	information disclosure and transparency	H4e	0.966	4
	level of awareness of interdependence among subjects	H4f	0.960	3
Collaborative outcomes	effect of physical space renovation	M1~3	0.960	3	0.977	9
	effect of collaborative governance improvement of public affairs	G1~6	0.979	6

Table 9

KMO and Bartlett’s test of sphericity.

KMO Coefficient		0.976
Bartlett’s Test of Sphericity	asymptotic chi-square statistic	88,800.865
	df	2415
	p	0.000

Table 10

Discriminant validity analysis table.

	Starting Conditions	Institutional Design	Facilitative Leadership	Collaborative Outcomes
Starting conditions	0.695
Institutional design	0.048	0.856
Facilitative leadership	0.04	0.046	0.836
Collaborative outcomes	0.044	0.046	0.043	0.881
Square Root of AVE	0.834	0.925	0.914	0.939

Table 11

Model parameter fitting effect.

Evaluation Indicators	Criteria	Measured Value	Compliance with Standards
CMIN/DF	<5	4.216	YES
CFI	>0.90	0.938	YES
TLI	>0.90	0.934	YES
IFI	>0.90	0.938	YES
RFI	>0.90	0.916	YES
NFI	>0.90	0.920	YES
RMSEA	0.05~0.08	0.061	YES

Table 12

Structural Equation Modeling path coefficients.

Path			Standardized Path Coefficient	p
Collaborative outcomes	←	Starting conditions	−0.025	0.258
Collaborative outcomes	←	Institutional design	0.356	0.001
Collaborative outcomes	←	Facilitative leadership	−0.276	0.042
Collaborative outcomes	←	Collaborative process	0.788	0.001

Table 13

Mediation analysis results of independent and dependent variables.

Path	Mediation Coefficient	95% Confidence Interval		p
		Lower	Upper
Collaborative outcomes ←collaborative process ←starting conditions	−0.119	−0.184	−0.062	0.01
Collaborative outcomes ←collaborative process ←institutional design	0.558	0.389	0.724	0.01
Collaborative outcomes ←collaborative process ←facilitative leadership	0.852	0.564	1.154	0.01
Collaborative outcomes ←facilitative leadership ←starting conditions	−0.120	−0.183	−0.068	0.01
Collaborative outcomes ←institutional design ←starting conditions	−0.127	−0.192	−0.0075	0.01
Collaborative outcomes ←facilitative leadership ←institutional design	0.188	−0.129	0.617	0.225

Table 14

Mediation analysis results of latent variable.

