Governing Rural Public Open Spaces in Taigu, China: An SES-Based Collective Action Model Using Delphic Hierarchy Process (DHP)

Abstract

China’s rural public open spaces (POS) are largely governed as common-pool resources through self-organized collective arrangements, often regarded as a viable pathway to sustainable commons management. Yet, in practice, these systems remain prone to overuse and under-maintenance, reflecting collective action failures associated with the tragedy of the commons. The governance of rural POS therefore constitutes a complex social–ecological problem shaped by the interplay of institutional rules, biophysical conditions, and user–stakeholder interactions. Taking Taigu District in Shanxi Province—characterized by heterogeneous social–ecological contexts and collective action dilemmas—as the empirical case, this study develops a meso-level baseline model to identify the key conditions (design principles) for sustainable rural POS governance. Adopting an expert-based epistemological approach, 24 specialists in rural governance (scholars, planners, and local administrators) were engaged. Grounded in commons and collective action theories within the Social–Ecological Systems (SES) framework and informed by Transaction Cost Economics (TCE), the study operationalizes a Delphic Hierarchy Process (DHP), combining three rounds of Delphi to establish consensus on governance conditions with the Analytic Hierarchy Process (AHP) to derive their relative weights. The model specifies 14 governance conditions across four interrelated dimensions: ecological (e.g., clearly defined resource boundaries and congruence between resource characteristics and user needs), institutional (e.g., simple and enforceable rules, accessible conflict-resolution mechanisms, accountable monitoring, and calibrated external support), social (e.g., social capital, leadership capacity, clearly defined user boundaries, and group interdependence), and interactional (e.g., resource dependence, equity in benefit distribution, and supply–demand alignment). It further clarifies their relative importance and systemic interdependencies. By operationalizing commons design principles within a meso-level analytical framework, the study advances their empirical application in rural planning and offers five targeted managerial implications to strengthen institutional robustness and the long-term sustainability of self-governed rural POS.

1. Introduction

Public open spaces (POS) are critical components of social–ecological systems, supporting human, economic, and environmental well-being. In rural China, POS are non-built areas within villages that serve multiple functions, including public leisure, social interaction, sports, ecological landscaping, agricultural production, and disaster mitigation [1]. Socially, POS strengthen community cohesion through festivals and communal activities, reinforcing kinship networks and local economic exchanges. Economically, they support agricultural processing and household-based production, contributing directly to villagers’ livelihoods. Ecologically, landscaped and natural elements enhance biodiversity, microclimates, and soil stability, while POS also provide critical refuges during disasters, bolstering rural resilience [1]. Collectively, these functions underscore the centrality of POS in sustaining rural social–ecological systems (SES).

China’s dual land system stipulates that urban land is owned by the state, while rural land is collectively owned by village collectives. Accordingly, the ownership and management rights of rural POS rest with village collectives, and their governance is carried out through collective self-governance. This decentralized management aligns with Ostrom’s [2] notion of self-governance as an alternative to state- or market-based approaches, promoting sustainable resource use when social–ecological conditions are favorable. Nevertheless, structural constraints, outmigration, and weakened governance capacity challenge effective management [1,3]. Theoretically, rural POS resemble club goods with restricted access and largely non-rival use [4], yet weak governance often leads to free-riding, underinvestment, and degradation, consistent with Hardin’s [5] “tragedy of the commons.” Empirically, they function more as common-pool resources, with rivalrous use and limited excludability [6,7]. Research on commons self-governance has identified conditions that facilitate sustainable management [7,8,9,10]. However, few studies systematically categorize these conditions or examine their interactions. The SES framework addresses this gap by integrating ecological, institutional, and social dimensions, enabling the diagnosis of governance challenges and providing a structured approach to prescriptive strategies [11]. In China and globally, most existing studies focus on diagnosing the effectiveness of individual influencing factors, which are typically examined in isolation, and have not yet produced a systematic model that captures the structural configuration among these factors [12,13]. Establishing a systematic governance model at the early stage of research can facilitate the formulation of effective management strategies and provide a reference for subsequent in-depth empirical studies.

Given the current research gaps, this study aims to developing a collective action model for the self-governance of rural POS. Rural POS governance constitutes a complex social–ecological system, shaped by the dynamic interactions among institutional arrangements, ecological conditions, and multiple groups of actors. Effectively capturing this complexity requires an integrative model-building approach that goes beyond the limitations of a single-actor perspective. On this basis, research on rural POS self-governance adopts a stepwise research design. This study represents an early-stage exploratory effort and aims to develop a baseline model for sustainable rural POS self-governance through expert consultation. Specifically, this model integrates the SES framework with collective action theories and is further evaluated and refined by experts with diverse professional backgrounds. This process reflects an extension of the SES framework in the context of POS governance—from a diagnostic analytical tool to a design-oriented, system-level analytical model. Although local residents are the primary actors in rural governance, incorporating both resident and expert perspectives at the early stage of model construction may introduce heterogeneity in knowledge types, thereby reducing data consistency and increasing variability in judgments. Residents’ insights are often context-dependent, experience-based, and oriented toward immediate practices. While such insights are highly valuable, the construction of the collective action model requires respondents who can understand how institutional arrangements operate across different contexts and grasp the systemic interrelationships among multiple influencing factors. In contrast, such cross-contextual and system-level knowledge is more typically held by domain experts. Therefore, the prescriptive collective action model proposed in this study is primarily constructed based on experts’ perspectives. This approach is valid as it has been widely adopted in many community-related studies, such as community forest governance [14], fisheries management [15], disaster risk management [16], and water resource management [17].

Therefore, grounded in the SES framework, this study aims to integrate and translate globally recognized theoretical constructs—such as the design principles/enabling conditions for sustainable commons management proposed by Wade [8], Ostrom [7], Baland and Platteau [9], Agrawal [10]—into a context-specific governance model for rural POS. This study focuses on 198 administrative villages in Taigu District, Shanxi Province, and employs purposive sampling to select 24 experts with extensive experience in rural POS governance, including scholars, planners, and government administrators. In line with this study’s epistemological position, Delphic Hierarchy Process (DHP) (combining Delphi and AHP approaches) for iterative expert evaluation was applied and transaction cost economics (TCE) [18] was embedded into the construction of the collective action model as an efficiency logic tool. It examines, from a transaction cost perspective, the mechanisms through which the model conditions affect rural POS governance effectiveness, thereby enhancing the robustness of the results [19]. The resulting model not only provides practical guidance for improving rural POS governance in Taigu and similar contexts, but also offers a systematic, expert-informed reference for future research.

