Information from the abstract
Digital transformation has emerged as a critical driver of agricultural supply chain resilience, yet the mechanisms through which technology investment translates into resilience outcomes remain inadequately understood. Addressing this gap, this study examines the mediating role of sustainable consumption and production in this relationship. Drawing on dynamic capabilities theory and the SDG12 framework, an integrated model is developed and tested using survey data from 423 agricultural enterprises across six provinces in China. Covariance-based structural equation modeling with bootstrap mediation analysis reveals that digital transformation significantly enhances agricultural supply chain resilience, with sustainable consumption and production (SCP) serving as a partial mediator that transmits 46.1% of the total effect. The indirect effects on the three resilience capability dimensions exhibit a differentiated pattern: absorptive capability shows the strongest effect, followed by responsive capability and recovery capability. Multi-group analysis demonstrates that these effects are more pronounced in eastern regions with better digital infrastructure and in large enterprises with more abundant resources. These findings reveal that the synergy between digital capabilities and sustainable practices, rather than technology alone, constitutes the true engine of resilience building. This study provides empirical evidence for agricultural enterprises and policymakers seeking to formulate digital-sustainable synergy strategies.
Why this record is monitored
This record has an Impact Signal of 83/100 based on recency, source, collaboration, and bibliographic signals. It prioritizes monitoring and is not a judgment of research quality.
Related topics: Supply Chain Resilience and Risk Management · Sustainable Supply Chain Management · COVID-19 Pandemic Impacts
Thai researcher and institutional participation
Sarana Photchanachan · Shinawatra University
Data limitations
This page is a bibliographic record based on abstract-level information, not a full analysis or quality assessment. Verify the DOI and original article before citation.