Factors influencing herders' willingness to engage in grassland ecological restoration in Ruoergai County.

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Learn more: PMC Disclaimer | PMC Copyright Notice Sci Rep . 2026 Mar 6;16:12411. doi: 10.1038/s41598-026-39449-9 Search in PMC Search in PubMed View in NLM Catalog Add to search Factors influencing herders’ willingness to engage in grassland ecological restoration in Ruoergai County Chuhao Shen Chuhao Shen 1 School of Design, Kashi University, Kashi, 844000 China Find articles by Chuhao Shen 1, ✉ , Kun Wang Kun Wang 2 School of Design, Jiangnan University, Wuxi, 214122 China Find articles by Kun Wang 2 , Linyu Huang Linyu Huang 3 Department of Performance, Film and Animation, Graduate School, Sejong University, Seoul, 05006 Korea Find articles by Linyu Huang 3 , Zhonghui Chen Zhonghui Chen 1 School of Design, Kashi University, Kashi, 844000 China Find articles by Zhonghui Chen 1 , Haibo Yuan Haibo Yuan 3 Department of Performance, Film and Animation, Graduate School, Sejong University, Seoul, 05006 Korea Find articles by Haibo Yuan 3 , Limin Zheng Limin Zheng 3 Department of Performance, Film and Animation, Graduate School, Sejong University, Seoul, 05006 Korea Find articles by Limin Zheng 3 Author information Article notes Copyright and License information 1 School of Design, Kashi University, Kashi, 844000 China 2 School of Design, Jiangnan University, Wuxi, 214122 China 3 Department of Performance, Film and Animation, Graduate School, Sejong University, Seoul, 05006 Korea ✉ Corresponding author. Received 2025 Sep 3; Accepted 2026 Feb 5; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13083994  PMID: 41792327 Abstract With the intensification of global climate change and human activities, grassland ecological degradation has become a prominent issue constraining ecological security on the Qinghai–Tibet Plateau and the sustainable development of pastoral areas. Existing research on pastoral grasslands has largely focused on surface-level variables such as policy responses and the acceptance of ecological compensation, with limited systematic exploration of the psychological and emotional factors underlying herders’ ecological behavioral intention. In particular, empirical analyses based on well-established theoretical frameworks remain scarce. In Ruoergai County, where grassland degradation is severe, the pathways and synergistic mechanisms through which key factors such as place attachment and risk perception influence behavioral intention have yet to be systematically verified, which to some extent restricts the precision of ecological policy interventions and the sustainability of governance outcomes. Therefore, this study aims to systematically reveal the formation mechanism of herders’ intention to engage in grassland ecological restoration. Drawing on the Value–Belief–Norm (VBN) theory and incorporating two extended variables—risk perception and place attachment—this study constructs a theoretical model and employs both structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) for dual validation. To enhance accessibility and sample representativeness in pastoral areas, a mixed data collection strategy combining online and offline questionnaire surveys was adopted. Based on this research design, 620 valid questionnaire responses were collected from pastoral grassland areas of Ruoergai County, Sichuan Province. The study employed scale measurements to ensure both reliability and cultural adaptability. The SEM results indicate that value cognition, risk perception, and place attachment all exert significant positive effects on ecological restoration belief, which in turn significantly promotes the formation of personal norm. Personal norm further enhances herders’ intention to engage in ecological restoration. In addition, both risk perception and place attachment have direct positive impacts on herders’ ecological restoration intention. The fsQCA results further reveal that the synergy of high levels of value cognition, risk perception, place attachment, ecological restoration belief, and personal norm constitutes a key configuration for fostering strong ecological restoration intention among herders. This study extends the applicability of the VBN theory to the context of herders’ grassland ecological restoration behavior and emphasizes that integrated strategies—such as shaping value cognition, strengthening risk perception, and cultivating emotional bonds of place attachment—should be adopted to enhance herders’ participation in grassland ecological restoration. The findings provide both theoretical and practical references for optimizing ecological governance policies and designing behavioral interventions in pastoral areas. Keywords: Grassland ecological restoration, Herders’ behavioral intention, Value–Belief–Norm theory, Risk perception, Place attachment Subject terms: Ecology, Ecology, Environmental social sciences Introduction With the intensification of global climate change and human activities, grassland ecosystems are experiencing increasingly severe degradation, as exemplified by ecologically fragile regions such as the Qinghai–Tibet Plateau. Grassland degradation manifests through vegetation loss, soil desertification, and hydrological disruption, thereby amplifying regional ecological risks and socio-economic vulnerability. In China, grasslands cover approximately 400 million hectares, accounting for 41.7% of the national land area, and function as both a critical ecological barrier and the material foundation of pastoral livelihoods 1 . Consequently, grassland degradation constitutes not only an environmental problem but also a coupled ecological–social challenge affecting the sustainability of pastoral regions. Against this backdrop, China has undertaken extensive and sustained efforts to promote large-scale grassland ecological restoration. Driven by concerns for ecological security and international sustainability commitments such as the United Nations Sustainable Development Goals (SDGs), the Chinese government has implemented a series of institutional interventions. In particular, the third round of the Grassland Ecological Protection Subsidy and Incentive Policy (2021–2025) encourages herders’ participation in restoration through measures including grazing bans, rotational grazing, and grass–livestock balance regulation 2 . However, accumulating evidence indicates that the effectiveness of such policies depends not only on institutional design, but also on the behavioral responses of local stakeholders—especially herders—whose perceptions, motivations, and intentions directly shape governance outcomes. As the primary users and managers of grassland resources, herders’ behavioral decisions are closely linked to both policy implementation and long-term ecosystem sustainability. In regions such as Hulunbuir, where more than 4.83 million hectares of grassland have experienced degradation, ecological decline has intensified livelihood pressures and increased production risks for herders 3 . Grassland degradation therefore affects livelihood security, demographic stability, and cultural continuity in pastoral regions. Under these conditions, stimulating herders’ intrinsic motivation to shift from passive policy compliance toward more proactive forms of ecological stewardship has become a central challenge in contemporary grassland governance. Despite sustained policy investment, multiple governance bottlenecks persist in practice, including heterogeneous policy responses, limited continuity of restoration behaviors, and uneven levels of cooperation among herders. These challenges suggest that reliance on external regulation and economic compensation alone may be insufficient to ensure durable restoration outcomes, particularly as governance paradigms shift from coercive management toward participatory and collaborative models. Neglecting herders’ internal motivational mechanisms may increase governance costs, reduce policy efficiency, and undermine long-term restoration effectiveness—concerns that have been increasingly emphasized in studies of community-based environmental governance and participatory restoration 4 – 7 . Accordingly, clarifying the psychological mechanisms underlying herders’ ecological restoration behavior has become an important research priority. Existing research on grassland restoration has predominantly focused on biophysical degradation processes, monitoring techniques, and engineering-based restoration pathways. Extensive studies have documented grassland degradation dynamics and evaluated technical interventions such as grazing prohibition and artificial restoration across the Qinghai–Tibet Plateau and other regions of China 5 – 9 . From a policy perspective, scholars have further assessed the ecological and socio-economic effects of state-led restoration programs, with particular attention to ecosystem service outcomes and policy efficiency 10 , 11 . While these studies provide essential ecological and institutional insights, they tend to treat herders as passive recipients of policy measures rather than as active behavioral agents. At the micro-behavioral level, an increasing body of research has begun to recognize herders as key actors in grassland governance. Empirical studies indicate that herders’ willingness to participate in ecological restoration is influenced by household characteristics, income structure, policy