Path	Mediation Coefficient	95% Confidence Interval		p
		Lower	Upper
Collaborative outcomes ←H2a←H1a	−0.081	−0.114	−0.053	0.001
Collaborative outcomes←H2a←H1c	−0.081	−0.124	−0.039	0.001
Collaborative outcomes←H2b←H1a	−0.078	−0.109	−0.052	0.001
Collaborative outcomes←H2b←H1c	−0.091	−0.139	−0.050	0.001
Collaborative outcomes←H2c←H1a	−0.064	−0.096	−0.034	0.001
Collaborative outcomes←H2c←H1c	−0.085	−0.137	−0.043	0.001
Collaborative outcomes←H2d←H1a	−0.082	−0.116	−0.052	0.001
Collaborative outcomes←H2d←H1c	−0.081	−0.128	−0.038	0.001
Collaborative outcomes←H3a←H1a	−0.073	−0.101	−0.049	0.001
Collaborative outcomes←H3a←H1c	−0.084	−0.126	−0.048	0.001
Collaborative outcomes←H3c←H1a	−0.058	−0.085	−0.032	0.001
Collaborative outcomes←H3c←H1c	−0.040	−0.078	−0.001	0.039
Collaborative outcomes←H4a←H1a	−0.091	−0.121	−0.062	0.001
Collaborative outcomes←H4a←H1c	−0.099	−0.146	−0.058	0.001
Collaborative outcomes←H4b←H1a	−0.078	−0.110	−0.047	0.001
Collaborative outcomes←H4b←H1c	−0.091	−0.141	−0.049	0.001
Collaborative outcomes←H4c←H1a	−0.068	−0.099	−0.038	0.001
Collaborative outcomes←H4c←H1c	−0.088	−0.138	−0.044	0.001
Collaborative outcomes←H4d←H1a	−0.064	−0.096	−0.034	0.001
Collaborative outcomes←H4d←H1c	−0.087	−0.144	−0.040	0.001
Collaborative outcomes←H4e←H1a	−0.075	−0.111	−0.043	0.001
Collaborative outcomes←H4e←H1c	−0.083	−0.142	−0.038	0.001
Collaborative outcomes←H4a←H2a	0.371	0.286	0.470	0.001
Collaborative outcomes←H4b←H2a	0.421	0.343	0.509	0.001
Collaborative outcomes←H4c←H2a	0.469	0.388	0.553	0.001
Collaborative outcomes←H4d←H2a	0.435	0.345	0.532	0.001
Collaborative outcomes←H4e←H2a	0.528	0.455	0.615	0.001
Collaborative outcomes←H4a←H2b	0.349	0.236	0.456	0.001
Collaborative outcomes←H4b←H2b	0.421	0.319	0.524	0.001
Collaborative outcomes←H4c←H2b	0.461	0.354	0.566	0.001
Collaborative outcomes←H4d←H2b	0.428	0.311	0.551	0.001
Collaborative outcomes←H4e←H2b	0.555	0.472	0.646	0.001
Collaborative outcomes←H4a←H2c	0.328	0.242	0.425	0.001
Collaborative outcomes←H4b←H2c	0.415	0.317	0.522	0.001
Collaborative outcomes ←H4c←H2c	0.429	0.339	0.523	0.001
Collaborative outcomes←H4d←H2c	0.396	0.301	0.499	0.001
Collaborative outcomes←H4e←H2c	0.495	0.418	0.576	0.001
Collaborative outcomes←H4a←H2d	0.325	0.254	0.404	0.001
Collaborative outcomes←H4b←H2d	0.375	0.302	0.465	0.001
Collaborative outcomes←H4c←H2d	0.400	0.326	0.492	0.001
Collaborative outcomes←H4d←H2d	0.445	0.345	0.558	0.001
Collaborative outcomes←H4e←H2d	0.440	0.377	0.513	0.001
Collaborative outcomes←H4a←H3a	0.491	0.358	0.627	0.001
Collaborative outcomes←H4a←H3c	0.453	0.375	0.550	0.001
Collaborative outcomes←H4b←H3a	0.555	0.428	0.676	0.001
Collaborative outcomes←H4b←H3c	0.442	0.363	0.527	0.001
Collaborative outcomes←H4c←H3a	0.612	0.483	0.742	0.001
Collaborative outcomes←H4c←H3c	0.471	0.393	0.561	0.001
Collaborative outcomes←H4d←H3a	0.528	0.402	0.658	0.001
Collaborative outcomes←H4d←H3c	0.461	0.371	0.564	0.001
Collaborative outcomes←H4e←H3a	0.673	0.569	0.790	0.001
Collaborative outcomes←H4e←H3c	0.526	0.437	0.625	0.001

Table 15

Partial results of factors’ mediation effects on collaborative community governance variable.

