Path dependency and differentiated driving mechanism: Revisiting the spatio-temporal evolution of rural settlement sustainable development for future policy insights

The intensifying rural decline poses escalating challenges to the Sustainable Development Goals (SDGs), thereby underscoring the imperative for localized assessments and regulation of rural settlement sustainable development (RSSD). The integration of SDGs and rural settlement characteristics provides a crucial perspective for RSSD assessment. Given this, we propose a novel assessment framework for RSSD, involving ecological health, social well-being, and economic development. The coupling coordination degree, spatial Markov chain, and panel quantile regression model are employed to decode the spatio-temporal evolution and driving mechanisms of RSSD in China. The results show that China's RSSD improved continuously from 2006 to 2020, with marked progress in social well-being. However, RSSD faced inherent constraints of path dependency and the trade-offs between ecological health and economic development. Rural settlements with low sustainable development levels primarily relied on endogenous resources, while those with high levels were more driven by exogenous factors, such as fiscal expenditure and industrial structure upgrading. Neo-endogenous development impetus, fostered by positive interactions between endogenous and exogenous factors, can facilitate the transition of rural settlement towards more sustainable ones. Comprehensive strategies that highlight the assets value of natural resources, promote urban-rural integration, and extend rural industrial chains are expected to accelerate this process. This study offers valuable research perspective and decision-making references to support the achievement of SDGs in rural area.