awareness, and perceived livelihood risks 12 , 13 . Institutional analyses have further identified conflicts of interest between herders and conservation authorities, highlighting the necessity of cooperative governance arrangements 14 . More recently, behavioral and psychological factors—such as emotional attachment to grasslands, perceived ecological risk, and grazing decision preferences—have been incorporated into pastoral studies, extending analytical attention beyond purely economic or institutional explanations 15 , 16 . However, these factors are often examined in isolation, and their interrelationships remain insufficiently theorized. Beyond pastoral contexts, ecological behavioral intention has been widely examined among farmers, urban residents, and other social groups, with research focusing on pro-environmental behavior, resource conservation, and responses to environmental risk 17 – 22 . Within this literature, the Value–Belief–Norm (VBN) theory has emerged as one of the most influential frameworks for explaining pro-environmental behavior. The VBN framework posits that environmental behavior is driven by a sequential mechanism linking value orientations, ecological beliefs, and personal moral norms, and has been empirically validated across diverse environmental contexts 23 – 27 . Its emphasis on internalized motivation makes it particularly relevant for understanding environmentally responsible behavior in contexts where long-term compliance and voluntary participation are essential. Despite these theoretical advances, research on pastoral grassland regions remains fragmented, with limited integration of psychological mechanisms into a unified analytical framework. In ecologically vulnerable areas such as Ruoergai County on the eastern Qinghai–Tibet Plateau, empirical studies grounded in mature behavioral theories remain scarce. Although some studies have introduced variables such as place attachment and risk perception into pastoral behavior research 13 , 28 , the causal pathways, interaction effects, and configurational mechanisms through which these factors jointly shape ecological restoration intention have not been systematically examined. Ruoergai County, located in the Aba Tibetan and Qiang Autonomous Prefecture of Sichuan Province, represents a typical pastoral region characterized by high ecological sensitivity and strong dependence on grassland-based livelihoods. As a key national ecological function zone and an important wetland conservation area, the region has experienced persistent grassland degradation and wetland shrinkage since the early 2020s, posing sustained constraints on both ecological security and pastoral livelihoods 29 . More than 90% of the local population relies directly or indirectly on pastoral production, making herders’ behavioral responses particularly consequential for the sustainability of ecological governance 30 . The region therefore provides a suitable empirical context in which ecological vulnerability, livelihood dependence, and policy intervention intersect. Against this background, this study examines how psychological and contextual factors jointly shape herders’ willingness to engage in grassland ecological restoration. Specifically, it addresses the following research questions: What psychological and contextual factors influence herders’ behavioral intention toward grassland ecological restoration? How are the causal pathways and configurational patterns among these factors structured in shaping herders’ ecological restoration intention? To address these questions, this study adopts the Value–Belief–Norm theory as its core analytical framework and extends it by incorporating place attachment and risk perception as complementary emotional and cognitive dimensions. Based on this integrated framework, this study makes three primary contributions. First, it develops an extended VBN-based behavioral model that integrates place attachment and risk perception into the analysis of herders’ ecological restoration intention. Second, it applies a mixed analytical approach combining structural equation modeling and fuzzy-set qualitative comparative analysis to examine both net effects and configurational pathways. Third, by using Ruoergai County as an empirical case, it provides region-specific evidence relevant to grassland ecological governance in ecologically fragile pastoral areas. Theoretical background and research hypotheses Value–Belief–Norm (VBN) theory The VBN theory proposed by Stern et al. conceptualizes pro-environmental behavior as an internally driven psychological process grounded in moral obligation rather than external coercion 31 . The framework specifies a sequential causal pathway in which value orientation shapes environmental belief, belief activates personal moral norm, and personal norm subsequently motivates behavioral intention and action. Within this framework, values provide the evaluative basis for environmental judgment, beliefs reflect perceived consequences and responsibility attribution, and personal norms represent an internalized sense of moral obligation that directly energizes behavior. Compared with regulation-centered or purely instrumental approaches, the VBN theory emphasizes internalized motivation and moral commitment and has been widely applied to explain pro-environmental intention across diverse populations 32 – 34 . However, its systematic application in pastoral grassland contexts remains limited. Accordingly, this study adopts the core VBN pathway—Values → Belief → Norm → Behavioral intention—as the theoretical backbone and extends it by incorporating risk perception and place attachment to better capture cognitive and emotional mechanisms relevant to herders’ ecological decision-making. The following sections specify each VBN component and develop hypotheses for the structural relationships examined in this study. Value cognition (VC) Within the VBN framework, values represent relatively stable psychological orientations that shape how individuals evaluate environmental issues and their responsibility toward ecological protection 35 . As the starting point of the VBN causal chain, value cognition provides the motivational basis for the formation of environmental belief and subsequent moral norm, thereby indirectly influencing behavioral intention 36 . In this study, value cognition reflects individuals’ overall value-based appraisal of grassland ecological restoration, encompassing evaluations of its legitimacy, importance, and desirability. Stronger value cognition is expected to promote positive beliefs regarding the consequences of ecological restoration and enhance perceived responsibility for addressing grassland degradation. Accordingly, value cognition is hypothesized to facilitate the formation of ecological restoration belief. H1 Herders’ value cognition has a positive effect on their ecological restoration belief. Ecological restoration belief (EB) Ecological restoration belief functions as a key mediating construct within the VBN framework, linking value cognition to personal norm 37 . It reflects individuals’ awareness of the consequences of environmental degradation and their perceived responsibility for addressing such problems, thereby providing the cognitive foundation for moral obligation. Consistent with VBN theory, ecological restoration belief is grounded in awareness of consequences and ascription of responsibility 38 . Together, these components facilitate the internalization of moral obligation and serve as the immediate psychological precursor to personal norm 39 . Accordingly, stronger ecological restoration belief is expected to promote the formation of personal norm. H2 Herders’ ecological restoration belief has a positive effect on their personal norm. Personal norm (PN) Within the VBN framework, personal norm refers to an individual’s internalized moral standard regarding appropriate behavioral responses to environmental issues and represents the most proximal psychological determinant of pro-environmental behavior 40 . Unlike external norms derived from institutional regulation, personal norm originates from internal moral judgment and a sense of responsibility. Once activated, personal norm motivates individuals to act in accordance with perceived moral obligations even in the absence of external monitoring or incentives 41 , 42 . In the context of grassland ecological restoration, personal norm reflects an internalized moral commitment to engage in restoration-related behavior. Accordingly, personal norm is expected to directly enhance behavioral intention toward ecological restoration. H3 Personal norm has a positive effect on herders’ behavioral intention toward ecological restoration. Behavioral intention of ecological restoration (BIER) Behavioral intention refers to an individual’s subjective readiness and willingness to perform a specific behavior and is widely regarded as an immediate psychological antecedent of actual behavior 43 . Within the VBN framework, behavioral intention represents the outcome of internalized values, ecological restoration belief, and personal norm, serving as the key link between moral cognition and action. In this study, behavioral intention toward ecological restoration captures herders’ overall willingness to participate in grassland restoration practices when confronted with grassland degradation. Consistent with environmental behavior research, such intention is primarily driven