Digital information's challenges and potential at the nexus of Big Data Analytics and supply chain management

Abstract

Despite the breadth of supply chain management (SCM) research, little attention has been paid to the application of Big Data Analytics to maximize the utilization of information in a supply chain. The objective of this article is to contribute to the development of SCM theory by examining the potential effects of Big Data Analytics on information utilization in a business and supply chain setting. Because it is critical for supply chain firms to have access to current, accurate, and useful data, the exploratory research will shed light on the opportunities and problems associated with the implementation of Big Data Analytics in SCM. While management is increasingly focusing on Big Data Analytics, actual research on the subject is still sparse. Due of the scarcity of relevant content at the nexus of Big Data Analytics and Supply Chain Management, the authors employ the Delphi research technique. The given Delphi survey findings complement to existing knowledge by identifying 43 opportunities and problems associated with the emergence of Big Data Analytics from a corporate and supply chain perspective. These structures provide the research community with a starting point for tailoring future research at the nexus of Big Data Analytics and SCM. The research contributes to the current body of knowledge by examining possibilities and challenges at the corporate and supply chain level with a particular emphasis on the consequences imposed by Big Data Analytics.