A landscape of Big data analytics in Supply chain planning: completing the puzzle and vision to the future

Despite the boom of research interest at the intersection of big data and supply chain domain, little research effort has been directed to investigate big data analytics (BDA) for the planning processes of supply chains. This paper aims to draw the landscape of current knowledge regarding the use of BDA in supply chain planning (SCP) and to provide a vision for future research. Based on a systematic literature review of 51 peer-reviewed papers published between 2013 and February 2019, we organized the literature according to the SCP process with the "supply chain planning matrix”, and studied the managerial issues related to BDA adoption in SCP. Results highlight that extant literature is dominant by the use of BDA in demand planning and production planning and scheduling, while other planning activities are relatively under-investigated. Most of the studies are restricted to the investigation of BDA in a single planning phase, where the supply chain perspective is weak. Finally, we suggest that empirical studies are in need to bridge academic and practitioner studies on the theme.