by internal moral commitment rather than short-term instrumental incentives 44 , 45 . Accordingly, behavioral intention is treated as the key outcome variable of the VBN-based framework, while additional cognitive and emotional influences are examined through risk perception and place attachment in subsequent sections. Risk perception (RP) In ecological behavior research, risk perception refers to individuals’ subjective evaluation of uncertainty and potential loss arising from environmental change. It reflects how individuals cognitively assess environmental threats and anticipate their possible consequences, thereby shaping motivation and behavioral responses. Within the context of grassland ecological governance, risk perception captures herders’ overall assessment of ecological and livelihood-related risks associated with grassland degradation. Higher levels of perceived risk are generally associated with stronger environmental concern and greater motivation to engage in pro-environmental behavior 46 , 47 . From a VBN perspective, heightened risk perception amplifies individuals’ awareness of adverse environmental consequences and strengthens perceived responsibility for addressing ecological problems, thereby reinforcing ecological restoration belief. In addition, risk perception may directly promote behavioral intention by motivating preventive and adaptive responses to anticipated environmental and livelihood risks. Accordingly, the following hypotheses are proposed: H4 Risk perception has a positive effect on herders’ ecological restoration belief. H5 Risk perception has a positive effect on herders’ behavioral intention toward ecological restoration. Place attachment (PA) Place attachment refers to a relatively stable psychological bond individuals develop with a specific place, encompassing emotional connection and perceived functional dependence within the human–place relationship 48 . As a core construct in environmental psychology, place attachment has been widely applied to explain environmentally responsible behavior, particularly in contexts where individuals’ lives and activities are closely tied to specific environments. From a behavioral perspective, place attachment influences how individuals interpret environmental change and evaluate their responsibility toward environmental protection. Stronger attachment to a place is associated with heightened concern for its condition and greater motivation to support actions that maintain or restore its ecological integrity. Within the extended VBN framework adopted in this study, place attachment is expected to function as an emotional driver that reinforces ecological restoration belief by strengthening perceived legitimacy and moral relevance of restoration actions. In addition, place attachment may directly promote behavioral intention by motivating individuals to engage in behaviors that protect valued places. Accordingly, the following hypotheses are proposed: H6 Place attachment has a positive effect on herders’ ecological restoration belief. H7 Place attachment has a positive effect on herders’ behavioral intention toward ecological restoration. In summary, this study constructs a model of the factors influencing herders’ behavioral intention toward grassland ecological restoration, as shown in Fig. 1 . Fig. 1. Open in a new tab Research model. Research methods Questionnaire design and variable measurement Based on the proposed theoretical model, this study developed a structured questionnaire to measure herders’ behavioral intention toward grassland ecological restoration. The instrument operationalized six core constructs derived from the VBN framework and its theoretical extensions: value cognition, ecological restoration belief, personal norm, risk perception, place attachment, and behavioral intention of ecological restoration. Basic demographic variables were included for sample description and heterogeneity analysis. Measurement items for each construct were adapted from validated scales in prior ecological behavior research and were linguistically and contextually adjusted to fit the pastoral setting of Ruoergai County. To ensure content validity, the questionnaire was reviewed by three experts in ecological behavior and pastoral studies, followed by a small-scale pilot test with local herders to improve clarity and item comprehension. All constructs were measured using a five-point Likert scale ranging from 1 (“strongly disagree”) to 5 (“strongly agree”). This measurement design enabled the quantitative assessment of latent variables and their structural relationships. The constructs, dimensions, and corresponding measurement items are presented in Table 1 . Table 1. Dimensions and measurement items. Second-order dimension First-order dimension Scale Items Sources Value cognition (VC) Egoistic value (EV) Participating in grassland restoration helps improve my family’s livestock feeding conditions.(EV1) 35 , 36 Improved grassland ecology will make my household income more stable.(EV2) I care about grassland ecology because it will affect my future quality of life.(EV3) Grassland degradation directly affects my family’s economic income, so I must participate in its protection.(EV4) Altruistic value (AV) Grassland restoration benefits not only me but also supports the common development of neighbors and the community.(AV1) Protecting the grassland is my responsibility to future generations.(AV2) Improved grassland will enhance the production and living conditions of the whole village.(AV3) I participate in ecological restoration to allow more people to enjoy a good natural environment.(AV4) Biospheric value (BV) I believe that the grassland itself is an entity that should be respected and protected.(BV1) Animals and plants have the same right to survive as humans, and we should protect the grassland ecosystem.(BV2) Even if grassland restoration brings no direct benefit to me, I am still willing to participate.(BV3) Respecting nature and protecting the ecology is part of my belief and way of life.(BV4) Risk perception (RP) Environmental risk perception (ERP) I worry that grassland degradation will lead to less grazing space.(ERP1) 46 , 47 I believe that current ecological changes may bring serious natural disasters.(ERP2) Reduced grassland vegetation makes me anxious about my future living environment.(ERP3) If no measures are taken, ecological degradation will greatly affect our lives.(ERP4) Economic risk perception (EcRP) Grassland degradation makes me concerned about unstable livestock yields and incomes.(EcRP1) Continued overgrazing may negatively affect my family’s economy.(EcRP2) Declining grassland quality will increase my breeding costs and risks.(EcRP3) I worry that future shortages of grassland resources will affect my children’s livelihoods.(EcRP4) Disease risk perception (DRP) Grassland degradation makes me worry that livestock will get sick more easily.(DRP1) Declining forage quality will affect livestock health and increase disease rates.(DRP2) Worsening grassland ecology will raise the risk of epidemic transmission.(DRP3) I believe that protecting grassland is an important way to prevent animal diseases.(DRP4) Place attachment (PA) Place identity (PI) Grassland is an important part of my personal and family life, and I have a deep emotional attachment to it.(PI1) 48 I regard the grassland not only as a grazing site but also as a symbol of our ethnic culture.(PI2) Protecting grassland is my responsibility and obligation as a community member.(PI3) The grassland is closely tied to my religion and way of life, and I am willing to make efforts for it.(PI4) Place dependence (PD) Grassland provides my family with long-term and stable grazing resources.(PD1) Losing the grassland would seriously affect my quality of life and livelihood stability.(PD2) My current dependence on grassland is high and cannot be replaced by other resources.(PD3) The sustainable health of the grassland is crucial for my family’s future development.(PD4) Ecological restoration belief (ERB) Awareness of consequences (AC) Without ecological restoration, it will become increasingly difficult to graze in the future.(AC1) 37 – 39 Grassland degradation will lead to serious consequences such as reduced water sources and declining livestock health.(AC2) I worry that worsening grassland ecology will harm the living environment of future generations.(AC3) I clearly realize that grassland degradation may trigger a chain reaction throughout the entire ecosystem.(AC4) Ascription of responsibility (AR) I feel a certain responsibility for grassland degradation.(AR1) As a user of the grassland, I am obliged to participate in its ecological restoration.(AR2) I believe my actions can have a positive impact on grassland restoration.(AR3) Regardless of others’ participation, I am willing to contribute to grassland restoration.(AR4) Personal norm (PN) I believe that protecting grassland ecology is my personal responsibility.(PN1) 41 , 42 Even without supervision, I will voluntarily participate in ecological restoration activities.(PN2) I cannot ignore grassland degradation, even if it causes me short-term inconvenience.(PN3) I firmly believe that destroying grassland resources is immoral.(PN4) Participating in ecological restoration makes me feel like a responsible herder.(PN5) In my view, protecting grassland ecology is a moral duty to both ancestors and future generations.