Path	Mediation Coefficient	95% Confidence Interval		p
		Lower	Upper
Collaborative community governance improvement←H4c←H2a	0.563	0.470	0.656	0.001
Collaborative community governance improvement←H4e←H2a	0.637	0.562	0.733	0.000
Collaborative community governance improvement←H4c←H2b	0.555	0.425	0.679	0.001
Collaborative community governance improvement←H4e←H2b	0.673	0.580	0.781	0.001
Collaborative community governance improvement←H4e←H2c	0.591	0.511	0.675	0.001
Collaborative community governance improvement←H4a←H3a	0.578	0.421	0.730	0.001
Collaborative community governance improvement←H4b←H3a	0.665	0.518	0.809	0.001
Collaborative community governance improvement←H4c←H3a	0.741	0.595	0.897	0.001
Collaborative community governance improvement←H4c←H3c	0.559	0.475	0.657	0.001
Collaborative community governance improvement←H4d←H3a	0.635	0.495	0.792	0.001
Collaborative community governance improvement←H4e←H3a	0.818	0.701	0.949	0.001
Collaborative community governance improvement←H4e←H3c	0.626	0.535	0.737	0.001

Table 16

Results of research hypothesis testing.

Code	Hypotheses	Results
H1	Favorable starting conditions have a positive impact on the collaborative governance of the renovation of OURA.	NO
H1a	The degree of asymmetry in the subjects’ renovation capacity, knowledge, and resources has a negative impact on the collaborative governance of OURA.	YES
H1b	The extent to which policies incentivize subjects to participate in collaborative renovation has a positive impact on the collaborative governance of OURA.	NO
H1c	The complexity of property rights has a negative impact on the collaborative governance of renovation of OURAs.	YES
H1d	Subjects’ past experiences of satisfactory cooperation have a positive impact on the collaborative governance of OURA renovation.	NO
H2	A comprehensive institutional design has a positive impact on the collaborative governance of OURA renovation.	YES
H2a	The establishment of an inclusive collaborative renovation participation mechanism has a positive impact on the collaborative governance of OURA renovation.	YES
H2b	The construction of an effective deliberative platform has a positive impact on the collaborative governance of OURA renovation.	YES
H2c	The establishment of conflict management and emergency response mechanisms has a positive impact on the collaborative governance of OURA renovation.	YES
H2d	The establishment of a reasonable cost- and benefit-sharing mechanism has a positive impact on the collaborative governance of OURA renovation.	YES
H3	Facilitative leadership has a positive impact on the collaborative governance of OURA renovation.	YES
H3a	The primary leadership and coordination role of government departments has a positive impact on the collaborative governance of OURA renovation.	YES
H3b	The primary leadership and coordination role of social enterprises has a positive impact on the collaborative governance of OURA renovation.	YES
H3c	The primary leadership and coordination role of residents’ self-governing organizations has a positive impact on the collaborative governance of OURA renovation.	YES
H3d	The primary leadership and coordination role of social organizations has a positive impact on the collaborative governance of OURA renovation.	YES
H4	Cooperative collaborative processes have a positive impact on the collaborative governance of OURA renovation.	YES
H4a	Effective conflict management has a positive impact on the collaborative governance of OURA renovation.	YES
H4b	Building mutual trust among subjects has a positive impact on the collaborative governance of OURA renovation.	YES
H4c	Face-to-face dialogue and consultation have a positive impact on the collaborative governance of OURA renovation.	YES
H4d	Reaching an intermediate consensus has a positive impact on the collaborative governance of OURA renovation.	YES
H4e	Information disclosure and transparency has a positive impact on the collaborative governance of OURA renovation.	YES
H4f	The level of awareness of interdependence among subjects has a positive impact on the collaborative governance of OURA renovation.	NO

References

1. Wang, J. New economic growth: Renovation of OURA. Adm. Reform; 2015; 11, pp. 32-37. [DOI: https://dx.doi.org/10.14150/j.cnki.1674-7453.2015.11.008]

2. Wang, Z.; Liu, L.; Yan, J. Study on the way and countermeasure of upgrading and reconstruction of old residential area in China. Urban Dev. Stud.; 2020; 27, pp. 26-32.

