Unlocking Sustainability in Manufacturing SMEs: Synergizing BDA–AI, Green Supply Chain Practices, Green Innovation, and Organizational Green Culture
TL;DR
The findings show that BDA–AI significantly improves GSCM, GI, and sustainable performance, and mediation results confirm that GSCM and GI act as essential mechanisms through which BDA–AI generates environmental and operational benefits.
Abstract
Growing pressures for environmental responsibility have intensified the need for manufacturing SMEs to pursue sustainability as a core strategic priority, especially as these firms often operate under severe resource constraints. In this context, firms increasingly adopt advanced digital technologies such as big data analytics–artificial intelligence to strengthen their environmental, social, and economic performance. Guided by the Resource‐Based View (RBV), this study contributes to the ongoing discussion on how digital technologies support sustainable development by proposing the mediating roles of green supply chain management and green innovation in the relationship between BDA–AI capability and sustainable performance. The study further examines whether organizational green culture enhances the ability of BDA–AI to foster green capabilities. Using survey data from 388 Chinese manufacturing SMEs and structural equation modeling through SmartPLS, the findings show that BDA–AI significantly improves GSCM, GI, and sustainable performance. Mediation results confirm that GSCM and GI act as essential mechanisms through which BDA–AI generates environmental and operational benefits. However, the moderating influence of OGC is uneven: it significantly strengthens the pathway from BDA–AI to GI, whereas its effect on the BDA–AI to GSCM relationship remains insignificant. These insights highlight that digital adoption alone is insufficient; sustainability gains emerge when technological investment is accompanied by strong green capabilities and supportive cultural values.