(PN6) Behavioral intention of ecological restoration (BIER) I am willing to participate in ecological restoration activities such as rotational grazing and enclosure.(BIER1) 43 – 45 If given the opportunity, I will actively apply to join grassland ecological protection projects.(BIER2) I plan to consider grassland ecological sustainability more in my future production.(BIER3) I am willing to encourage family members or neighbors to participate in grassland ecological restoration.(BIER4) For me, actively participating in ecological restoration is my own choice, not something forced by the government.(BIER5) Open in a new tab Value cognition was operationalized based on prior studies on environmental value orientations and encompasses egoistic, altruistic, and biospheric value elements. Risk perception was measured through three subdimensions—environmental risk perception, economic risk perception, and disease risk perception—reflecting herders’ subjective assessments of ecological degradation and associated uncertainties. Place attachment was conceptualized through place identity and place dependence, capturing emotional belonging and functional reliance on grasslands. Ecological restoration belief was measured via awareness of consequences and ascription of responsibility, while personal norm assessed internalized moral obligation toward restoration behavior. Behavioral intention of ecological restoration captured herders’ psychological readiness and planned tendency to engage in restoration activities. Overall, the questionnaire demonstrates strong theoretical grounding, cultural appropriateness, and methodological rigor. Combined with expert review and pilot testing, it provides a reliable empirical basis for subsequent SEM and fsQCA analyses. A total of 51 measurement items were included in the final instrument. Data collection The formal questionnaire survey was conducted between March and July 2025 in multiple representative pastoral areas of Ruoergai County. A mixed data collection strategy combining online and offline surveys was adopted to improve accessibility across different literacy levels, settlement patterns, and living contexts in pastoral communities. The online survey was administered via the Wenjuanxing platform, and questionnaire links were distributed through WeChat and local pastoral community groups. To reduce literacy-related barriers, audio explanations were provided in both Mandarin and Tibetan, allowing respondents to complete the questionnaire independently. A total of 287 online questionnaires were collected. Responses were screened to exclude questionnaires with substantial missing values, logical inconsistencies, excessively short completion times, or patterned answering behavior. After screening, 251 online questionnaires were retained as valid. The offline survey was jointly organized by the research team in collaboration with local ecological organizations, cooperatives, and temple networks, and was implemented in seven typical pastoral towns, including Tiebu, Baxi, and Xiaman. For respondents with limited formal education, Tibetan annotations and on-site oral explanations were provided by trained research assistants and volunteers with pastoral backgrounds. Offline questionnaires were distributed in commonly frequented locations such as cooperative markets, religious activity areas, and township-level pastoral management stations. Through offline collection, 416 questionnaires were obtained. Applying the same data screening criteria as the online survey, 369 questionnaires were retained as valid. To minimize potential social desirability bias and perceived response pressure, participation was strictly voluntary. Respondents were informed that the survey was anonymous and conducted solely for academic research purposes. The same questionnaire content and screening standards were applied consistently across both online and offline surveys. In total, 703 questionnaires were collected across both survey modes. After data screening, 620 valid questionnaires were retained, yielding an effective response rate of 88.2%. Based on a 95% confidence level and a ± 5% margin of error, the minimum required sample size was 385. The final sample exceeded this threshold, ensuring sufficient statistical power and configurational diversity for subsequent SEM and fsQCA analyses. Analysis results Demographic characteristics of the sample The demographic characteristics of the sample are summarized in Table 2 . The respondents were predominantly middle-aged and older herders, with 86.5% aged 31 years or above. The gender distribution was relatively balanced, with males accounting for 52.9% and females 47.1%. Table 2. Demographic characteristics of the sample ( n = 620). Category Frequency Percentage (%) Cumulative Percentage (%) Gender Male 328 52.9 52.9 Female 292 47.1 100.0 Age Under 30 years 84 13.5 13.5 31–40 years 182 29.4 42.9 41–50 years 202 32.6 75.5 51 years and above 152 24.5 100.0 Education Level Junior secondary or below 284 45.8 45.8 Senior high school/Vocational secondary 188 30.3 76.1 College or above 148 23.9 100.0 Household Size 3 persons or fewer 137 22.1 22.1 4–6 persons 317 51.2 73.3 7 persons or more 166 26.7 100.0 Annual Income Less than 50,000 CNY 271 43.7 43.7 50,000-100,000 CNY 201 32.4 76.1 Above 100,000 CNY 148 23.9 100.0 Grassland Dependency High dependency 335 54.0 54.0 Moderate dependency 203 32.7 86.7 Low dependency 82 13.3 100.0 Open in a new tab Regarding educational attainment, most respondents had junior secondary education or below (45.8%), followed by senior high school or vocational secondary education (30.3%), and college education or above (23.9%). Household size was generally moderate to large, with 51.2% of households comprising four to six members and 26.7% having seven or more members. In terms of annual household income, 43.7% of respondents reported incomes below 50,000 CNY, 32.4% between 50,000 and 100,000 CNY, and 23.9% above 100,000 CNY. With respect to grassland dependency, a majority of respondents reported high (54.0%) or moderate (32.7%) dependence on grassland resources. Overall, the sample covers a broad range of demographic and socio-economic characteristics representative of pastoral households in Ruoergai County. Reliability analysis of variables In this study, Cronbach’s alpha (α) coefficient was employed to assess the internal consistency reliability of the scales. A higher α value indicates greater consistency among the items within the questionnaire, thereby reflecting stronger reliability of the scale. According to the reliability coefficient criteria proposed by DeVellis(1991), an α coefficient below 0.6 denotes low reliability, suggesting the need to redesign the questionnaire or remove contentious items; an α above 0.9 indicates exceptionally stable results; and values between 0.7 and 0.8 represent relatively stable reliability 49 . In the present study, the Cronbach’s alpha coefficients for all latent variables exceeded 0.8, indicating high internal consistency and demonstrating that the scales exhibit good reliability (Table 3 ). Table 3. Reliability analysis of variables. Cronbach’s reliability analysis Variable Dimension Number of Items Cronbach’s α Coefficient Value cognition Egoistic value 4 0.846 Altruistic value 4 0.842 Biospheric value 4 0.839 Risk perception Environmental risk perception 4 0.833 Economic risk perception 4 0.847 Disease risk perception 4 0.838 Place attachment Place identity 4 0.83 Place dependence 4 0.852 Ecological restoration belief Awareness of consequences 4 0.835 Ascription of responsibility 4 0.824 Personal norm 6 0.881 Behavioral intention of ecological restoration 5 0.868 Open in a new tab Measurement model validation and convergent validity Confirmatory factor analysis (CFA) was conducted using AMOS 23.0 to assess the measurement model and convergent validity of all latent constructs. Convergent validity was evaluated based on standardized factor loadings, composite reliability (CR), and average variance extracted (AVE). Following established criteria, factor loadings above 0.70, CR values above 0.70, and AVE values above 0.50 indicate satisfactory convergent validity. The Kaiser–Meyer–Olkin (KMO) measure and Bartlett’s test of sphericity confirmed the suitability of the data for factor analysis (KMO = 0.937; Bartlett’s test: Approx. Chi-Square = 15,863.628, df = 1275, p < 0.001; see Table 4 ). Table 4. KMO and bartlett’s test. KMO and Bartlett’s Test KMO Measure of Sampling Adequacy 0.937 Bartlett’s test of sphericity Approx. Chi-Square 15863.628 df 1275 p-value 0.000 Open in a new tab The CFA results show that all standardized factor loadings exceeded the recommended threshold of 0.70. In addition, all constructs exhibited CR values greater than 0.70 and AVE values above 0.50, demonstrating satisfactory convergent validity and internal consistency (Table 5 ). Table 5. Analysis of convergent validity. Factor Loadings, AVE, and CR Values Latent variable Observed variable Factor loading AVE CR Egoistic value EV1 0.752 0.589 0.851 EV2 0.781 EV3 0.787 EV4 0.748 Altruistic value AV1 0.756 0.58 0.846 AV2 0.764 AV3 0.76 AV4 0.766 Biospheric value BV1 0.721 0.581 0.847 BV2 0.795 BV3 0.773 BV4 0.757 Environmental risk perception ERP1 0.74 0.563 0.837 ERP2 0.752 ERP3 0.769 ERP4 0.74 Economic risk perception EcRP1 0.76 0.588 0.851 EcRP2 0.787 EcRP3 0.787 EcRP4 0.733 Disease risk perception DRP1 0.742 0.574 0.843 DRP2 0.789 DRP3 0.72 DRP4 0.777 Place identity PI1 0.75 