Traditional approaches to influencing factors research focus on quantitative analysis, which makes it difficult to explore causality behind complex results. This study uses the qualitative comparative analysis (QCA) method proposed by American sociologist Charles to analyze the causality behind the complex results. QCA is a social science research method based on fuzzy mathematics and set theory, which combines quantitative mathematical statistics analysis with qualitative data analysis. QCA shows that a particular outcome or output (Y) is the result of the combined action of several interrelated influencing factors (X). That is, a particular outcome may be caused by a single influence or a combination of complex factors. Therefore, QCA combines the advantages of quantitative and qualitative research (Ragin, 1987) and is good at explaining the causal relationships behind complex phenomena. Methodologically, QCA is particularly suitable for multi-case comparative studies in the range 10–60 (Bennett and Elman, 2016). This approach allows for the interpretation of multiple concurrent paths of farmer participation affecting environmental governance effects by combining different conditional variables, which goes beyond the limitations of a single case or a single variable explanation. The specific operation steps of this method are as follows: Firstly, define the result variables and condition variables, formulate calibration rules, and assign values to variables according to the case facts and theoretical knowledge (Fiss, 2007). Secondly, establish a truth table to present the score combination of condition variables and result variables of each case in detail. Thirdly, using fsQCA software to calculate the truth table, the combination of sufficient and necessary conditions of the result was obtained. For a more detailed software manual, see Ragin (2017).

For the research problem in this paper, QCA has the following adaptability. First, QCA is suitable for the analysis of small and medium-sized sample sizes and can analyze multi-cause concurrent events. Since it is difficult to obtain relevant official data on farmers’ participation in affecting the effect of environmental governance, it is impossible to carry out complex statistical studies with large samples, and regression analysis is not applicable. We collected 15 cases of rural environmental governance in China through a combination of official websites and field research. FsQCA software was used to reveal the coupling relationship between different factors, and then to reveal the combination path of farmers’ participation in affecting the effect of rural environmental governance. Second, from the existing literature studies, farmers’ participation in affecting the effect of rural environmental governance is a complex causal logic involving the interaction of many factors. QCA allows us to show the coupling relationship between different factors through combination condition analysis, and reveal the generation path and mechanism of farmers’ participation in affecting the effect of rural environmental governance. Combined with variable characteristics and case situations, this study uses the CsQCA method to explore the core factors and mechanisms of farmers’ participation affecting the effect of rural environmental governance. CsQCA is used in this study because the conditional dichotomy required by CsQCA follows the binary logic of “do this or do that”, which is a good reflection of real-world decision-making practices (Blackman, 2013) and helps inform decisions in complex systems (He et al., 2024).

The purpose of this study is to explore the factors and paths that affect the effect of farmers’ participation in rural environmental governance. Therefore, data selection needs to meet two basic requirements: On the one hand, based on QCA best practices, case selection should follow the principle of “achieving maximum variation on the basis of maximum similarity” (Mahoney and Goertz, 2004), which means diversity of case selection. On the other hand, the cases must meet the requirements of achieving good environmental governance participation, and it is necessary to collect cases of farmers participating in environmental governance and achieving good results. On this basis, the principles of case collection and selection are set up: First, representativeness, cases should achieve good results in a certain field, and be recognized by the local government and the masses. The second is diversity, and cases need to involve different areas of rural environmental governance, rather than focusing on just one area. The third is data availability and comprehensiveness. The selected case data should be as rich and comprehensive as possible, including statistical data, public reports, academic research literature, official policy texts, and other data related to rural environmental governance.

Following the above principles, we acquire cases in two ways. First, we used effective cases retrieved from the National Typical Cases of Rural Public Services issued by the National Development and Reform Commission, the official websites of local governments, and the Peking University Talisman database as our sampling framework. The initial database included 23 cases, but 10 cases were excluded due to low data availability. We also applied QCA best practices to distinguish between cases and data verifiability criteria, thus excluding three cases that did not meet the requirements. In the end, 10 cases were collected in this way. In QCA analysis, this sample size meets the requirements for small and medium-sized sample analysis (Rihoux and Ragin, 2009). Secondly, the research team conducted research on grassroots ecological and environmental governance in CS, SS, YZ, and LD cities of H Province in June- July 2022 and January- February 2023. Interviews with township leaders, staff, and people familiar with grassroots environmental governance work. Conduct field surveys on local environmental governance and collect information on policy documents, internal data, public data, governance ledgers, and results reports. The research was carried out in the form of semi-structured interviews, open symposia, and individual talks. After interviews and qualitative data collection, five villages were selected as case samples for this study. Therefore, this study finally obtained 15 case samples (see Table 1).

