Investigating the critical influencing factors of rural public services resilience in China: A grey relational analysis approach

Investigating and enhancing rural public services resilience is essential to address the significant issue of rural decline, yet existing research lacks quantitative studies in this area. This study innovatively establishes a quantitative evaluation model of rural public services resilience according to the P-S-R (Pressure-State-Response) model to calculate the spatiotemporal distribution and identifies the critical influencing factors through the grey relational analysis method. Statistics data from China has been employed to make the empirical research. The results indicate that (1) the areas with high-quality rural public services perform better in resilience than the areas with high-quantity rural public services and excellent early-warning capability greatly facilitates response resilience thus improving the whole resilience level; (2) the critical factors of pressure resilience encompass indicators in healthcare and public education, while public services quality emerges as the pivotal aspect of state resilience, and financial input is assumed to be the most critical factor in response resilience. This research contributes significantly by presenting a quantitative resilience assessment framework considering the dynamic recovery attributes of rural public services and identifying critical influencing factors to propose targeted strategies for enhancing rural public services resilience.