Multiple Pathways of Digital Technology Driving the Enhancement of Agricultural Economic Resilience

Enhancing agricultural economic resilience is critical for ensuring national food security, advancing agricultural modernization, and responding to increasingly complex external shocks. Against the backdrop of rapid digital economy development, digital technologies are progressively becoming a key driver of agricultural economic resilience by reshaping production patterns, optimizing resource allocation, and strengthening risk-response capacity. However, existing studies are predominantly grounded in linear analytical frameworks, which are insufficient to capture the complex mechanisms of multi-dimensional factor interactions, and they pay limited attention to spatiotemporal heterogeneity. In this context, a configurational perspective is adopted to systematically examine how agricultural economic resilience is enhanced through the synergistic interaction of multiple factors by digital technologies. The aim is to provide a more comprehensive theoretical basis for formulating differentiated digital agriculture development policies.

Based on the technology-organization-environment (TOE) framework, an analytical model was constructed for digital technology-driven agricultural economic resilience. Using provincial panel data from China spanning 2011 to 2023, a dynamic qualitative comparative analysis (QCA) approach was employed to identify multiple configurational pathways linking combinations of conditions to agricultural economic resilience. Specifically, necessity analysis was first conducted to examine whether any single antecedent condition was a necessary condition for the outcome. Second, configurational analysis was used to identify multiple equifinal pathways through which different combinations of conditions generate high agricultural economic resilience. Third, between-group and within-group analyses were further conducted to examine the temporal evolution and spatial heterogeneity of these configurational pathways. In addition, robustness tests were performed by adjusting the original consistency threshold, frequency threshold, and the threshold of proportional reduction in inconsistency to validate the stability of the identified configurations.

(1) A single digital technology factor was not a necessary condition for achieving high agricultural economic resilience. Instead, resilience improvement depended on the coordinated configuration of multiple dimensions, exhibiting a typical "multiple concurrent causality" characteristic. (2) Five effective configurational pathways were identified for enhancing agricultural economic resilience through digital technologies. These pathways were further summarized into three typologies: policy-market dual-driven type, production-chain enabling type, and synergistic driving type, reflecting the equifinality of different condition combinations. (3) The configurational pathways exhibited pronounced spatiotemporal heterogeneity. Temporally, the effects of certain pathways evolved dynamically with the deepening penetration of digital technologies. Spatially, due to differences in resource endowments, Eastern, Central, and Western regions, as well as different grain functional zones, corresponded to distinct dominant pathways. In terms of regional heterogeneity, production-chain enabling and synergistic driving pathways were mainly concentrated in Western and Eastern regions. In terms of grain functional zoning, the policy-market dual-driven pathway was primarily observed in major grain-producing and balanced production-marketing areas, while production-chain enabling and synergistic driving pathways were more prevalent in major marketing and balanced production-marketing regions.

The results demonstrate that there is no single optimal pathway for enhancing agricultural economic resilience; rather, it fundamentally depends on the effective synergistic configuration of multiple factors under specific contexts. As a core driving force, digital technology must be aligned with institutional environments, organizational capabilities, and resource endowments to fully realize its enabling effects. Meanwhile, regional heterogeneity further shapes the diversity of digital technology's impact pathways, implying that different regions should adopt development models tailored to their own conditions and continuously optimize them dynamically. From a configurational perspective, the results reveal the multi-path mechanisms through which digital technologies enhance agricultural economic resilience, enrich the existing theoretical literature, and provide important policy implications for implementing differentiated strategies, optimizing digital agriculture development pathways, and strengthening agricultural system resilience.