Drivers of fishermens’livelihood resilience and transitioning to ecological farming in Yangtze River,China:From PLS-SEM and fs/QCA

Abstract

This study investigates the effects of risk perception, buffering ability, self-organization ability and learning ability on the fishermens’ecological farming willingness in Yangtze River, China. Using the Yangtze River basin fishermen as a case study, this study simultaneously used the partial least squares structural equation model (PLS-SEM) and fuzzy-set qualitative comparative analysis (fs/QCA) to explore the linear and nonlinear dynamic impacts among the variables. PLS-SEM analysis revealed that livelihood resilience positively affect ecological farming willingness of retired fishermen; risk perception and livelihood resilience can positively influence ecological farming willingness through buffering, self-organization and learning abilities. The fs/QCA revealed that simple antecedent variables do not constitute a necessary condition for promoting fishermens’ strong ecological farming willingness, which depends on the conditions combined with another element. The analysis also elucidates the optimized combination of support policies for fishermen in different regions. In the eastern region, a compensation configuration that emphasizes “livelihood capital” through natural and material resources is identified as the most effective approach. This strategy aims to enhance the stock of livelihood capital for fishermen, thereby ensuring stability and sustainability in their livelihoods. Conversely, the central region is most effectively served by “policy-driven” assistance measures. These measures emphasize enhancing policy implementation to promote the transformation and restoration of livelihoods. Simultaneously, in the western region, an optimal comprehensive support model, characterized as “integrated capital -policy-community-skills,” comes to the fore. This approach empowers communities and offers substantial support for the sustainable development of fishermen’s livelihoods.