Measurement and Influencing Factors of Rural Livelihood Resilience of Different Types of Farmers: Taking “Agri-Tourism–Commerce–Culture Integration” Areas in China

In the rapid development of rural tourism, multiple disturbances, such as capital reorganization, uneven resource distribution, and the marginalization of farmers as the main body, have emerged. This has led to the dual challenges of increased vulnerability and insufficient resilience of farmers’ livelihood systems in the face of risk shocks. Based on survey data of the “Agri-Tourism–Commerce–Culture Integration” demonstration zone in China, this study integrates the Pressure–State–Response model into the analysis of livelihood resilience and constructs a “vulnerability–adaptability–recuperability” tri-dimensional framework. Through methods such as the entropy weight method, the synthetical index method, grey relational degree analysis, and the obstacle degree model, this study measures the levels of different livelihood types of farmers in each dimension of livelihood resilience and their influencing factors. The research findings indicate that the overall livelihood resilience of farmers in the study area was at a medium level, with vulnerability making the most significant contribution, reflecting that the current livelihood system is dominated by risk resistance. Different types of farmers exhibit heterogeneity in resilience, with tourism-oriented farmers showing the highest resilience and agriculture-oriented farmers the lowest. However, tourism-oriented farmers also display the most prominent vulnerability, revealing the tension between short-term efficiency enhancement and long-term risk diversification in single livelihood strategies. Key factor analysis reveals that vulnerability correlates most strongly with livelihood resilience. The most correlated indicators are the price increase rate, proportion of migrant workers, and neighborhood trust in the vulnerability, adaptability, and recuperability dimensions. Diagnosis of obstacle factors reveal that loan accessibility, land resource dependency, and agricultural risk perception rank as the top three common obstacles, with tourism-driven farmers exhibiting higher obstacle degrees than other farmer categories. These findings not only validate the empowering effect of rural tourism on farmers’ livelihoods but also reveal the different livelihood strategies chosen by various farmers. Based on the results, this study proposes policy recommendations of “common optimization + individual adaptation” to enhance farmers’ livelihood resilience. This is conducive to transforming external support into farmers’ endogenous resilience capabilities and provides a useful reference for achieving the deep integration of rural tourism and farmers’ livelihood systems.