Big data-enabled supply chains and sustainable food system performance: evidence from China’s Agri-food enterprises

Introduction Digital technologies are reshaping agri-food supply chains, yet empirical evidence on how big data adoption relates to sustainability outcomes remains limited, particularly regarding the mechanisms through which such associations operate. Methods This study analyzes panel data from 156 Chinese A-share listed agri-food companies spanning 2016 to 2024, yielding 1,024 firm-year observations. Big data adoption is measured through text mining of annual reports, and sustainable performance is operationalized across economic, environmental, and social dimensions following the triple bottom line framework. Two-way fixed effects models with instrumental variable estimation are employed, and supply chain integration is tested as a potential mediator. Results Big data adoption exhibits positive associations with all three sustainability dimensions, with the strongest coefficient observed for social performance and the weakest for environmental performance. Supply chain integration partially mediates these associations, with the environmental and economic pathways showing similar indirect proportions (approximately 29–30%) and the social pathway showing a lower proportion (approximately 22%). Heterogeneity analysis indicates that smaller firms show stronger economic associations while larger firms demonstrate more pronounced environmental associations. Discussion These findings suggest that big data technologies may be associated with multiple sustainability outcomes simultaneously, though through differentiated pathways. The agri-food sector’s emphasis on food safety may explain the prominence of social performance associations. Supply chain integration appears to play a more critical role in environmental improvements, which typically require cross-organizational coordination.