3. Lin, C.; Du, Y.; Yue, J.; Wang, J. A research on the urban regeneration mechanism of multiple-stakeholder collaboration: A case study of Shenzhen. Urban Plan. Forum; 2019; 6, pp. 56-62. [DOI: https://dx.doi.org/10.16361/j.upf.201906007]

4. Liu, C.; Jiang, R. Study on the governance model of the old community from the perspective of pluralistic co-governance. Adm. Reform; 2023; 8, pp. 48-55. [DOI: https://dx.doi.org/10.14150/j.cnki.1674-7453.2023.08.005]

5. Yang, J.; Chen, Y. Review on the development of urban regeneration in China from 1949 to 2019. City Plan. Rev.; 2020; 44, pp. 9–19+31.

6. Tian, Y. Research on the Operational Logic and Practical Path of Collaborative Governance: Based on A Comparative Case Study Between China and the United States. Ph.D. Thesis; Jilin University: Changchun, China, 2017.

7. Ansell, C.; Gash, A. Collaborative Governance in Theory and Practice. J. Bus. Res.; 2008; 18, pp. 330-337. [DOI: https://dx.doi.org/10.1093/jopart/mum032]

8. Emerson, K.; Nabatchi, T.; Balogh, S. An integrative framework for collaborative governance. J. Public Adm. Res. Theory; 2012; 22, pp. 1-29. [DOI: https://dx.doi.org/10.1093/jopart/mur011]

9. Bryson, J.M.; Crosby, B.C.; Bloomberg, L. Public value governance: Moving beyond traditional public administration and the new public management. Public Adm. Rev.; 2014; 74, pp. 445-456. [DOI: https://dx.doi.org/10.1111/puar.12238]

10. Stoker, G.; Hua, X. Governance as theory: Five arguments. Int. Soc. Sci. J. (Chin. Ed.); 1999; 1, pp. 19-30.

11. Donahue, J.D.; Zeckhauser, R.J. Collaborative Governance: Private Roles for Public Goals in Turbulent Times; Princeton University Press: Princeton, NY, USA, 2011.

12. Lees, L.; Slater, T.; Wyly, E. Gentrification; Routledge: Abingdon, UK, 2008.

13. Lees, L. Gentrification, Race, and Ethnicity: Towards a Global Research Agenda?. City Community; 2016; 15, pp. 208-214. [DOI: https://dx.doi.org/10.1111/cico.12185]

14. Florida, R. The Rise of the Creative Class, and How It Is Transforming Work, Leisure, Community and Everyday Life; Basic Books: New York, NY, USA, 2002.

15. Pratt, A.C. Creative cities: Tensions with and between social, cultural and economic development: A critical reading of the UK experience. City Cult. Soc.; 2010; 1, pp. 13-20. [DOI: https://dx.doi.org/10.1016/j.ccs.2010.04.001]

16. Wang, H.; Shen, Q.; Tang, B.S.; Lu, C.; Peng, Y.; Tang, L.Y.N. A framework of decision-making factors and supporting information for facilitating sustainable site planning in urban renewal projects. Cities; 2014; 40, pp. 44-45. [DOI: https://dx.doi.org/10.1016/j.cities.2014.04.005]

17. Zeng, W.; Shen, Q.; Wang, H. A review of recent studies on sustainable urban renewal. Habitat Int.; 2014; 41, pp. 272-279. [DOI: https://dx.doi.org/10.1016/j.habitatint.2013.08.006]

18. Zhou, T.; Zhou, Y.; Liu, G. Key variables for decision-making on urban renewal in China: A case study of Chongqing. Sustainability; 2017; 9, 370. [DOI: https://dx.doi.org/10.3390/su9030370]

19. Aigwi, I.; Phiipps, R.; Ingham, J.; Filippova, O. Characterisation of adaptive reuse stakeholders and the effectiveness of collaborative rationality towards building resilient urban areas. Syst. Pract. Action Res.; 2020; 34, pp. 141-151. [DOI: https://dx.doi.org/10.1007/s11213-020-09521-0]

20. Liao, K.; Cai, Y. A review of foreign urban renewal studies during the last ten years. Urban Dev. Stud.; 2017; 24, pp. 27-34.