Variables include result variables and condition variables. In this study, the effect of rural environmental governance is taken as the outcome variable. If the case or official report is recognized and selected as a typical governance case at a local or higher level, the governance effect is judged to be good, and the value is 1. On the contrary, if the case is not officially reported and is not selected as a typical case, the governance effect is judged to be poor, and the value is 0. The exploration of the effect of rural environmental governance aims to explore which influencing factors and their combinations can have a positive impact on rural environmental governance by analyzing the conditional variables related to farmer participation.

Necessary and sufficient conditions for calculating results using fsQCA3.1b software. The calculation results are shown in Table 3. A necessary condition usually means that the condition variable guiding a particular outcome is always present, and if the consistency level is greater than 0.9, then the condition variable can be considered necessary for a particular outcome (Peer, 2011). When the consistency of a condition variable is between 0.8 and 09, it is considered a sufficient condition for the result variable. The results show that the conditional consistency level of the good governance effect is lower than 0.9, indicating that there is no necessary condition for the good governance effect, but the participation channel (consistency = 0.875) can be regarded as a sufficient condition for good governance effect. At the same time, insufficient participation ability (consistency = 1) is a necessary condition for poor governance results, and limited participation channels constitute a sufficient condition for poor governance results. The necessity analysis results show that the improvement of the effect of farmers’ participation in promoting rural environmental governance is the result of the combination of multiple causes. Therefore, we will conduct an analysis of the conditional configuration next to obtain more information about the path of farmers’ participation in influencing the effect of rural environmental governance.

In this study, we used fsQCA3.1b software to analyze the intermediate solution and simple solution of farmers’ participation in producing good environmental governance effects. The statistical analysis results are shown in Table 4. In the analysis results, QCA requires that the consistency of the solution should be greater than 0.8, and the coverage rate should be higher than 0.5. This shows that our calculation results meet the requirements of consistency and coverage. The results show that there are five configurations of farmers’ participation in producing good environmental governance effects. The consistency of the five configuration paths is 1, and the coverage is 0.875, indicating that five interpretation paths can explain 87.5% of the case sample. In addition, the core and edge conditions are distinguished based on the union of simplified and intermediate solutions (Lou et al., 2022). In Table 4, the condition variables that appear in both the intermediate solution and the simple solution are the core variables and are represented by “•” in the path. Other condition variables are auxiliary conditions that have relatively little influence on the result variable and are represented by “Δ.” Spaces indicate that the presence or absence of a conditional variable is irrelevant to the result.

Among them, Configuration one shows that participation ability and supervision & punishment play a core role, and interest association and information disclosure play an important auxiliary role. This means that farmers’ participation ability and the government’s supervision and punishment mechanism are important conditions to promote farmers’ active participation in rural environmental pollution control. In Configuration 2, participation ability, participation channel, and supervision & punishment play a core role, while interest association and demand response play an important auxiliary role. This means that farmers, driven by strong participation ability, enter the field of governance through diverse and unimpeded channels of participation. Subject to effective government response and clear rules of engagement, governments and farmers can work together to control environmental pollution. In Configuration 3, participation ability and participation channel play a core role, while interest association, demand response, and information disclosure play a supplementary role. This means that farmers have a strong incentive and willingness to participate, and the government can effectively respond to participation and provide information support. With multiple channels of participation, the interaction between individual needs and government goals can be achieved, and the impetus for collective action can be formed. In Configuration 4, participation channel and supervision & punishment constitute the core conditions for promoting good governance in rural environments, which means that clear and specific supervision and punishment norms are important conditions for ensuring effective participation. In Configuration 5, participation ability and participation channel are the core conditions, and demand response plays an auxiliary role. In addition, weak interest correlation, ineffective regulatory penalties, and insufficient information disclosure also play an important role. This means that when farmers have the ability to participate and the channels for participation are smooth, their participation in environmental governance is not entirely driven by interests. Instead, they are motivated to respond to the demands of governance. From the perspective of a single condition (horizontal), participation ability and participation channel play a core role in the configuration of multiple conditions, indicating that farmers’ participation ability and willingness and participation channel have an important driving effect on their participation in environmental governance. Participation channel, as the core condition, further validates its sufficient condition result in necessity analysis.