0.556 0.834 PI2 0.764 PI3 0.729 PI4 0.739 Place dependence PD1 0.74 0.599 0.856 PD2 0.754 PD3 0.778 PD4 0.821 Awareness of consequences AC1 0.754 0.565 0.839 AC2 0.779 AC3 0.751 AC4 0.723 Ascription of responsibility AR1 0.75 0.547 0.828 AR2 0.705 AR3 0.743 AR4 0.76 Personal norm PN1 0.757 0.558 0.883 PN2 0.756 PN3 0.749 PN4 0.751 PN5 0.735 PN6 0.735 Behavioral intention of ecological restoration BIER1 0.776 0.576 0.872 BIER2 0.744 BIER3 0.755 BIER4 0.76 BIER5 0.76 Open in a new tab Several core constructs in this study (value cognition, risk perception, place attachment, and ecological restoration belief) were specified as higher-order constructs composed of multiple first-order dimensions. CFA was conducted at the first-order level, and the validated dimensions were subsequently aggregated to represent higher-order constructs in the structural model. Overall, the results indicate that the measurement model meets accepted standards of reliability and convergent validity, providing a sound basis for subsequent structural equation modeling and configurational analyses. Discriminant validity As shown in Table 6 , discriminant validity is established when the correlation coefficients between constructs are lower than the square roots of their corresponding AVE values. In this study, the correlation coefficients among the main variables are all below the respective square roots of AVE, indicating that the latent constructs exhibit good discriminant validity. Table 6. Discriminant validity analysis. Discriminant validity: Pearson correlations and square root of AVE EV AV BV ERP EcRP DRP PI PD AC AR PN BIER EV 0.767 AV 0.503 0.761 BV 0.469 0.483 0.762 ERP 0.271 0.306 0.277 0.750 EcRP 0.275 0.302 0.279 0.478 0.767 DRP 0.292 0.348 0.326 0.507 0.492 0.758 PI 0.388 0.343 0.322 0.291 0.250 0.294 0.746 PD 0.336 0.354 0.346 0.273 0.264 0.326 0.394 0.774 AC 0.432 0.361 0.394 0.257 0.334 0.340 0.326 0.318 0.752 AR 0.374 0.367 0.375 0.324 0.283 0.343 0.363 0.275 0.441 0.740 PN 0.288 0.338 0.339 0.341 0.344 0.352 0.331 0.353 0.268 0.305 0.747 BIER 0.328 0.327 0.298 0.376 0.316 0.372 0.346 0.288 0.369 0.382 0.415 0.759 Open in a new tab Note: The diagonal blue numbers represent the square root of AVE. Moreover, Pearson correlation analysis was conducted in this study to examine the relationships among variables. As shown in Table 7 , all variables were significantly correlated with each other ( p < 0.05), and the absolute values of the correlation coefficients were all greater than 0.3. These results indicate that the variables exhibit moderate correlations, supporting the feasibility of subsequent analyses. Table 7. Pearson correlation analysis. Pearson correlation Value perception Risk perception Place attachment Ecological restoration belief Personal norm Behavioral intention of ecological restoration Value perception 1 Risk perception 0.451** 1 Place attachment 0.514** 0.417** 1 Ecological restoration belief 0.558** 0.454** 0.451** 1 Personal norm 0.397** 0.425** 0.410** 0.337** 1 Behavioral intention of ecological restoration 0.392** 0.436** 0.379** 0.443** 0.415** 1 Open in a new tab * p < 0.05 ** p < 0.01. Structural equation modeling (SEM) analysis Model construction In this study, structural equation modeling was performed using AMOS 23. The model includes six latent variables: value cognition, ecological restoration belief, personal norm, risk perception, place attachment, and behavioral intention of ecological restoration, comprising a total of 51 observed indicators, which were aggregated into parcels based on their validated first-order dimensions. Given the large number of parameters to be estimated, directly constructing the model using all original items could introduce substantial estimation bias. To address this, the internal consistency parceling method proposed by Bian et al. (2007) 50 was employed, aggregating scale items into parcels according to their respective subdimensions. Specifically, value cognition was represented by three parcels: egoistic value, altruistic value, and biospheric value; risk perception was represented by three parcels: environmental risk perception, economic risk perception, and disease risk perception; place attachment was represented by two parcels: place identity and place dependence; ecological restoration belief was represented by two parcels: consequence awareness and ascription of responsibility. The latent variables of personal norm and behavioral intention of ecological restoration were measured using their original observed indicators. Model fit analysis The model fit indices based on the data collected in this study using the maximum likelihood estimation method are presented in Table 8 . The chi-square to degrees of freedom ratio (χ²/df) was 1.27, which is below the threshold of 3, indicating an acceptable fit. The Standardized Root Mean Square Residual(SRMR) was 0.031, below the recommended value of 0.05. Both the Goodness-of-Fit Index(GFI) and Adjusted Goodness-of-Fit Index (AGFI) were 0.966 and 0.956, respectively, exceeding the standard criterion of 0.9. The Root Mean Square Error of Approximation (RMSEA) was 0.021, well below the 0.08 threshold. Additionally, the Normed Fit Index (NFI), Incremental Fit Index (IFI), Tucker–Lewis Index (TLI), and Comparative Fit Index (CFI) were 0.958, 0.991, 0.989, and 0.991, respectively, all surpassing the 0.9 criterion. The Parsimony Normed Fit Index (PNFI) and Parsimony Comparative Fit Index (PCFI) were 0.817 and 0.845, both exceeding the 0.5 threshold. Overall, all fit indices met the recommended standards, indicating a good fit between the collected data and the constructed research model (Table 8 ). Table 8. Model fit index analysis. Model fit Fit index type Fit index Criterion Observed value Fit result Absolute Fit index CMIN/DF < 3 1.27 Excellent SRMR < 0.05 0.031 Excellent GFI > 0.9 0.966 Excellent AGFI > 0.9 0.956 Excellent RMSEA < 0.08 0.021 Excellent Relative Fit index NFI > 0.9 0.958 Excellent IFI > 0.9 0.991 Excellent TLI > 0.9 0.989 Excellent CFI > 0.9 0.991 Excellent Parsimonious Fit index PNFI > 0.5 0.817 Excellent PCFI > 0.5 0.845 Excellent Open in a new tab Path effect analysis Based on the results illustrated in Table 9 , value cognition exerts a significant positive effect on ecological restoration belief (β = 0.344, p < 0.05), thus supporting H1. Ecological restoration belief has a significant positive effect on personal norm (β = 0.586, p < 0.05), thereby supporting H2. Personal norm significantly and positively influences behavioral intention of ecological restoration (β = 0.175, p < 0.05), supporting H3. Risk perception shows a significant positive impact on ecological restoration belief (β = 0.276, p < 0.05), supporting H4. Moreover, risk perception has a significant positive effect on behavioral intention of ecological restoration (β = 0.249, p < 0.05), supporting H5. Place attachment significantly and positively affects ecological restoration belief (β = 0.466, p < 0.05), supporting H6. Finally, place attachment demonstrates a significant positive influence on behavioral intention of ecological restoration (β = 0.327, p < 0.05), thereby supporting H7. Table 9. Path effect analysis. Path Analysis Hypothesis Path B β SE t P H1 Value Cognition → Ecological Restoration Belief 0.294 0.344 0.11 2.678 0.007 H2 Ecological Restoration Belief → Personal Norm 1.073 0.586 0.102 10.499 *** H3 Personal Norm → Behavioral Intention of Ecological Restoration 0.179 0.175 0.052 3.423 *** H4 Risk Perception → Ecological Restoration Belief 0.221 0.276 0.062 3.587 *** H5 Risk Perception → Behavioral Intention of Ecological Restoration 0.372 0.249 0.107 3.486 *** H6 Place Attachment → Ecological Restoration Belief 0.456 0.466 0.156 2.929 0.003 H7 Place Attachment → Behavioral Intention of Ecological Restoration 0.597 0.327 0.149 4.004 *** Open in a new tab Fuzzy-set qualitative comparative analysis (fsQCA) Data calibration Data calibration is a critical step in calculating the membership scores of antecedent variable sets. In this study, the mainstream three-anchor-point method was employed, using 95%, 50%, and 5% as thresholds corresponding to full membership, the crossover point, and full non-membership, respectively. The calibration anchors for each variable are presented in Table 10 . Table 10. Variable calibration anchors. Value cognition Risk perception Place attachment Ecological restoration belief Personal norm Behavioral Intention of Ecological Restoration Full membership 4.500 4.500 4.500 4.500 4.500 4.600 Crossover point 2.750 2.750 2.750 2.875 2.667 2.800 Full non-membership 1.667 1.667 1.625 1.750 1.500 1.400 Open in a new tab Analysis of necessary conditions of single antecedents The analysis of necessary conditions of single antecedents helps to determine whether a particular antecedent is indispensable for producing an outcome. In this study, the Necessary Analysis function in fsQCA 4.1 was employed to examine the necessity of single antecedents. According to established criteria, an antecedent condition with a consistency score greater than 0.9 can be considered a necessary condition for the outcome 51 , where “~” denotes logical negation. As shown in Table 11 , the consistency scores for both high-level and low-level behavioral intention of ecological restoration ranged from 0.500 to 0.833, all below the 0.9 threshold. This indicates that no single antecedent condition qualifies as a necessary condition for either high-level or low-level