Data-driven supply chain management capabilities enhance supply chain performance by providing insights, analyses, and predictions. However, the mechanisms through which data-driven supply chain management capabilities enhance the sustainability of agro-processing firms' supply chains remain insufficiently explored. This study, grounded in organizational information processing theory, investigates the relationship between data-driven supply chain management capabilities and sustainable supply chain performance. Survey data from 249 Chinese agro-process firms were analyzed using structural equation modeling, confirming that data-driven supply chain management capabilities significantly boost supply chain performance and transparency. Supply chain transparency mediates the relationship between data-driven supply chain management capabilities and sustainable supply chain performance, while circular economy thinking further amplifies this effect. This study extends organizational information processing theory by demonstrating how data-driven supply chain management capabilities can enhance sustainability in agro-processing firms through improved transparency and the integration of circular economy thinking. For practitioners, the findings highlight how strategically leveraging data-driven supply chain management capabilities and transparency, supported by circular economy thinking, can drive sustainable performance, offering a clear pathway for enhancing sustainability in agricultural supply chains. • Examines how DDSCMC improve environmental sustainability in agro-processing firms. • Identifies supply chain transparency as a mediator between DDSCMC and performance. • Shows CET strengthens sustainability gains through resource reuse and waste reduction. • Offers a practical framework for greener, more competitive agricultural supply chains.
Qiao et al. (Wed,) studied this question.