Based on the configuration analysis of conditional variables, the mechanism of farmers’ participation in improving the effect of rural environmental governance was summarized and refined. According to the five configurations, three mechanisms of farmers’ participation in improving the effect of rural environmental governance were extracted. That is, the two-wheel drive mechanism (Path 1) in which dynamic and process factors are coupled to produce good environmental governance effects, the process empowering mechanism (path two and path 5) in which process factors are strongly empowered to produce good environmental governance effects, and the comprehensive support mechanism (path three and path 4) in which dynamic - process - guarantee factors are coupled to produce good environmental governance effects.

(1) Two-wheel drive mechanism coupled with dynamic and process factors. Configuration one is a typical path that represents the coupling of dynamic factors and process factors to produce good environmental governance effects. The core conditions of this path include participation ability and supervision & punishment, combined with interest correlation and information disclosure as auxiliary conditions. In this mechanism of farmers’ participation in improving the effect of rural environmental governance, although farmers lack diversified channels and effective demand response to participate in environmental governance work. However, under the joint drive of strong participation ability, effective supervision & punishment, and moderate interest correlation, farmers can still use limited participation channels to improve the effect of rural environmental governance.

Case 1 is a typical example of the two-wheel drive mechanism. In Case 1, villages served as the basic units for action. Special task forces for improving rural living environments were established by organizing village cadres, stationed work teams, and grid administrators. These groups convened public meetings to solicit feedback and suggestions from farmers, effectively mobilizing them to actively participate in environmental improvement efforts. This significantly enhanced the farmers’ ability to engage in environmental governance. At the township level, a three-list system was implemented—comprising a “problem list,” a “responsibility list,” and a “rectification list.” A supervisory task force, organized by the township discipline inspection committee, conducted follow-up inspections and reviews. Tasks that were completed were checked off the list, while grid administrators who failed to meet rectification requirements were suspended from their duties to focus solely on completing the necessary corrections within a set timeframe. At the village level, a “red and black list” system was introduced. Comprehensive inspections of all natural villages were conducted quarterly, with monthly announcements of the red and black lists at the natural village level, and quarterly updates at the administrative village level. This system continuously improved the standardization of farmer participation in governance and provided institutional support and supervision for effective management. Thus, the combination of moderate participation ability and a system of supervision and penalties serves as a driving force, enabling rural residents to effectively address environmental issues.

(2) Process empowering mechanism dominated by process factors. The core conditions of this path include participation ability, participation channel, and supervision & punishment, combined with interest correlation and demand response as auxiliary conditions. This shows that even if there is a lack of adequate environmental information disclosure, the combination of strong participation ability, diversified participation channels, effective supervision & punishment can ensure that farmers’ participation can produce good environmental governance effects. Appropriate interest correlation and the government’s response to farmers’ participation appeal play an important role in promoting and assisting.

Case 6 is a typical example of the process empowering mechanism. In Case 6, a special task force for rural living environment improvement was established, composed of stationed village officials and university-graduate village officers. This team was responsible for educating rural residents about the importance of environmental governance and informing them of the specific methods and channels available for participation. This effectively enhanced farmers’ participation ability and clarified the channels for their involvement. Meanwhile, during their visits throughout the villages, the task force also played a dynamic supervisory role by identifying environmental issues and promptly implementing appropriate punitive measures. Additionally, the village organized weekly public clean-up campaigns, engaging all residents in collective efforts to remove waste from public areas. A “Home Beauty Points Supermarket” was also established. In this system, farmers could accumulate points through participation in environmental sanitation improvement activities and “Beautiful Courtyard” initiatives. These points could then be redeemed for daily necessities such as buckets, clothes racks, electric kettles, and laundry detergent. This system subtly linked farmers’ interests with environmental governance. Through the combination of enhanced participation ability, clear participation channels, dynamic supervision & punishment, and interest-based incentives, the village successfully motivated residents to actively engage in environmental governance, thereby achieving effective and sustainable environmental management.