21. Jacobs, J. The Death and Life of Great American Cities; Random House: New York, NY, USA, 1961.

22. Alexander, C. Notes on the Synthesis of Form; Harvard University Press: Cambridge, MA, USA, 1964.

23. Alexander, C.; Ishikawa, S.; Silverstein, M.; Jacobson, M.; Fiksdahl-King, I.; Angel, S. A Pattern Language: Towns, Buildings, Construction; Oxford University Press: New York, UY, USA, 1977.

24. Alexander, C. The Timeless Way of Building; Oxford University Press: New York, UY, USA, 1979.

25. Mehaffy, M.W.; Kryazheva, Y.; Rudd, A.; Salingaros, N.A. A New Pattern Language for Growing Regions: Places, Networks, Processes; Sustasis Press: Portland, OR, USA, 2020.

26. Yang, J. Innovation and construction of urban renewal system in the new stage of transformation and development. Constr. Sci. Technol.; 2021; 426, pp. 8-21.

27. Xie, Q.; Hu, L.; Wu, J.; Shan, Q.; Li, W.; Shen, K. Investigating the influencing factors of the perception experience of historical commercial streets: A case study of Guangzhou’s Beijing Road Pedestrian Street. Buildings; 2024; 14, 138. [DOI: https://dx.doi.org/10.3390/buildings14010138]

28. Liu, G.; Fu, X.; Han, Q.; Huang, R.; Zhuang, T. Research on the collaborative governance of urban regeneration based on a Bayesian network: The case of Chongqing. Land Use Policy; 2021; 109, 105640. [DOI: https://dx.doi.org/10.1016/j.landusepol.2021.105640]

29. Li, Z.; Wang, X. A comparative study of models of collaborative governance in the renovation of OURA: Based on an examination of three governance cases in Beijing. Hubei Soc. Sci.; 2023; 10, pp. 46-60. [DOI: https://dx.doi.org/10.13660/j.cnki.42-1112/c.016188]

30. Du, Y.; Qu, K.; Hu, Y. Research on the Construction of Multi-stakeholder Collaborative Governance Mechanism of Urban Renewal Projects Based on Power Perspective. J. Eng. Manag.; 2024; 38, pp. 63-68. [DOI: https://dx.doi.org/10.13991/j.cnki.jem.2024.05.011]

31. Shen, L.; Tang, L.; Mu, Y. Critical success factors and collaborative governance mechanism for the transformation of existing residential buildings in urban renewal: From a social network perspective. Heliyon; 2024; 10, e27672. [DOI: https://dx.doi.org/10.1016/j.heliyon.2024.e27672] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/38510033]

32. Kim, H.; Kim, H.; Woosnam, K.M. Considering urban regeneration policy support: Perceived collaborative governance in cultural heritage-led regeneration projects of Korea. Habitat Int.; 2023; 140, 102931. [DOI: https://dx.doi.org/10.1016/j.habitatint.2023.102921]

33. Zhang, W.; Zhang, X.; Wu, G. The network governance of urban renewal: A comparative analysis of two cities in China. Land Use Policy; 2021; 106, 105448. [DOI: https://dx.doi.org/10.1016/j.landusepol.2021.105448]

34. Qu, K. Research on Multi-Stakeholder Collaborative Governance of Urban Renewal Projects in China: Based on 2-Mode Network Analysis. Master’s Thesis; Dongbei University of Finance and Economics: Dalian, China, 2022.

35. Zhu, D.; Gao, X. Collaborative governance mechanism for urban renewal: A case study of Shanghai. J. Beijing Inst. Technol. (Soc. Sci. Ed.); 2018; 20, pp. 58-66. [DOI: https://dx.doi.org/10.15918/j.jbitss1009-3370.2018.1341]

36. Wood, D.J.; Gray, B. Toward a comprehensive Theory of Collaboration. J. Appl. Behav. Sci.; 1991; 27, pp. 139-162. [DOI: https://dx.doi.org/10.1177/0021886391272001]

37. Liu, X.; Zhu, D. Collaborative governance: A new governance model of complex public issues. J. Shanghai Adm. Inst.; 2016; 17, pp. 46-54.

