Bridging Big Data Analytics Capability and Competitive Advantage in China’s Agribusiness: The Mediator of Absorptive Capacity

This research examines the relationship between big data analytics capability (BDAC) and competitive advantage (CA) in China’s agribusiness sector, with a specific focus on the mediating role of absorptive capacity (AC). Although BDAC has been extensively studied in other industries, its role within agribusiness remains underexplored, particularly in developing economies like China. This study addresses this gap by investigating how BDAC can be utilized to enhance competitive advantage in the unique context of agribusiness. Grounded in Resource-Based Theory (RBT), a comprehensive framework is developed to elucidate the interconnections among BDAC, CA, and AC. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) on data collected from 287 agribusiness firms in China, the findings reveal that key resources—such as data quality, infrastructure, information systems, data governance, data-driven culture, managerial expertise, and technical proficiency—significantly influence BDAC. Moreover, BDAC is shown to positively impact CA, with AC serving as a critical mediator in this relationship. These results emphasize the strategic importance of integrating BDAC and AC to enhance the competitiveness of agribusinesses, particularly amidst rapid digital transformation. This study provides valuable contributions to the literature on BDAC, enriches the theoretical foundations of RBT in agribusiness contexts, and offers practical recommendations for digital transformation strategies in the sector.