(3) Comprehensive support mechanism of dynamic-process-guarantee factor coupling. The core conditions of this path include participation ability and participation channel, combined with interest correlation, demand response, and information disclosure as auxiliary conditions. The comprehensive support mechanism shows that the aggregation of multi-link factor energy is the key to ensuring farmers’ participation in improving the effect of rural environmental governance. As long as participation ability and participation channel are guaranteed, farmers can achieve effective participation with the support of interest correlation, demand response, and information disclosure elements, overcome the difficulties of lack of supervision & punishment, and improve the effect of environmental governance.

All in all, there are three different mechanisms for farmers to participate in improving the effect of rural environmental governance: two-wheel drive, process empowering, and comprehensive support. These three mechanisms indicate that farmers’ participation in improving the effect of rural environmental governance is the result of multi-factorial coupling.

Case 7 is a typical example of the comprehensive support mechanism. In Case 7, although no explicit supervision and punishment system was established at the village level, the local government played a supportive role through multiple channels. It distributed brochures on rural living environment improvement, promoted informative articles via WeChat public accounts, and converted promotional content into audio formats. These were broadcast repeatedly through village loudspeakers, sanitation vehicle speakers, and handheld “mini-speakers” to encourage residents to abandon unhealthy living habits and to familiarize themselves with the various channels and methods for participating in environmental governance. These efforts significantly improved farmers’ environmental awareness and participation abilities. At the same time, the government actively and promptly responded to residents’ concerns about rural living conditions. A three-level response system was established, involving farmers, village cadres, and township officials. In addition to being responsive, the authorities proactively disclosed relevant information to all villages, including policies on rural environment improvement, funding usage, and the status of rectification efforts. This transparency ensured farmers’ right to be informed and to participate. Ultimately, these combined efforts generated an internal motivation among farmers to engage actively in rural environmental governance, resulting in effective management of the village environment.

The consistency level setting affects the number of logically minimized truth table rows, which in turn affects the result. Schneider and Wagemann (2012) proposed a robustness test by adjusting the consistency level. In this work, the robustness of the results is tested by adjusting the consistency level. If the consistency level between the generated conditional configurations is changed, there is still a clear subset relationship. The results are considered to be document-reliable, even if there are differences in specific configurations. In contrast, the results are not robust. In this study, by reducing the consistency level from 0.85 to 0.8 or increasing it to 0.9, the consistency level of the global solution did not change significantly, and the configuration did not change significantly. Therefore, after adjusting the threshold of the consistency level, the configuration conclusions of this study did not change substantially, and the results were considered robust.

A key contribution of this study is the shift from isolated variable analysis to a configurational perspective. By constructing a “dynamics–process–support” coupled analytical framework, the study identifies three governance mechanisms: the two-wheel drive mechanism, the process empowering mechanism, and the comprehensive support mechanism. These mechanisms explain why and how farmer participation can improve governance outcomes at a deeper, more systemic level. This mechanistic explanation responds to past criticisms of participation studies for neglecting variable interactions and instead emphasizes the interactive role of participation within a system. The findings show that effective environmental governance does not depend solely on whether farmers are “passively involved” but hinges on the organic interplay among multiple layers of factors. This marks a transition from studying “influencing factors” to exploring “mechanisms”, providing both theoretical reference and practical guidance for farmer participation in environmental governance.