38. Yao, Z.; Li, H. Research on collaborative governance of old community renovation based on the SFIC model: A case study of Shanghai. Mod. Urban Res.; 2024; 6, pp. 22-29. [DOI: https://dx.doi.org/10.3969/j.issn.1009-6000.2024.06.004]

39. Ansell, C.; Doberstein, C.; Henderson, H.; Siddki, S.; Hart, P. Understanding inclusion in collaborative governance: A mixed methods approach. Policy Soc.; 2020; 39, pp. 570-591. [DOI: https://dx.doi.org/10.1080/14494035.2020.1785726]

40. Wang, D.; Wang, M. Multiple collaborative and lulti-dimensional absorption: Community governance dynamics and its mechanism construction. Qinghai Soc. Sci.; 2019; 3, pp. 126–131+141. [DOI: https://dx.doi.org/10.14154/j.cnki.qss.2019.03.019]

41. Yung, E.H.K.; Chan, E.H.W.; Xu, Y. Community-Initiated adaptive reuse of historic buildings and sustainable development in the inner city of Shanghai. J. Urban Plan. Dev.; 2013; 140, 0000174. [DOI: https://dx.doi.org/10.1061/(ASCE)UP.1943-5444.0000174]

42. Wang, H.; Zhao, Y.; Gao, X.; Gao, B. Collaborative decision-making for urban regeneration: A literature review and bibliometric analysis. Land Use Policy; 2021; 107, 105479. [DOI: https://dx.doi.org/10.1016/j.landusepol.2021.105479]

43. Zhu, F.; Tian, W.; Yu, M. Concept development for the effectiveness of project conflict management. Proj. Manag. Technol.; 2019; 17, pp. 7-11.

44. Lei, X.; Chen, Z. Seeking collaborative advantage: Collective action logic for realizing effective consultative democracy in urban communities: A case study of T community in Xi’an. Truth Seek.; 2023; 5, pp. 72-83.

45. Ringle, C.M.; Sarstedt, M.; Mitchell, R.; Gudergan, S.P. Partial least squares structural equation modeling in HRM research. Int. J. Hum. Resour. Manag.; 2020; 31, pp. 1617-1643. [DOI: https://dx.doi.org/10.1080/09585192.2017.1416655]

46. Liu, Z.; Zhou, H. Regulatory impact of policy incentive on open innovation strategies and innovation performance. Technol. Econ.; 2019; 38, pp. 15–20+130.

47. Liu, G.; Huang, R.; Li k Shrestha, A.; Wang, H.; Cai, M. Exploring the dilemma of enterprises participating in the old community renewal: Perspective of managers. Cities; 2024; 150, 105073. [DOI: https://dx.doi.org/10.1016/j.cities.2024.105073]

48. Zheng, L.; Xiong, Z.; Wu, J. Research on the performance and mechanism of participatory community regeneration governance based on Social Network Analysis: A case study of Xinhua Community in Shanghai. Urban Dev. Stud.; 2024; 31, pp. 111-120.

49. Wu, H.; Wang, Y.; Zhuang, T.; Li, K.; Hu, W. What makes co-production work in sustainable neighnorhood rehabilitation in China? A stakeholder structure perspective. Cities; 2024; 150, 105068. [DOI: https://dx.doi.org/10.1016/j.cities.2024.105068]

50. Ding, R.; Fan, H.; Zhang, X.; Wang, J. Research on the mechanism of collaborative governance of old neighborhood renovation based on fuzzy cognitive map. Chongqing Soc. Sci.; 2024; 7, pp. 111-127. [DOI: https://dx.doi.org/10.19631/j.cnki.css.2024.007.008]

51. Vogel, R.; Masal, D. Public leadership: A review of literature and framework for future research. Public Manag. Rev.; 2014; 17, pp. 1165-1189. [DOI: https://dx.doi.org/10.1080/14719037.2014.895031]

