Big Data in operations and supply chain management: a systematic literature review and future research agenda

Abstract

In the era of digitalisation, the role of Big Data is proliferating, receiving considerable attention in all sectors and domains. The domain of operations and supply chain management (OSCM) is no different since it offers multiple opportunities to generate a large magnitude of data in real-time. Such extensive opportunities for data generation have attracted academics and practitioners alike who are eager to tap different elements of Big Data application in OSCM. Despite the richness of prior studies, there is limited research that extensively reviews the extant findings to present an overview of the different facets of this area. The current study addresses this gap by conducting a systematic literature review (SLR) to uncover the existing research trends, distil key themes, and identify areas for future research. For this purpose, 116 studies were identified through a stringent search protocol and critically analysed. The key outcome of this SLR is the development of a conceptual framework titled the Dimensions-Avenues-Benefits (DAB) model for BDA adoption as well as potential research questions to support novel investigations in the area, offering actionable implications for managers working in different verticals and sectors.