This study investigates how different types of “big data analytics” (BDA) usage influence organizational decision-making in the area of supply chain management (SCM). Drawing on decision-making theory and organizational information processing theory, we conceptualize two patterns of BDA usage for supply chain (SC) activities (BDA use for SC optimization and BDA use for SC learning) and report two complementary channels via which the two BDA usage patterns impact a supply chain organization’s BDA-enabled decision-making capability. An analysis of questionnaire data from supply chain managers representing 157 companies based in North American suggests that BDA use for SC optimization is directly associated with better decision-making capability. In contrast, the influence of BDA use for SC learning does not impact decision-making directly but indirectly, as its effect is fully mediated by organizational integration. We discuss the implications of these findings for future academic research and for managers in practice who seek to maximize business values from BDA implementations.
Chen, Daniel Q.; Preston, David S.; and Swink, Morgan
"How Big Data Analytics Affects Supply Chain Decision-Making: An Empirical Analysis,"
Journal of the Association for Information Systems, 22(5), 1224-1244.
Available at: https://aisel.aisnet.org/jais/vol22/iss5/9
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