Furthermore, this study responds to the tension in participatory governance literature between “participation quality” and “governance effect.” For example, some configurations yield good results even with limited information disclosure, while others require robust information support. This suggests that participation quality is relational and context-dependent rather than absolute. Its effect depends on how it interacts with other governance dimensions. This echoes the view that participatory practices exist along a continuum between democratic and technocratic governance (Bäckstrand, 2006). As the literature increasingly shifts toward co-governance models (Ansell and Gash, 2008), governance effect ultimately depend not on the quantity of participation but on its quality, responsiveness, and institutional embeddedness.

The critical role of participation channels in this study supports prior findings that accessible and diversified participation pathways are the foundation of meaningful involvement. Nearly all configurations that led to effective governance outcomes emphasized the importance of participation channels. This finding aligns with Arnstein’s (1969) “Ladder of Citizen Participation” theory, which posits that participation becomes substantive—not merely symbolic—only when institutional design guarantees meaningful power-sharing mechanisms. Existing research has shown that farmers’ internet access (He et al., 2021), environmental knowledge (Zhang et al., 2022), and access to usable participation channels significantly enhance their willingness and effectiveness in engaging with environmental governance. Chen and Liu (2022) also noted that a lack of clear participation methods is a key barrier to civic involvement in environmental governance. Furthermore, when farmers are involved in more critical domains and political activities, urban-rural environmental governance receives stronger support (Huang et al., 2024).

For instance, in Case 5, the local government used home visits, media outreach, and WeChat platforms to diversify participation methods, enabling more inclusive governance. This institutionalized design allowed farmers to truly engage in governance processes, aligning with Fung’s (2006) three key elements of participation quality: degree of communication, redistribution of power, and representativeness.

The study finds that a lack of participation ability is a necessary condition for poor governance outcomes, reinforcing the foundational role of ability building for effective participation. Even when participation opportunities exist in form, farmers who lack environmental literacy, technical knowledge, or organizational skills often fail to translate participation into governance influence (Meng et al., 2022). This indicates that “having opportunities to participate” does not equate to “effective participation”. This distinction echoes the theory of participatory governance that differentiates between nominal and substantive participation. It also aligns with Rowe and Frewer’s (2000) argument that many participation mechanisms fail not because of poor design but because the public lacks the knowledge and skills to engage meaningfully. A critical solution to this issue is for governments to enhance information disclosure and promote environmental policy awareness (Yang et al., 2022).

For example, organizing diverse environmental awareness campaigns and tailoring strategies to farmers’ specific characteristics (Yu et al., 2024) can strengthen their capabilities and willingness to participate, ultimately improving governance outcomes. Some studies further reveal that as farmers’ participation abilities improve, the influence of social networks and norms on participation behavior diminishes (Wang et al., 2022), highlighting the central role of ability in sustaining governance outcomes. Such capacity-building efforts enhance environmental literacy, enabling more impactful participation. This aligns with the theory of deliberative democracy by Dryzek (2000), which emphasizes informed civic participation as a prerequisite for effective governance. Fischer (2000) also argues that better-informed participants are more likely to make sound judgments, thereby improving the quality of environmental governance.

Although factors such as interest correlation, supervision & punishment, demand response, and information disclosure are not individually sufficient to drive effect of environmental governance, they serve as important interactive catalysts. Their effectiveness depends on how they are embedded within the overall participation mechanism. This study finds that interest correlation acts as a catalyst for encouraging farmer participation and enhancing governance outcomes. Including key stakeholders with a direct interest in environmental governance (Yao et al., 2020; Sun et al., 2016) can help mitigate NIMBY conflicts and promote policy implementation. Field research from several cases showed that the stronger the interest relevance, the greater the farmers’ motivation to engage. For instance, in Case 11, farmers were more inclined to participate in addressing pollution near their homes but showed lower willingness to act on issues in public areas.

Additionally, the study reinforces the positive role of supervision & punishment in improving governance effect. In Case 1, the “Red-Black List” system reinforces behavioral constraints and a sense of responsibility, aligning with Ostrom’s (1990) institutional arrangement of “monitoring and graduated sanctions” in the management of common-pool resources. It also finds that the effects of responsiveness and information disclosure must be understood in conjunction with other factors. This partially addresses scholarly debates over the uncertain effects of governmental responsiveness (Yan and Luo, 2024), suggesting that such effects depend on capabilities and participation channels.