behavioral intention of ecological restoration. Consequently, it is essential to further explore the configurational effects of multiple interacting conditions. A configuration refers to a specific combination of antecedent conditions that jointly lead to a particular outcome or phenomenon. Table 11. Analysis of necessary conditions of single antecedents. High-level behavioral intention of ecological restoration Low-level behavioral intention of ecological restoration Consistency Coverage Consistency Coverage Value cognition 0.705 0.747 0.575 0.594 ~Value cognition 0.617 0.598 0.755 0.714 Risk perception 0.721 0.756 0.565 0.578 ~Risk perception 0.598 0.585 0.762 0.727 Place attachment 0.717 0.738 0.581 0.584 ~Place attachment 0.596 0.593 0.739 0.718 Ecological restoration belief 0.700 0.766 0.533 0.570 ~Ecological restoration belief 0.607 0.571 0.781 0.717 Personal norm 0.699 0.743 0.544 0.564 ~Personal norm 0.590 0.570 0.752 0.709 Open in a new tab Configuration analysis Configuration analysis is used to identify the multi-factor synergistic pathways that lead to a given outcome. Based on the previous necessity tests, a truth table was constructed and subsequently minimized to obtain three solutions: complex solution, intermediate solution, and parsimonious solution. The parameters for truth table minimization were set as follows: frequency threshold = 14, consistency threshold = 0.8, and PRI threshold = 0.7 52 , 53 . Due to the lack of definitive evidence regarding the directional impact of antecedent conditions on the outcome, antecedent conditions in the parsimonious solution were coded as “present or absent,” indicating that the presence or absence of a single antecedent condition could contribute to the outcome. Following the common paradigm in previous studies, this study primarily relied on the intermediate solution and used the parsimonious solution to differentiate core conditions from peripheral conditions, resulting in the configuration shown in Table 12 . Table 12. Configurational paths for behavioral intention of ecological restoration. Open in a new tab In each causal pathway, “●” indicates a high-level core condition, “·” indicates a high-level peripheral condition, “ ” indicates a low-level core condition, “ ” indicates a low-level peripheral condition, and “—” indicates that the condition can be either present or absent. The overall solution consistency exceeds the 0.8 threshold, and the overall solution coverage exceeds the 0.3 threshold, demonstrating good model fit. Two distinct causal pathways were ultimately identified. Analysis of configurational pathways leading to high-level behavioral intention of ecological restoration Based on the fsQCA results, configurational pathways leading to high-level behavioral intention of ecological restoration were identified. The overall solution coverage was 0.400, and the overall solution consistency was 0.938, indicating that the model is robust, valid, and effectively represents the complex causal combinations underlying high-level behavioral intention. Configuration 1 reveals that simultaneously high levels of value cognition, risk perception, place attachment, ecological restoration belief, and personal norm function as core conditions, collectively facilitating herders’ strong behavioral intention of ecological restoration. Specifically, value cognition provides a meaningful cognitive foundation, enabling herders to perceive grassland restoration as a long-term responsibility intimately connected to their livelihood and cultural identity. Risk perception enhances awareness of potential ecological threats, including reduced livestock health and unstable income. Place attachment reinforces the emotional motivation to protect and restore grasslands. Ecological restoration belief legitimizes and strengthens herders’ confidence in taking restorative action, while personal norm internalizes this belief as a moral obligation to engage in ecological governance. When all five core conditions are present at high levels, herders possess integrated cognitive, emotional, and normative drivers, making them more likely to consistently invest resources and effort in practical restoration activities. The raw coverage of this pathway is 0.400, demonstrating its representativeness and stability among samples exhibiting high-level behavioral intention. For policymakers, these findings imply that strategies aiming to enhance herders’ awareness through policy campaigns, ecological education, and community cultural activities should be complemented by interventions that simultaneously strengthen value cognition, risk perception, place attachment, restoration belief, and moral norms, thereby creating a comprehensive and synergistic mechanism for promoting ecological restoration behavior. Analysis of configurational pathways leading to low-level behavioral intention of ecological restoration The fsQCA results for low-level behavioral intention of ecological restoration reveal an overall solution coverage of 0.470 and an overall solution consistency of 0.901, indicating that the model has substantial explanatory power and effectively represents the complex causal pathways underlying low-level behavioral intention. Configuration 2 indicates that when value cognition, risk perception, place attachment, ecological restoration belief, and personal norm are all at low levels and act as core conditions simultaneously, herders’ behavioral intention of ecological restoration is significantly inhibited. Specifically, low value cognition makes it difficult for herders to link grassland restoration with personal benefits and long-term livelihood development. Low risk perception diminishes sensitivity to potential ecological threats and associated economic or livelihood risks. Low place attachment reflects weak emotional ties to the grasslands, reducing intrinsic motivation to engage in restoration activities. Furthermore, the absence of ecological restoration belief prevents herders from forming positive expectations regarding restoration outcomes, while low personal norm signals that participation is not perceived as a moral or social obligation. When these five core conditions are simultaneously absent, herders lack integrated drivers across cognitive, emotional, belief, and normative dimensions, resulting in a pronounced decrease in behavioral intention. The raw coverage of this pathway is 0.470, indicating that it represents a substantial portion of the low-level behavioral intention samples. From an intervention perspective, these findings suggest that targeting a single factor is unlikely to produce meaningful improvements; effective enhancement of behavioral intention requires simultaneous reinforcement across multiple core conditions to reverse the low-intention state. Robustness test To further examine the robustness and stability of the fsQCA results, a robustness test was conducted by adjusting key analytical parameters and comparing the resulting configurational solutions with those reported in the main analysis. Following common practice in fsQCA research 52 , 53 , the consistency threshold was increased from 0.80 to 0.90, while the frequency threshold (14) and the proportional reduction in inconsistency (PRI) threshold (0.70) were kept unchanged. This procedure aims to assess whether the identified configurational pathways are sensitive to stricter consistency requirements. The robustness test results are presented as shown in Table 13 . Table 13. Robustness test results. Open in a new tab The robustness test results indicate that the configurational solutions remained fully stable under the more stringent consistency threshold. Specifically, the number of sufficient configurations, the core and peripheral condition structure, and the directional patterns of antecedent conditions for both high-level and low-level behavioral intention of ecological restoration showed no changes compared with the original results. No new configurations emerged, and none of the previously identified configurations were eliminated. Moreover, the overall solution consistency and solution coverage values exhibited no substantive variation, remaining at levels comparable to those reported in the main configurational analysis. The high-level behavioral intention configuration continued to demonstrate strong explanatory power, with high solution consistency and adequate coverage, while the low-level behavioral intention configuration likewise maintained stable consistency and coverage values. Taken together, these findings indicate that the fsQCA results are robust and not contingent upon a specific consistency threshold setting. The identified configurational pathways linking value cognition, risk perception, place attachment, ecological restoration belief, and personal norm to herders’ ecological restoration intention demonstrate strong stability, thereby reinforcing the reliability and credibility of the configurational conclusions. Discussion Grounded in the VBN theory and extended by incorporating risk perception and place attachment, this study systematically examined the formation mechanisms of grassland ecological restoration behavioral intention among herders in Ruoergai County through a combined SEM and fsQCA approach. Overall, the findings not only confirm the core causal logic proposed by VBN theory, namely the sequential influence of values, beliefs, and personal norms on pro-environmental behavioral intention, but