The remainder of this paper is structured as follows. Section 2 reviews the literature and develops the conceptual framework. Section 3 details the study area, data collection, and data analysis. Section 4 presents empirical results, Section 5 discusses findings, and Section 6 concludes with contributions and limitations.

2. Literature Review

2.1. SES Framework

Ostrom [2] developed the social–ecological systems (SES) framework through extensive commons management research [20], later refined by McGinnis and Ostrom [11]. As shown in Figure 1, the framework comprises three tiers. The outer tier represents the external environment, including social, economic, and political settings (S) and ecosystems (ECO), which shape internal SES configurations and influence resource conditions, interactions, and governance outcomes. The core encompasses four interrelated subsystems: resource systems (RS) (e.g., forests, lakes, fisheries), resource units (RU) (e.g., trees, fish, water), governance systems (GS) (e.g., institutions, policies, laws), and actors (A) (e.g., resource users and managers with their knowledge systems). The third component focuses on focal action situations, capturing the interactions (I) among subsystems and the resulting outcomes (O).

Beyond the interconnections among subsystems, the SES framework also features a multi-tiered structure. McGinnis and Ostrom [11] expanded it to 56 second-tier variables, with flexibility to incorporate additional lower-tier variables tailored to specific research contexts [21]. This hierarchical and networked design enables the SES framework to function both as a diagnostic and a prescriptive tool. Specifically, the diagnostic function seeks to understand why POS governance fails or which factors contribute to such failure, while the prescriptive function focuses on how and through what feasible measures successful governance can be achieved [22]. The second-tier variables of the SES framework provide a foundation for diagnosing commons management problems, while its prescriptive applications are often integrated with collective action theories [23]. Drawing on a substantial body of diagnostic research on commons management, Wade [8], Ostrom [7], Baland and Platteau [9], as well as Agrawal [10], proposed a set of prescriptive conditions/principles for the sustainable commons governance. At the current stage of research, conceptualizing these conditions within the SES framework and developing a meso-level baseline model (focusing on regional governance of rural POS) through systematic analysis for rural POS self-governance in Taigu, China can provide a reference for subsequent micro-level studies of POS management (focusing on specific rural POS cases). In other words, such a model enables researchers to identify potential influencing factors and mechanisms in advance, so that later studies can focus on refining and validating the model, thereby enhancing the coherence of prescriptive research and reducing the complexity of research design.

2.2. Key Theories and Conceptual SES Framework

2.2.1. Collective Action Theories

Since the 1990s, scholars of common-pool resources have argued that property rights alone are insufficient for sustainability. Dynamic, decentralized self-governance can overcome the limitations of rigid policies, limited state capacity, and insufficient private investment, promoting enduring resource management [7]. Consequently, research attention shifted toward identifying the incentive conditions that support effective self-governance.

Seminal studies by Wade [8], Ostrom [7], and Baland and Platteau [9] examined community-managed commons and proposed key conditions for institutional sustainability. Ostrom [7] termed these “essential conditions,” emphasizing their role in maintaining compliance across generations. Agrawal [10] synthesized these contributions, incorporating insights from prior studies (e.g., Blomquist et al. [24]; Agrawal and Gibson [25]; Young [26]; Tang [27]; Ostrom et al. [28]; Pinkerton [29]; Sengupta [30]), identifying 33 enabling conditions, categorizing them, and clarifying their causal mechanisms. These works provide a critical foundation for the development of the SES framework.

Despite their influence, these conditions have rarely been systematically integrated with the SES framework. This study aims to fill this gap by drawing on Agrawal’s [10] classification of conditions for sustainable commons management and mapping them into corresponding subsystems of the SES framework. The detailed classification process is as follows: conditions under “resource system characteristics” are grouped into “resource systems and units (RSU)”; those under “group characteristics” are assigned to “actors (A)”; and those under “institutional arrangements” are incorporated into “governance systems (GS)”. Conditions describing relationships between resource system characteristics and group characteristics, as well as those between resource system characteristics and institutional arrangements, reflect interactions among system components and are therefore integrated into the “interaction (I)” subsystem. For conditions under the “external environment” category, “low levels of articulation with external markets” and “gradual change in articulation with external markets” represent the market context in which the commons are embedded and are thus included in “resource systems and units (RSU)”. “Time for adaptation to new technologies related to the commons” reflects users’ adaptive capacity to technological change and is therefore classified under “actors (A)”. Finally, “low-cost exclusion technology,” “central governments should not undermine local authority,” “supportive external sanctioning institutions,” “appropriate levels of external aid to compensate local users for conservation activities,” and “nested levels of appropriation, provision, enforcement, and governance” all pertain to institutional arrangements for commons governance and are therefore categorized under “governance systems (GS)”.

Unlike the typical diagnostic function of the SES framework, the conceptual framework developed in this study is more design-oriented, representing a system-level analytical framework with prescriptive implications. It integrates established enabling conditions with the SES structure to guide the design of targeted collective action strategies for rural POS. By leveraging the SES framework’s systematic, multi-level structure, the conceptual framework supports precise institutional design and policy interventions for sustainable commons management, forming the basis for the SES-based conceptual framework presented in Figure 2.

2.2.2. Transaction Cost Economics (TCE)

To enhance the analytical rigor of this study, transaction cost theory is introduced into the conceptual framework as an efficiency logic for explaining governance effectiveness. It examines how influencing conditions affect costs in information acquisition, collective decision-making, and monitoring and enforcement, thereby revealing their mechanisms of impact on the sustainable rural POS self-governance. Originally introduced by Coase [31] and later formalized by Williamson [32], transaction costs are defined as the expenses associated with initiating, executing, and enforcing exchanges. Williamson further categorized the determinants of transaction costs into three groups: human factors, transaction-specific characteristics, and the transaction environment.

Human Factors

Williamson [32] conceptualized economic actors as “contractual men” who operate under bounded rationality, seeking to minimize transaction costs while mitigating opportunism. Four key dimensions characterize this framework: (i) bounded rationality, reflecting decision-making under incomplete information and cognitive limitations; (ii) self-interest, which motivates actors to maximize personal benefits and may lead to opportunistic behavior; (iii) information asymmetry, arising when parties possess unequal knowledge, thereby increasing opportunism risk; and (iv) negotiation and bargaining, where uncertainty and strategic behavior (e.g., information concealment) generate additional coordination and monitoring costs.

