Livelihood resilience is the ability of individuals, families or communities to withstand external shocks based on existing resources. It is an important research paradigm in sustainable development studies. The outbreak of COVID-19 and strict epidemic prevention policies have greatly impacted the production and life of rural farmers in China. The resilience of farmers’ livelihoods during the epidemic is crucial to the sustainable development of their livelihoods and regional stability. This study uses classic buffer capacity, self-organization ability, and the capacity for learning a three-dimension livelihood resilience framework using the comprehensive index, OLS, and geographical detector methods based on Hubei province and neighboring Anhui and Chongqing. Rural household survey data investigate the background of epidemic hit the livelihood of farmers resilience and its spatial distribution pattern and identify the key influencing factors. The results show that the livelihood shock faced by farmers was higher than the risk of disease, and the overall level of livelihood resilience was low after the pandemic. Financial capital and social capital can effectively help farmers to eliminate livelihood difficulties. In contrast, natural capital has a limited driving force, and physical and human capital have no obvious impact. The spatial agglomeration differentiation is obvious, indicating that the impact of COVID-19 on livelihoods was closely related to the degree of local socio-economic development and geographical location. The results of this study provide targeted recommendations for the development of epidemic prevention and livelihood resilience policies tailored to local conditions, emphasizing the importance of boosting livelihood recovery at both the government and household levels.

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This study explores how promoting e-commerce participation impacts the adoption of green agrotechnology by resettlers in China’s Three Gorges Reservoir area and helps rural revitalization and the realization of value from ecological produce. First, we combine induced innovation model theory with the risk perception factor of expected utility theory. A model of resettlers’ green agrotechnology adoption under different levels of e-commerce participation is constructed, and research hypotheses are proposed accordingly. Survey data gathered from resettled farmers in Zigui, the first county of the studied area, are tested empirically with an ordered probit model. The results show first, that e-commerce participation significantly and positively affects the level of green agrotechnology adoption at the 1% level; and second, that expectations of the ecological value of agricultural products and the agrotechnology support provided by e-commerce are important driving factors. The promotion effect of different modes of e-commerce participation on agrotechnology adoption differ. The risk-averse behavior of resettlers can weaken the promotion effect of e-commerce participation on agrotechnology adoption.

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