How big data analytics capabilities drive supply chain resilience: the mediating roles of supply chain visibility and flexibility

Purpose: With the increasing adoption of big data analytics (BDA), academics and practitioners are examining how and under what conditions BDA capabilities enhance supply chain resilience (SCR). Drawing on dynamic capability theory (DCT) and inertia theory, this study investigates the differentiated impacts of BDA capabilities on proactive and reactive SCR. It further explores the mediating roles of supply chain visibility and flexibility as well as the moderating role of firm size. Design/methodology/approach: Survey data were collected from 277 Chinese manufacturing enterprises. Data were used to test the conceptual model, using the structural equation modeling-partial least square approach. Findings: The results demonstrate that BDA capabilities positively influence reactive SCR, but their effect on proactive SCR is insignificant. Furthermore, visibility and flexibility mediate the relationship between BDA and SCR, exhibiting distinct mediating effects on proactive and reactive SCR. Additionally, the influence of BDA on visibility is more pronounced in large firms than in small firms, whereas its effect on flexibility is less significant in large firms compared to small firms. Originality/value: First, this study extends understanding of BDA’s distinct roles in the pre- and post-disruption contexts. Second, drawing on DCT, it uncovers the mediating effects of visibility and flexibility on the relationship between BDA and SCR, elucidating the differentiated mechanisms through which BDA delivers value to SCR. Finally, it highlights the moderating role of firm size in explaining the effects of BDA on visibility and flexibility, providing a richer and more detailed picture of how BDA impacts supply chain management.