Transaction-Specific Factors

Transaction characteristics critically influence governance arrangements [32]. (i) Specific investments are tailored to particular transactions and may lose value outside them, requiring safeguards to reduce risk. (ii) Transaction frequency affects costs: while repeated transactions may increase search and enforcement costs, they can also foster stable relationships that lower long-term transaction costs. (iii) Incomplete contracts fail to anticipate all contingencies, creating uncertainty and enabling opportunistic behaviour. (iv) Irreversible investments involve sunk costs that heighten risk, thereby increasing the costs of contract design, negotiation, and enforcement.

Transaction Environment Factors

The broader institutional and market context further shapes transaction costs [32]. Specifically, (i) market competition affects bargaining power and the availability of alternatives, with more competitive environments generally lowering transaction costs; (ii) environmental uncertainty elevates risk and associated costs; and (iii) the institutional environment, including legal and regulatory frameworks, enhances contract enforceability and mitigates transaction risks.

As a cornerstone of new institutional economics, TCE has been widely applied to explain conditions for sustainable commons governance, including Ostrom’s design principles, across diverse contexts [19]. In this study, it complements the SES-based conceptual framework, jointly providing a robust theoretical foundation for developing a collective action model to guide rural POS self-governance. Grounded in the SES framework, this study integrates conceptualized collective action theories and TCE to develop the conceptual framework of the study (see Figure 2).

3. Research Methodology

3.1. Study Area

This study examines the self-governance of rural POS in Taigu District, Jinzhong City, Shanxi Province, selected for its relatively pronounced governance challenges compared to more developed regions in China. Economically, Taigu’s per capita GDP (37,700 RMB) is well below the national average (85,700 RMB) [33], constraining local capacity for POS management amid rapid urbanization. These limitations are compounded by rural outmigration and talent loss, which weaken collective governance capacity [34]. Ecologically, Shanxi’s location on the Loess Plateau, with a dry climate and severe soil erosion, increases the costs of maintaining functional and green POS.

Taigu also exhibits substantial socio-economic and geographical heterogeneity. Villages span plains, hills, and mountains and display diverse livelihood structures. In peri-urban and tourism-oriented villages, income largely derives from the tertiary sector, whereas villages near industrial clusters or collective enterprises rely on industrial earnings. Agriculture remains significant, from traditional smallholder farming to high-tech agribusiness, reflecting Taigu’s status as a national agricultural high-tech demonstration zone. These heterogeneous social–ecological contexts produce varied governance challenges and differentiated demands for POS. It is noteworthy that rural POS in Taigu, like in other rural areas of China, is collectively owned and managed by village collectives. In addition, rural out-migration is a common issue faced by most rural areas in China, particularly in villages with weak economic development and limited access to surrounding industrial and service sectors [35]. Given the diversity of the socio-ecological context in rural Taigu, as well as the shared institutional and demographic characteristics, this study not only contributes to local understanding but also provides a model foundation and governance implications for rural POS management in other regions of China, especially in economically underdeveloped areas.

Taigu comprises 198 administrative villages, accounting for 42.77% of the district population in 2024 (Figure 3 and Figure 4). Each village typically contains at least one central POS, located in the village core and often adjacent to structures such as theatre stages, temples, or village committee offices. These central POS support agricultural processing, handicraft production, recreation, and community events. Additional POS include entrance spaces, roadside greens, and sports fields.

3.2. Data Collection

Based on the study objectives and context, purposive sampling was employed to select 24 panelists: eight scholars, eight private planners, and eight local government administrators, each with over five years of experience in planning and managing rural POS in Taigu. Although not direct managers or users, these experts provide systematic, multi-village insights, acting as external advisors to enhance POS governance. Government administrators, including village “first secretaries,” contribute operational experience in promoting self-governance; private planners offer practical strategies from multiple projects, while scholars provide evidence-based analyses and recommendations drawn from broader research. It is noteworthy that constructing a collective action model for rural POS self-governance requires identifying and structuring recurring governance conditions, institutional arrangements, and interactions between actors and resources, rather than documenting the specific locational characteristics of all 198 villages. Therefore, panelists are not expected to possess detailed knowledge of each individual POS. Instead, they were selected for their familiarity with the local SES attributes of rural POS in Taigu and the wider region, including local institutional arrangements, socio-cultural aspects, policy frameworks, and shared governance challenges. Accordingly, panelists develop the collective action model by drawing on meso-level insights and experience, linking individual cases to broader governance structures through comparative and analytical reasoning, and synthesizing them into generalizable structural governance conditions. This approach differs from detailed case-by-case analysis and is consistent with established traditions in commons research [10,14].

The panelists participated in three Delphi survey rounds followed by an Analytic Hierarchy Process (AHP) assessment over two months, with the option to withdraw at any stage. This composition ensures a comprehensive spectrum of perspectives [36]. The study employs the DHP method [37], in which multiple Delphi rounds enhance reliability while minimizing panelist fatigue [38,39]. In the first round, panelists completed a quantitative scoring table and responded to open-ended questions. Using a five-point Likert scale, the scoring table assessed the relevance of conditions from the conceptual SES framework to rural POS self-governance in Taigu. Open-ended questions allowed panelists to propose additional conditions, capturing both observed factors and professional judgments on potentially beneficial but currently absent conditions [39,40]. Demographic data, judgment bases, and familiarity with survey content were also collected. Judgment bases were evaluated on four criteria using a three-point Likert scale, and familiarity was rated on a five-point scale. The quantification of these indicators is summarized in

Table 1. Panelists’ judgement bases and familiarity quantification Table for indicators.

Judgement Bases (Ca)	Quantized Value			Familiarity (Cs)	Quantized Value
	Big	Middle	Small
Experience	0.5	0.4	0.3	Very familiar	1
Theoretical analysis	0.3	0.2	0.1	Familiar	0.8
References at home and abroad	0.1	0.1	0.1	Generally familiar	0.6
Intuition	0.1	0.1	0.1	Less familiar	0.4
				Not familiar	0.2

Source: Li et al. [41].

.