52. Mcevily, B.; Tortoriello, M. Measuring trust in organizational research: Review and recommendations. J. Trust Res.; 2011; 1, pp. 23-63. [DOI: https://dx.doi.org/10.1080/21515581.2011.552424]

53. Adobor, H. Trust as sensemaking: The microdynamics of trust in interfirm alliances. J. Bus. Res.; 2005; 58, pp. 330-337. [DOI: https://dx.doi.org/10.1016/S0148-2963(03)00077-8]

54. Laan, A.; Voordijk, H.; Noorderhaven, N.; Dewulf, G. Levels of interorganizational trust in construction projects: Empirical evidence. J. Constr. Eng. Manag.; 2012; 138, pp. 821-831. [DOI: https://dx.doi.org/10.1061/(ASCE)CO.1943-7862.0000495]

55. Cheng, D.; Dong, R. Evaluation study on the synergy of governance of multiple subjects in urban communities in the new era. Adm. Trib.; 2022; 29, pp. 102-108. [DOI: https://dx.doi.org/10.16637/j.cnki.23-1360/d.2022.06.003]

56. Dryzek, J.S.; Niemeyer, S. Foundations and Frontiers of Deliberatative Governance; Oxford University Press: Oxford, UK, 2010.

57. Zhang, D. Conditions, types and quality identification of consultation systems in community governance: A comparsion based on six experimental cases of community consultation. Probe; 2020; 6, pp. 45-54. [DOI: https://dx.doi.org/10.16501/j.cnki.50-1019/d.2020.06.004]

58. Fishkin, J.S. When the People Speak; Oxford University Press: Oxford, UK, 2009.

59. Sanchez, G.M.E.; Renterghem, T.V.; Sun, K.; Coensel, B.D.; Botteldooren, D. Using virtual reality for assessing the role of noise in the audio-visual design of an urban public space. Landsc. Urban Plan.; 2017; 167, pp. 98-107. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2017.05.018]

60. Li, Q.; Long, L.; Li, X.; Yang, G.; Bian, C.; Zhao, B.; Chen, X.; Chen, B.M. Life cycle cost analysis of circular photovoltaic façade in dense urban environment using 3D modeling. Renew. Energy; 2024; 238, 121914. [DOI: https://dx.doi.org/10.1016/j.renene.2024.121914]

61. Durdurana, S.S.; Temiza, F. Creating 3D modelling in urban regeneration projects: The case of Mamak, Ankara. Procedia Earth Planet. Sci.; 2015; 15, pp. 442-447. [DOI: https://dx.doi.org/10.1016/j.proeps.2015.08.035]

62. Labovkin, F. Modern Technologies in Renovation and Restoration Cases. Bachelor’s Thesis; Saimaa University of Applied Sciences: Lappeenranta, Finland, 2019.

63. Li, T.; Hu, H.; Ma, H.; Ma, J.; Li, Q. Using virtual reality to enhance learning performance and address educational resource disparities in Architectural History Courses. Sustainability; 2025; 17, 866. [DOI: https://dx.doi.org/10.3390/su17030866]

64. Li, Q.; Yang, G.; Gao, C.; Huang, Y.; Zhang, J.; Huang, D.; Zhao, B.; Chen, X.; Chen, B.M. Single drone-based 3D reconstruction approach to improve public engagement in conservation of heritage buildings: A case of Hakka Tulou. J. Build. Eng.; 2024; 87, 108954. [DOI: https://dx.doi.org/10.1016/j.jobe.2024.108954]

65. Du, Z.; Guo, W.; Li, W.; Gao, X. A study on the optimization of wind environment of existing villa buildings in Lingnan Area: A case study of Jiangmen’s “Yunshan Poetic” Moon Island Houses. Buildings; 2022; 12, 1304. [DOI: https://dx.doi.org/10.3390/buildings12091304]