also demonstrate that the relative strength, activation mode, and interaction patterns of these mechanisms are highly sensitive to socio-ecological context. Importantly, the results reveal that the VBN framework does not operate as a rigid linear chain in pastoral systems. Instead, its internal pathways are reconfigured by livelihood dependence, environmental exposure, and place based identity, suggesting that extensions of VBN should move beyond attitudinal variables alone and explicitly account for experiential and spatial dimensions. Difference 1: integrated operation of value cognition Consistent with the VBN theory proposed by Stern, value cognition was found to exert a significant positive influence on ecological restoration belief. However, unlike studies conducted in non-livelihood-dependent environmental contexts—such as solid waste management or generalized environmental behavior—where different value orientations may exhibit differentiated or competing effects on pro-environmental intention (e.g 39 . , , this study demonstrates that egoistic, altruistic, and biospheric values simultaneously and positively contribute to ecological restoration belief among herders. In Ruoergai, grasslands constitute the material basis of household income, the social foundation of community stability, and the ecological system sustaining pastoral production. As a result, egoistic value related to economic security, altruistic value related to collective well-being, and biospheric value related to ecosystem integrity are not perceived as competing motivations but as interdependent concerns embedded within everyday pastoral practice. This pattern is also consistent with findings among ethnically Tibetan pastoralists, where cultural norms, collective responsibility, and livelihood dependence jointly shape grassland conservation decisions 42 . From a theoretical perspective, this finding suggests that the value dimension of VBN theory functions as an integrated cognitive system rather than a set of competing orientations in livelihood-dependent socio-ecological systems. This refines the application of VBN theory by highlighting the contextual integration of value orientations under strong human–environment interdependence. Difference 2: place attachment as a structurally anchoring factor The results indicate that place attachment plays a prominent and direct role in shaping both ecological restoration belief and behavioral intention. The SEM results show that place attachment exerts a significant positive effect on ecological restoration belief, while the fsQCA findings further reveal that high behavioral intention most consistently emerges when place attachment coexists with value cognition, risk perception, ecological belief, and personal norm. These findings suggest that place attachment functions not merely as an auxiliary emotional factor, but as a structurally anchoring component within the extended VBN framework. As conceptualized in this study, place attachment represents a stable psychological bond integrating emotional connection and perceived functional dependence on grasslands. This bond enhances the perceived legitimacy and moral relevance of ecological restoration, thereby reinforcing belief formation and directly motivating behavioral intention. Notably, this pattern implies that the role of place attachment may vary across socio-ecological contexts. In pastoral systems characterized by strong livelihood dependence on specific environments, place attachment appears to operate as a more immediate motivational force, directly linking emotional bonds with ecological responsibility and action, rather than relying primarily on attitudinal mediation. From a theoretical perspective, these results extend the VBN framework by positioning place attachment as a stabilizing antecedent that anchors belief formation and behavioral intention in place-based contexts. Rather than functioning solely through indirect pathways, place attachment strengthens the internal coherence of the value–belief–norm process, thereby enhancing the persistence and reliability of ecological restoration intention. Difference 3: experiential risk perception and direct behavioral activation This study also identifies risk perception as a direct driver of both ecological restoration belief and behavioral intention, diverging from studies such as Yoon et al. (2021) 47 , which found that risk perception of ocean microplastics primarily influenced tourists’ pro-environmental behavioral intention through indirect cognitive pathways. The discrepancy can be attributed to differences in risk exposure intensity and experiential proximity. In tourism contexts, environmental risks are often abstract, temporally distant, and weakly connected to personal livelihood outcomes. In contrast, for herders in Ruoergai, grassland degradation is a continuously experienced reality manifested through declining forage availability, livestock health risks, and increasing climate variability. Under such conditions, risk perception becomes embedded in daily production practices and livelihood decision-making. Persistent and direct exposure transforms risk perception from a purely cognitive assessment into an experiential motivational force, enabling it to directly activate ecological restoration belief and behavioral intention. This finding extends the contextual application of VBN theory by clarifying that, under conditions of strong environmental dependence and sustained exposure, risk perception can bypass intermediate attitudinal stages and function as a direct behavioral driver. Theoretical synthesis and contribution Taken together, this study demonstrates that its contribution to VBN theory lies not merely in adding new variables, but in reconceptualizing how the VBN framework operates under conditions of strong human–environment interdependence. The findings indicate that the internal logic of VBN is not a fixed linear sequence, but a context-sensitive mechanism whose structure and activation pathways are reshaped by livelihood dependence, spatial embeddedness, and sustained environmental exposure in pastoral socio-ecological systems. Specifically, this study shows that value cognition functions as an integrated cognitive system rather than a set of competing orientations, that place attachment operates as a structurally anchoring antecedent that stabilizes ecological beliefs and personal norms, and that risk perception can act as a direct motivational driver rather than merely an indirect cognitive trigger. Through these mechanisms, the traditional VBN pathway is conditionally restructured, advancing the framework toward a more context-responsive model capable of capturing place-based and experience-driven behavioral dynamics. Methodologically, the combined use of SEM and fsQCA enables both net-effect testing and configurational interpretation, preserving consistency with prior linear studies while capturing the complexity and equifinality of real-world behavioral mechanisms. Together, these findings provide a theoretically grounded and empirically nuanced understanding of grassland ecological restoration behavioral intention among herders, and establish a robust analytical foundation for future cross-regional and cross-cultural applications of extended VBN-based models. Conclusion Research findings This study, grounded in the VBN theory, incorporates two extended variables—risk perception and place attachment—to construct a comprehensive model of the factors influencing the behavioral intention of ecological restoration among herders. Using Ruoergai County as the study area, empirical data were collected through a structured questionnaire, and dual-method verification was conducted using SEM and fsQCA. Overall, all hypotheses (H1–H7) were supported, providing empirical support for the contextual applicability of the VBN framework in grassland pastoral systems and revealing the direct effects of risk perception and place attachment on herders’ behavioral intention toward ecological restoration. The results indicate that: (1) Value cognition has a significant positive effect on ecological restoration belief; ecological restoration belief significantly influences personal norm; and personal norm, in turn, significantly affects behavioral intention toward ecological restoration. This confirms that the core chain pathway proposed by VBN theory remains operative in grassland ecosystems. Compared with studies focusing on urban residents and university students, the strength of value cognition and the synergistic interaction among egoistic, altruistic, and biospheric value orientations are more pronounced in pastoral contexts, reflecting the value structure of herders who are highly dependent on natural grassland resources. (2) Risk perception has a significant positive effect on ecological restoration belief and also exerts a direct positive influence on behavioral intention. This suggests that for herder populations who are chronically and directly exposed to ecological risks, risk perception can be rapidly translated into behavioral intention without extensive additional information processing, highlighting its critical role in shaping restoration-related decision-making. (3) Place attachment significantly affects ecological restoration belief and also directly promotes behavioral intention. This indicates that strong emotional bonds and cultural identity associated with grasslands can directly motivate