Following the first Delphi round, responses were analyzed and new conditions suggested by panelists were incorporated into the second-round questionnaire. Unlike the initial round, the second-round instrument consisted solely of a structured quantitative scoring table, in which panelists rated each condition’s relevance to rural POS self-governance in Taigu using a five-point Likert scale. Anonymous results from the previous round were shared with all panelists to facilitate reflection and adjustment of judgments. The third Delphi round followed the same procedure, enabling panelists to reconsider prior evaluations—a key feature that distinguishes this approach from studies that focus solely on previously agreed conditions [38].

Upon completion of three Delphi rounds, the study identified the key conditions influencing rural POS self-governance. These conditions were subsequently evaluated through a structured Analytic Hierarchy Process (AHP) questionnaire, employing Saaty’s 1–9 scale [42] for pairwise comparisons. Panelists rated the relative importance of each condition, assigning values from 1 (equal importance) to 9 (extreme importance), with intermediate values for moderate differences. Reciprocal values were applied when the comparison direction was reversed, as detailed in

Table 2. Saaty’s 1–9 scale.

Intensity of Importance	Definition
1	Equal importance
3	Moderate importance of the first element over the second element in the pair
5	Essential or strong importance
7	Very strong importance
9	Extreme importance
2, 4, 6, 8	Intermediate values between the two adjacent judgments
Reciprocals of the above non-zero numbers	The inverse of the importance (e.g., a value of 1/5 means that the second element has a very strong importance over the first element in the pair)

Source: Saaty [42].

.

3.3. Data Analysis

Data analysis followed the structure of data collection, comprising three Delphi rounds and a subsequent Analytic Hierarchy Process (AHP) round. Prior to analysis, each panelist’s authority coefficient (Cr) was calculated to assess the validity of the consultation outcomes by quantifying expertise and familiarity [43]. In addition, the Cr in AHP analysis is used as a weighting factor to account for differences among experts in terms of professional experience and disciplinary background. This process is important because differences in experts’ professional experience and academic backgrounds may lead to uneven contributions during the AHP evaluation. Incorporating the authority coefficient as a weighting factor in the AHP analysis helps mitigate biases arising from individual differences, improves the reliability and consistency of judgments, and thereby enhances the robustness of the results [44]. Cr was computed as the mean of the panelists’ judgment basis (Ca) and familiarity (Cs), with Cr ≥ 0.7 considered acceptable [41].

During the Delphi rounds, responses were evaluated for reliability, tendency, and consensus. Reliability was assessed using medians and interquartile ranges (IQR) across rounds, with stability reflecting the consistency and dependability of panelist judgments [38]. Tendency was measured via mean scores, with values ≥ 3.56 indicating general agreement on a condition’s relevance to rural POS self-governance in Taigu [45]. Consensus was assessed using multiple indicators: positive rate, content validity ratio (CVR), IQR, and Kendall’s W. A positive rate ≥ 55% (panelists rating 4 or 5) signified agreement [45]; CVR ≥ 0.37 indicated consensus for 24 panelists [46]; and IQR ≤ 1 demonstrated alignment among more than half of the panelists [38]. Kendall’s W (0–1) measured overall concordance, with W ≥ 0.5 indicating statistically significant consensus and W = 1 representing complete agreement [47]. Conditions satisfying these thresholds in the third Delphi round were deemed relevant for enhancing rural POS self-governance. Evaluation criteria are summarized in

Table 3. Evaluation criteria for Delphi analysis results.

Statistic	Criteria
Median	The median value is relatively stable in several Delphi rounds
Interquartile Range (IQR)	The IQR is relatively stable in several Delphi rounds. IQR =< 1
Mean	Mean >= 3.56
Positive rate	Positive rate > 0.55
Content validity ratio (CVR)	Content validity ratio (CVR) > 0.37
Kendall’s W	Kendall’s W > 0.5

.

After identifying key conditions influencing rural POS self-governance in Taigu through the Delphi method, the Analytic Hierarchy Process (AHP) was employed to determine the relative weight of each condition. Panelists’ responses were used to construct the judgment matrix, which was first tested for consistency to address potential inconsistencies in pairwise comparisons. Consistency was assessed via the consistency ratio (CR), calculated as the consistency index (CI) divided by the random index (RI), with CR < 0.1 indicating an acceptable level of consistency and reliable data. The calculation equation for the CI is shown in Equation (1):

$$\mathrm{C}\mathrm{I}={\displaystyle \frac{{\lambda }_{max}-n}{(n-1)}}$$

(1)

In Equation (1), $n$ represents the order of the matrix, and ${\lambda }_{max}$ denotes the maximum eigenvalue of the judgment matrix. The calculation equation for the maximum eigenvalue is shown in Equation (2).

$${\lambda }_{max}=\sum _{i=1}^n{\displaystyle \frac{{\left[AW\right]}_i}{{nW}_i}}$$

(2)

In Equation (2), $n$ is the matrix order, $A$ is the judgment matrix, $W$ is the weight vector, and ${\left[AW\right]}_i$ represents the $i$th component of the matrix $\left[AW\right]$.

The calculation of $CR$ is shown in Equation (3).

$$CR={\displaystyle \frac{CI}{RI}}={\displaystyle \frac{{\lambda }_{max}-n}{(n-1)RI}}<0.1$$

(3)

The $RI$ value depends on the matrix order, as shown in

Table 4. Random index.

n	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15
RI	0.00	0.00	0.52	0.89	1.11	1.25	1.35	1.40	1.45	1.49	1.52	1.54	1.56	1.58	1.59

.

After validating the collected data from panelists, the study used the geometric mean method (square root method) to calculate the weight of each condition in each judgment matrix, as shown in Equation (4).

$${\mathrm{W}}_i={\displaystyle \frac{(\prod _{j=1}^n{a}_{ij}{)}^{\frac{1}{n}}}{\sum _{i=1}^n(\prod _{j=1}^n{a}_{ij}{)}^{\frac{1}{n}}}},i=1,2,3\dots ,n$$

(4)

In Equation (4), ${\mathrm{W}}_i$ represents the weight of the $i$th condition in the judgment matrix, $n$ is the matrix order, and $a_{ij}$ is the pairwise comparison value between the $i$th row condition and the $j$th column condition in the judgement matrix. After calculating the weights for each condition in each judgment matrix, they are combined using the results aggregation method to form a weight matrix ${\mathrm{W}}^{\prime }$, as shown in Equation (5).

