The impact of data elements on agricultural economic resilience: a dynamic QCA analysis

Enhancing agricultural economic resilience is a critical component for ensuring sustainable agricultural development and promoting agricultural modernization. To explore the diverse influencing factors and effective pathways for enhancing agricultural economic resilience in the context of digital transformation in China, this study constructs a theoretical model of data elements empowering agricultural economic resilience based on the “Technology-Organization-Environment” framework. Using dynamic QCA methods, panel data from 30 provinces and municipalities in China from 2012 to 2022 are analyzed to configure the factors influencing agricultural economic resilience. The results indicate that no single variable constitutes a necessary condition for high agricultural economic resilience. With the introduction of time effects, it is found that digital inclusive finance and the necessity of agricultural industry digitalization have been increasing year by year. The patterns of enhancing agricultural economic resilience can be summarized as follows: the market-driven industrial technological innovation ecosystem optimization model, the TOE-enabled agricultural digital development model and the government-led cultural promotion of agricultural digital transformation model, all showing significant temporal and regional effects. Based on these findings, it is recommended that regions strengthen the synergistic interaction among elements in the technology, organization, and environment dimensions and formulate differentiated strategies for enhancing agricultural economic resilience tailored to local economic levels and the actual development of agricultural industries. These insights provide both theoretical and practical value for enhancing agricultural economic resilience in various regions worldwide.