ecological restoration behavior, underscoring the importance of place-based attachment in influencing pro-environmental action in pastoral regions. (4) fsQCA results further demonstrate that high behavioral intention toward ecological restoration emerges from the simultaneous presence of high value cognition, strong risk perception, strong place attachment, high ecological restoration belief, and strong personal norm. This finding indicates that enhancing herders’ willingness to participate in ecological restoration requires coordinated, multi-factor interventions rather than reliance on any single mechanism. In summary, this study demonstrates the contextual relevance of VBN theory in grassland ecosystems and highlights the direct motivational roles of place attachment and risk perception in shaping ecological restoration intention. The findings provide theoretically grounded and empirically supported insights into the behavioral mechanisms underlying herders’ participation in ecological restoration. Practical implications The findings of this study offer concrete practical implications for the design and implementation of grassland ecological restoration policies in pastoral regions, particularly within the context of China’s ongoing transition from policy-driven ecological regulation to collaborative and incentive-based environmental governance. The results indicate that herders’ behavioral intention toward ecological restoration is shaped by a coordinated set of cognitive, emotional, and experiential mechanisms rather than by any single factor. Accordingly, effective grassland governance should adopt integrated intervention strategies aligned with these mechanisms. First, the integrated operation of value cognition suggests that ecological restoration policies in China should be communicated through frames that explicitly connect environmental protection with livelihood security and long-term household resilience. In many pastoral regions, including the Qinghai–Tibet Plateau, ecological restoration is often perceived as imposing short-term constraints on grazing activities. This study shows that such perceptions can be mitigated when restoration is framed as supporting sustainable livestock production, income stability, and intergenerational livelihood continuity. In practice, this implies that policy communication under programs such as the Grassland Ecological Protection Subsidy and Incentive Policy should emphasize the long-term economic and social co-benefits of restoration, rather than focusing solely on ecological targets. Second, the structurally anchoring role of place attachment highlights the importance of incorporating place-based and culturally grounded approaches into grassland governance. In China’s pastoral areas, grasslands are not merely productive resources but are deeply embedded in ethnic identity, religious practices, and historical modes of land use. Policy implementation that recognizes these dimensions—for example, through participatory restoration planning, community-led monitoring, and the integration of local ecological knowledge—can strengthen herders’ ecological restoration belief and reinforce personal norms related to environmental responsibility. Such approaches are particularly relevant in ethnic minority regions, where externally imposed governance measures may otherwise be perceived as disconnected from local values. Third, the direct motivational effect of risk perception underscores the need for localized and experiential risk communication strategies. For Chinese herders who are directly exposed to grassland degradation, climate variability, and livestock health risks, abstract ecological indicators or generalized environmental messaging are insufficient. Instead, governance interventions should provide concrete, locally observable feedback, such as pasture condition assessments, livestock productivity indicators, and climate-related early-warning information. Integrating scientific monitoring results with herders’ everyday experiences can enhance the salience of ecological risks and facilitate the direct translation of risk perception into restoration-oriented behavioral intention. Finally, the fsQCA results demonstrate that high behavioral intention toward ecological restoration emerges from the simultaneous presence of multiple favorable conditions, including high value cognition, strong place attachment, elevated risk perception, ecological restoration belief, and personal norm. This finding has important implications for policy design in China, where grassland governance has traditionally relied on single-instrument interventions such as grazing bans or compensation schemes. The results suggest that isolated measures are unlikely to produce sustained behavioral change. Instead, coordinated policy packages that combine economic incentives, value-oriented communication, place-based engagement, and normative reinforcement are more likely to promote long-term participation and reduce governance costs. Taken together, these practical implications suggest that enhancing herders’ participation in grassland ecological restoration in China requires moving beyond uniform policy enforcement toward context-sensitive, multi-dimensional governance strategies. By aligning ecological objectives with livelihood realities, cultural attachment, and experiential risk awareness, policymakers can foster more durable and internally motivated restoration behavior among herders. Research limitations This study has several limitations. First, the research scope is confined to Ruoergai County, and the specific socio-cultural context, ecological characteristics, and policy environment may limit the generalizability of the findings to other pastoral regions. Second, the use of cross-sectional survey data restricts the ability to capture dynamic changes in herders’ behavioral intention over time. Third, although the combined SEM–fsQCA approach provides complementary insights, the findings remain constrained by the subjectivity of self-reported data and potential measurement bias. In addition, the measurement of risk perception and place attachment is primarily perception-based and lacks validation against objective ecological indicators. Future research directions Future research may extend this study in several directions: Conducting cross-regional and cross-cultural comparative studies to examine the generalizability of extended VBN-based models across different grassland systems; Incorporating longitudinal data to capture dynamic changes in behavioral intention and policy responses over time; Integrating objective ecological indicators and remote sensing data with subjective perceptions to enhance explanatory robustness; and. Exploring threshold effects and interaction mechanisms of place attachment and risk perception under varying levels of resource dependence to inform targeted grassland governance strategies. Author contributions Conceptualization: Chuhao Shen and Kun Wang; methodology: Chuhao Shen and Linyu Huang; formal analysis: Chuhao Shen and Zhonghui Chen; investigation: Chuhao Shen, Haibo Yuan and Limin Zheng; data curation: Chuhao Shen and Linyu Huang; writing—original draft preparation: Chuhao Shen and Zhonghui Chen; writing—review and editing: Chuhao Shen, Linyu Huang and Kun Wang; visualization: Chuhao Shen; supervision: Linyu Huang; project administration: Chuhao Shen; funding acquisition: Chuhao Shen. All authors have read and agreed to the published version of the manuscript. Funding This research was funded by the Scientific Research Funds for High-Level Talent Introduction at Kashi University. Data availability The data used in this study are original. If access is required, please contact the corresponding author. Declarations Competing interests The authors declare no competing interests. Institutional review board statement This study was conducted in accordance with the Declaration of Helsinki and all relevant institutional and national guidelines and regulations. Ethical review and approval were waived by the Ethics Committee of Kashi University, in accordance with the University’s policy that non-interventional research using anonymized data without sensitive personal information or physical/psychological risk may be exempt from ethics review. The study posed minimal risk, did not involve minors or other vulnerable groups, and only involved voluntary participation by adults aged 18 or older. Participation was entirely anonymous, with no collection of personally identifiable information. All participants were fully informed about the purpose and content of the survey before starting and provided their informed consent by agreeing to participate after reading the online consent notice. Participants retained the right to withdraw at any time without consequence. The research involved non-interventional online questionnaires, ensuring participants’ privacy and data confidentiality. Informed consent Informed consent was obtained from all subjects involved in the study. Footnotes Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. China Government Network. Ecological Environment. Available online: (2005). https://www.gov.cn/test/2005-07/28/content_17792.htm (Accessed 9 Aug 2025). 2. Ministry of Agriculture and Rural Affairs of the People’s Republic of China. Reply to Proposal No. 3893 of the Second Session of the 14th National People’s Congress. 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