$${\mathrm{W}}^{\prime }=\left[\begin{array}{cccc}{\mathrm{w}}_{11}& {\mathrm{w}}_{12}& {\mathrm{w}}_{1\dots }& {\mathrm{w}}_{1\mathrm{j}}\\ {\mathrm{w}}_{21}& {\mathrm{w}}_{22}& {\mathrm{w}}_{2\dots }& {\mathrm{w}}_{2\mathrm{j}}\\ {\mathrm{w}}_{\dots }& {\mathrm{w}}_{\dots }& {\mathrm{w}}_{\dots }& {\mathrm{w}}_{\dots }\\ {\mathrm{w}}_{\mathrm{n}1}& {\mathrm{w}}_{\mathrm{n}2}& {\mathrm{w}}_{\mathrm{n}\dots }& {\mathrm{w}}_{\mathrm{i}\mathrm{j}}\end{array}\right]$$

(5)

In Equation (5), ${\mathrm{W}}^{\prime }$ represents the condition weight matrix, where $\mathrm{i}$ is the $\mathrm{i}$th panelist and $\mathrm{j}$ is the $\mathrm{j}$th condition. The study calculates each panelist’s weight based on their authority coefficient from the first round of the Delphi survey, as shown in Equation (6).

$$Wp={\displaystyle \frac{{Cr}_i}{{\sum }_{j=1}^n{Cr}_i}}$$

(6)

In Equation (6), ${Cr}_i$ represents the authority coefficient of a panelist, ${\sum }_{j=1}^n{Cr}_i$ represents the sum of authority coefficients of all panelists, and $Wp$ represents the weight of each panelist. In the final step, the study multiplies the weight matrix ${\mathrm{W}}^{\prime }$ by the panelists’ weights $Wp$ to obtain the integrated weight vector $W$ for all conditions, as shown in Equation (7). The research design process is shown in Figure 5.

$$W=W_z{W}^{\prime }=[ W_1, W_2, W_3, W_4,\dots ,W_n ]$$

(7)

4. Research Results

4.1. Demographics of the Panelists

All 24 panelists completed the surveys without withdrawal. As summarized in

Table 5. Demographic profile of panelists (n = 24).

		n (%)
Gender	Male	12 (50%)
	Female	12 (50%)
Age	30–40	13 (54.17%)
	41–50	7 (29.17%)
	51–60	4 (16.67%)
Work experience	5–10	9 (37.50%)
	11–20	8 (33.33%)
	21–30	5 (20.83%)
	31–40	2 (8.33%)
Education	Associate degree	2 (8.33%)
	Bachelor	5 (20.83%)
	Master	8 (33.33%)
	PhD	9 (37.50%)
Occupation	Scholar	8 (33.33%)
	Private planner	8 (33.33%)
	Government administrator	8 (33.33%)

Notes. “n” represents the number of panelists.

, the panel was gender-balanced, with ages ranging from 30 to 60, most between 30 and 40. Professional experience spanned 5–20 years, and all held higher education degrees, predominantly at the postgraduate level. The panel included eight scholars, eight private planners, and eight government administrators. Authority coefficients, derived from quantified judgment bases and familiarity scores, all exceeded 0.7, confirming the reliability and validity of the results (

Table 6. Authority coefficient of the panelists.

	Judgment Bases	Familiarity	Authority Coefficient
1	0.90	0.60	0.75
2	0.90	0.60	0.75
3	0.80	0.60	0.70
4	1.00	0.60	0.80
5	1.00	0.80	0.90
6	0.70	0.80	0.75
7	0.90	0.60	0.75
8	0.80	0.80	0.80
9	0.80	0.60	0.70
10	0.90	0.80	0.85
11	0.90	0.80	0.85
12	0.90	0.60	0.75
13	0.90	0.60	0.75
14	0.80	0.60	0.70
15	0.80	0.80	0.80
16	0.90	0.60	0.75
17	0.90	0.60	0.75
18	0.80	1.00	0.90
19	0.90	0.80	0.85
20	0.90	0.80	0.85
21	0.90	1.00	0.95
22	0.80	0.60	0.70
23	1.00	0.80	0.90
24	0.90	0.60	0.75

).

4.2. First-Round Delphi Analysis

The first-round Delphi results, presented in the Appendix A, identified key conditions influencing rural POS self-governance in Taigu. Panelists highlighted four institutional conditions—“rules are simple and easy to understand,” “ease in enforcement of rules,” “availability of low-cost adjudication,” and “accountability of monitors and other officials to users”; three social conditions—“clearly defined boundaries (Social and political boundaries),” “past successful experiences-social capital,” and “interdependence among group members”; and one interaction condition—“fairness in allocation of benefits from common resources.” Open-ended responses suggested two additional conditions, which were incorporated into the second-round Delphi survey: “public open space adapted to the needs of the majority of users” and “matching the supply of resource with users’ demand.”

4.3. Second-Round Delphi Analysis

Kendall’s W [48] was used to assess overall consensus among panelists, with 0 indicating no agreement and 1 representing complete consensus. As shown in the Appendix A, Kendall’s W increased slightly in the second round, indicating improved alignment among panelists. From the second-round Delphi analysis of 35 conditions, key factors influencing rural POS self-governance in Taigu were identified: two ecological conditions—“well-defined boundaries (physical boundaries)” and “public open space adapted to the needs of the majority of users”; five institutional conditions—“rules are simple and easy to understand,” “ease in enforcement of rules,” “availability of low-cost adjudication,” “accountability of monitors and other officials to users,” and “appropriate levels of external aid to compensate local users for conservation activities”; four social conditions—“clearly defined boundaries (social and political boundaries),” “past successful experiences-social capital,” “appropriate leadership—young, familiar with changing external environments, connected to local traditional elite,” and “interdependence among group members”; and three interaction conditions—“high levels of dependence by group members on resource system,” “fairness in allocation of benefits from common resources,” and “matching the supply of resource with users’ demand.”

4.4. Third-Round Delphi Analysis

The third-round Delphi analysis (Appendix A) produced a Kendall’s W of 0.672, indicating strong consensus among panelists. Key conditions identified for rural POS self-governance in Taigu included two ecological conditions—“well-defined boundaries (physical boundaries)” and “public open space adapted to the needs of the majority of users”; five institutional conditions—“rules are simple and easy to understand,” “ease in enforcement of rules,” “availability of low-cost adjudication,” “accountability of monitors and other officials to users,” and “appropriate levels of external aid to compensate local users for conservation activities”; four social conditions—“clearly defined boundaries (social and political boundaries),” “past successful experiences-social capital,” “appropriate leadership—young, familiar with changing external environments, connected to local traditional elite,” and “interdependence among group members”; and three interaction conditions—“high levels of dependence by group members on resource system,” “fairness in allocation of benefits from common resources,” and “matching the supply of resource with users’ demand.” These conditions were subsequently weighted using AHP to determine their relative importance.

4.5. Results of AHP Analysis

AHP analysis confirmed the consistency of all 24 panelists’ judgment matrices, with CR values reported in

Table 7. Consistency test results for 24 judgement matrices.

Matrix No	CR
1	0.0218
2	0.0209
3	0.0247
4	0.0280
5	0.0209
6	0.0229
7	0.0220
8	0.0229
9	0.0261
10	0.0259
11	0.0209
12	0.0246
13	0.0209
14	0.0289
15	0.0279
16	0.0245
17	0.0182
18	0.0247
19	0.0281
20	0.0345
21	0.0247
22	0.0247
23	0.0190
24	0.0190

. Figure 6 presents the relative weights of the identified conditions. “Fairness in allocation of benefits from common resources” emerged as the most critical factor influencing rural POS self-governance in Taigu. Institutional conditions show marked polarization: “accountability of monitors and other officials to users,” “ease in enforcement of rules,” and “rules are simple and easy to understand” rank just below the top factor, whereas “availability of low-cost adjudication” and “appropriate levels of external aid to compensate local users for conservation activities” occupy the 10th and 14th positions, respectively. Social conditions are generally of moderate importance, led by “clearly defined boundaries (social and political boundaries),” followed by “interdependence among group members” and “past successful experiences-social capital,” with “appropriate leaders-experienced, familiar with rural governance affairs, connected to local traditional elite” ranking relatively lower. Ecological conditions—“well-defined boundaries (physical boundaries)” and “public open space adapted to the needs of the majority of users”—carry moderate weights, slightly below institutional and social factors. Among interaction conditions, “high levels of dependence by group members on resource system” is moderately important, while “matching the supply of resource with users’ demand” ranks lower across all categories. Relevant policymakers may consider prioritizing conditions with higher weights when formulating rural POS self-governance policies. Research has shown that when critical conditions are missing, sustainable commons management cannot be achieved, even if most other conditions are present in POS self-governance [22].

Based on data analysis and SES framework, this study develops a collective action model for self-governed rural POS in Taigu, China. The model is illustrated in Figure 7, and its specifics will be discussed in the next section.

5. Discussions

Panelists identified multiple interrelated factors that shape the self-governance of rural public open spaces (POS) in Taigu, spanning resource characteristics, governance systems, social dynamics, and interactions among users. Within the resource systems and units (RSU), two conditions were deemed moderately influential: “well-defined boundaries (physical boundaries)” and “public open space adapted to the needs of the majority of users.” Clearly delineated boundaries distinguish POS from surrounding land and are closely tied to confirmed land ownership, reducing disputes, encroachment [49]. From a perspective of transaction costs, unclear boundaries imply institutional uncertainty and potential risks associated with specific investments, thereby increasing the costs of POS governance. In China, rural POS must have land ownership and usage rights confirmed through land registration under the Land Administration Law, with collective certificates issued to village collectives or committees. In Taigu, registration of rural POS—including collective construction land—was completed by July 2012, with subsequent modifications managed by the Taigu District Natural Resources Bureau. Such formalization mitigates property conflicts, supports collective governance, and reduces risks of encroachment.

Alignment of POS with the needs of local users further enhances self-governance by lowering participation costs. Villagers tend to prioritize personal benefits, and facilities that do not meet daily production, living, or leisure requirements diminish motivation to engage in governance [50]. For example, Zhang et al. [51] emphasize that when public facilities in rural POS fail to meet residents’ daily needs, villagers not only reduce their frequency of use of these spaces but also become less willing to participate in governance activities. Rural POS in China traditionally support daily life, agricultural production, and handicraft activities [1] and increasingly serve tourism functions in villages undergoing economic transition. Misaligned priorities, such as overemphasizing tourist needs at the expense of villagers’ requirements—as observed in She Village, Nanjing—can reduce self-governance performance [52]. In Taigu, many rural POS primarily host festivals and fail to meet daily production or living needs, reducing users’ reliance on these spaces as well as their willingness to participate in governance. Effective self-governance therefore requires careful allocation of resources to balance the diverse needs of local users.

Governance systems (GS) emerged as another critical determinant. Simple and clear rules reduce transaction costs by minimizing learning requirements and knowledge constraints, while facilitating rapid allocation of responsibilities during governance challenges. Conversely, complex or ambiguous rules can encourage opportunistic behavior [53]. Rules that are easy to implement help maintain governance effectiveness and reduce implementation costs, whereas rules that are difficult to enforce gradually lose their influence. According to Cox et al. [54], governance rules for POS should be adapted to local conditions. In China, management rules for rural POS are typically incorporated into village regulations or related agreements, with the aim of clarifying villagers’ rights and responsibilities regarding use [55]. The effectiveness of such rules largely stems from collective participation by villagers and their consistency with the broader legal framework. Therefore, governance rules for rural POS should be developed through collective participation of villagers. In addition, local governments can assist in drafting POS management rules to ensure compliance with legal requirements and to integrate them into the informal grassroots legal system. In Taigu, some villages have already formulated and publicly issued POS management rules; however, many of these regulations lack detailed implementation procedures and monitoring standards, which limits their effective enforcement in practice.

Conflict resolution mechanisms further support sustainable governance. Commons inherently generate disputes, and efficient, low-cost mechanisms enhance reliability, reduce participation risks, and encourage engagement [7]. In Taigu, unresolved conflicts escalate from village committees to township government or the People’s Mediation Committee, while formal judicial processes remain costly and potentially disruptive to social cohesion. For these low-cost internal conflict resolution mechanisms to function effectively, their operation must be embedded in a fair and just rural political environment. For example, the election process of village leaders should be lawful and transparent. Recent anti-crime campaigns have reinforced fair village leadership elections, supporting low-cost dispute resolution. Monitoring mechanisms are equally essential. “Grid officers,” typically elected by village collectives, supervise POS usage and provide channels for villager feedback [56]. By monitoring opportunistic behavior, accountable monitors can identify and curb such actions, thereby reducing the risks associated with rural POS self-governance and lowering the costs arising from transactional uncertainty in governance. Notably, in some villages in Taigu, POS monitors are village leaders themselves. This arrangement makes it difficult for villagers to hold these leaders accountable for their managerial actions, thereby weakening villagers’ confidence in the fulfilment of their responsibilities.

Although external assistance ranks relatively lower in terms of importance, appropriate support can help compensate for deficiencies in governance systems [9]. According to ‘incomplete contract theory,’ POS self-governance systems cannot perfectly address all contingencies. When local self-governance mechanisms are unable to resolve challenges in rural POS governance, appropriate external intervention can reduce governance costs. For example, government-provided legal guidance can assist village collectives in formulating POS governance rules, while higher-level administrative authorities can help resolve governance issues such as conflicts between villagers and village cadres (see O’Brien [57]). In Taigu, oversight at the township government level helps ensure the legality of village-level elections. In addition, the “Democratic and Rule-of-Law Model Village” initiative launched in 2023 has provided institutional support for revising and strengthening regulations related to rural POS management.

Social and political boundaries delineate actors’ rights and responsibilities, clarifying roles and enabling the rapid identification of accountable parties during disputes, thereby reducing transaction costs [58]. In contrast, unclear boundaries can invite free riders into rural POS, creating uncertainty in the governance environment and increasing the costs of self-governance, such as the appropriation of common space for private use and other behaviors that undermine the fair distribution of resources. These boundaries intersect with institutional conditions, including property rights, management rules, enforcement, and monitoring. Rural POS in China are typically classified as collective construction land, with village collectives holding ownership, management, and usage rights [59]. External entities, such as government bodies or enterprises, may participate through leasing, joint operations, or equity arrangements, particularly to promote rural tourism or economic development [60]. Such hybrid arrangements increase the complexity and cost of clarifying and distributing rights. In Taigu, Yangjiazhuang Village leases POS to external merchants, whereas Yangyi Village’s ‘Sannong Town’ project involves shared management among villagers, government, and enterprises, with jointly established usage and governance rules.

Past successful cooperation fosters social capital and trust, reducing negotiation and monitoring costs for collective action [17]. When similar self-governance problems arise, actors can draw on past successful experiences, thereby reducing the costs associated with collective action. The positive role of social capital has been widely demonstrated in various contexts of rural collective action in China, such as land transfer, community development, and collective production activities [61]. Whether social capital is directly generated through rural POS governance or derived from other sources, higher levels of social capital can improve decision-making efficiency by reducing the costs of negotiation and mutual monitoring among participants. Lehavi [62] notes that social capital may erode in the absence of sustained collective action over time. Therefore, in addition to rural POS governance, cultivating social capital through other forms of collective action is equally important. In Taigu, collective activities organized by village collectives—such as POS cleaning initiatives, POS management meetings, cultural associations, and farmer cooperatives—have helped strengthen social capital, thereby contributing to more effective governance of public open spaces.

Community leaders play a pivotal role in reinforcing trust, coordinating stakeholders, and facilitating access to external resources, reducing transaction costs [63]. Against the backdrop of China’s land transfer policies, in addition to traditional institutional village leaders, a number of non-institutional elites have emerged as key actors in rural commons management. These new-type leaders, who are familiar with modern technologies and management practices, play a pivotal role in governance processes [63]. As a result, rural communities are undergoing a transition from traditional governance structures toward hybrid governance models, enabling them to better cope with increasing economic pressures. This transformation has effectively enhanced the management capacity of rural common resources [64]. However, maintaining a balance between traditional leaders and non-institutional elites is crucial. If the authority of traditional leaders is weakened, it may undermine community cohesion and erode social capital (see Luo et al. [63]). Taking Fancun Village in Taigu as an example, the village collective has formed a partnership with a private enterprise to develop a “tomato specialty town” project. In this project, traditional village leaders organized villagers to establish an agricultural cooperative and cooperated with private investors. The investors built modern agricultural production facilities as well as rural POS infrastructure closely related to villagers’ daily life and production needs, and provided guidance for agricultural production and tertiary sector development. This model has improved the village’s economic conditions, preserved the authority of traditional village leadership, and promoted the accumulation of social capital among villagers. However, the exercise of leadership authority also entails risks: information asymmetry may induce opportunistic behavior, thereby necessitating strengthened monitoring or external intervention—a point illustrated by the case of Beiguo Village [65].

In the self-governance of rural POS, when actors are mutually interdependent in terms of interests, participants are more likely to cooperate, as opportunistic behavior ultimately undermines their own benefits (see Olson [66]). Such interdependence helps reduce transaction costs in POS self-governance. The positive effects of actor interdependence on collective action have been empirically demonstrated in irrigation systems in China [67]. As key sites for agricultural production, rural POS often foster cooperation among villagers, encouraging collective maintenance of these spaces—particularly when most villagers rely on them for grain processing. However, when only a subset of villagers depends on these spaces for agricultural use, conflicts may arise with those who prefer recreational uses, leading to disputes over usage rights and reducing governance efficiency. In some villages in Taigu where household-based farming predominates, farmers commonly use POS for drying grain or processing agricultural products during the harvest season. During this period, they actively maintain cleanliness and comply with relevant rules to avoid disrupting others. This pattern is especially evident in villages with farmer cooperatives, where members maintain strong interdependent relationships across agricultural production and marketing processes.

Actors’ dependence on resources significantly influences governance outcomes. When POS are critical to villagers’ livelihoods, they actively engage in governance and implement management mechanisms to protect their interests, reducing governance costs [10]. Although there is currently no direct empirical evidence demonstrating that villagers’ dependence on rural POS affects the effectiveness of their self-governance, studies of other commons governance cases in rural China have shown a strong relationship between governance outcomes and users’ dependence on shared resources [67]. Given that rural POS function as important commons supporting agricultural production and household-based handicraft activities, villagers’ economic dependence on these spaces is likely to influence their governance. Moreover, as rural POS also serve daily living and recreational purposes, analyses of their governance should also take into account villagers’ emotional or psychological attachment to these spaces. The degree of dependence among group members is shaped not only by the functional services provided by the resource, but also by the social attributes of the actors involved. In some villages in Taigu, when the services provided by rural POS are irreplaceable and villagers’ daily production and livelihoods are highly dependent on them, these spaces tend to be governed more effectively.

Equitable allocation of resources sustains participation. Fairness, shaped by clearly defined boundaries, governance rules, leadership, social norms, and higher-level policies, encourages engagement [9,10]. Allocation must consider diverse needs, including age-specific requirements [68], accessibility [69], and both production and recreational functions. Unfair resource allocation is highly likely to trigger conflicts among users, thereby increasing the coordination costs within POS self-governance. In some villages in Taigu, disputes occasionally arise due to improper resource allocation. To mitigate such conflicts, some village committees proactively intervene by coordinating the distribution of POS during specific periods. For instance, during the harvest season, POS may be allocated to different households for drying and processing agricultural products, or the functions of certain spaces may be temporarily adjusted.

Finally, the alignment of POS services with villagers’ needs influences self-governance efficiency. When POS fulfill daily production, living, or leisure requirements, participation is high and management costs are lower. Misaligned facilities reduce engagement, encourage rule violations, and increase governance costs. Evidence from rural China shows that POS designed primarily for tourism or aesthetics often fail to meet local needs, leading to underutilization or neglect [52]. In Taigu, several POS constructed for recreational purposes are underused because they do not support essential daily or production activities. Perceived benefits further shape motivation, as villagers are more likely to participate when tangible returns—such as convenience, production efficiency, or social utility—are evident [68]. Studies on the self-governance of rural commons in China have found that the resource environment, policy frameworks, and the attributes of actors all influence the degree of alignment between resource provision and users’ needs [51,52,70].

6. Conclusions

By embedding specific design principles—derived from the conditions facilitating sustainable commons management proposed by Wade [8], Ostrom [7], Baland and Platteau [9], and Agrawal [10]—as functional attributes within the structural categories of the SES framework, this study develops a collective action model for rural POS self-governance aimed at achieving sustainable governance. Within this model, the resource system and units are characterized by clearly defined boundaries and alignment with the needs of primary users. Actors are represented by accountable, high-social-capital, experienced, and reputable leaders, as well as interdependent community members. The governance system is built upon simple, enforceable, and well-monitored institutional arrangements, supported by appropriate external assistance. These institutional–social–ecological attributes interact to foster interdependent groups and POS that meet diverse user needs, thereby enabling sustainable governance outcomes. TCE serves as the underlying efficiency logic, evaluating these attributes in terms of minimizing “frictions”—particularly information, negotiation, and enforcement costs. When these embedded conditions are satisfied, the SES structure shifts from a static configuration to an active state of sustainable self-governance, ensuring the long-term resilience and equitable use of rural POS. The proposed collective action model can be regarded as a meso-level baseline framework for POS governance, providing a systematic foundation for both practice and future research. First, it can guide the formulation of rural POS governance strategies in Taigu. Moreover, grounded in the extensive experience of experts, the model is scalable and not confined to specific case studies; rather, it is applicable to rural POS governance and research in regions with similar institutional–social–ecological conditions—particularly economically underdeveloped and ecologically fragile areas in northern China. Based on these findings, this study further proposes five practical management implications to improve POS self-governance in Taigu and its surrounding rural areas, offering actionable guidance for sustainable POS management.

A fundamental consideration is the clarity of property and usage rights. Rural POS should be established on collective construction land free from disputes, and when land ownership changes occur, village collectives, villagers’ groups, or other land rights holders must promptly complete registration and transfer procedures. For POS involving external actors, clearly defining the rights and responsibilities of all stakeholders through legal and management regulations is essential to provide a stable institutional foundation for self-governance.

Equally important is the design and functionality of POS. Aligning POS services with the diverse needs of villagers enhances participation and reduces management costs. Villagers’ requirements fluctuate throughout the year, and proactive coordination by village committees can optimize resource allocation and maximize collective satisfaction. In Taigu, many POS currently fall short of meeting these needs; however, coordinated management can improve usage efficiency and foster engagement.

The governance framework itself is critical for sustaining effective self-governance. Detailed and enforceable management rules—developed with active villager participation and, where necessary, government or legal guidance—ensure clarity, compliance, and operational effectiveness. Complementing this, the fair election of village leaders, POS managers, and monitors, coupled with accessible feedback and supervision channels, promotes accountability and reduces opportunistic behavior. While elections in Taigu are supervised by township governments, ongoing monitoring mechanisms remain uneven across villages, highlighting the need for standardized oversight and continuous support.

Building social capital and fostering collective action beyond POS-specific governance further strengthen self-governance capacity. Farmers’ cooperatives, cultural associations, and recreational groups cultivate interdependence among villagers, enhance collective capabilities, and facilitate cooperation with external stakeholders. In Taigu, such organizations support agricultural productivity while reinforcing relationships between local communities and external actors, creating a more cohesive governance environment.

Finally, interactions with external elites require careful management. Village leaders should act as coordinators and resource allocators, leveraging social networks to mediate among stakeholders, organize collective action, and prevent excessive external influence. Leaders who successfully balance collaboration with external actors while maintaining village authority preserve community cohesion and safeguard the long-term capacity for self-governance.

This study makes significant theoretical and empirical contributions. From a theoretical perspective, this study translates the enabling conditions and design principles proposed by Wade, Ostrom, Baland and Platteau, and Agrawal into a context-specific governance model for rural POS. This model provides a systematically defined set of variables and relationships, offering a clear reference for subsequent empirical analyses based on residents and local managers. Future research can build on this model to examine the effects and interactions of these variables in specific cases of rural POS governance.

Empirically, this research represents the first application of the SES framework to POS self-governance in China. By developing a collective action model for self-governed rural POS in Taigu, the study identifies conditions that facilitate sustainable self-governance and highlights their practical implications. The findings enable village collectives to base management rules on identified conditions, while governments and planners can use the model to inform governance strategies. The five managerial implications provide actionable guidance for village collectives and policymakers in formulating rules and implementing governance measures, contributing to enhanced participatory, integrative, and sustainable human settlement management, thereby supporting Sustainable Development Goal (SDG) 11, particularly SDG 11.3.

Despite these contributions, the study has several limitations. First, this study focuses exclusively on rural POS in Taigu. Although the area exhibits socio-ecological diversity, the external validity of the findings has not been further empirically validated. Future studies should examine POS self-governance across diverse regions to complement and refine the findings. Second, as this study represents an early-stage exploratory effort focused on structuring governance conditions, its design does not fully capture the context-specific dynamics of local POS management. However, this does not diminish the importance of examining practical and informal governance processes in specific settings. In the next stage of research, insights from villagers’ practical experiences can be considered and incorporated to empirically validate, refine, and improve the rural POS collective action model, thereby enhancing its alignment with everyday practices and local governance dynamics.