Big data optimisation and management in supply chain management: a systematic literature review

Abstract

The increasing interest from technology enthusiasts and organisational practitioners in big data applications in the supply chain has encouraged us to review recent research development. This paper proposes a systematic literature review to explore the available peer-reviewed literature on how big data is widely optimised and managed within the supply chain management context. Although big data applications in supply chain management appear to be often studied and reported in the literature, different angles of big data optimisation and management technologies in the supply chain are not clearly identified. This paper adopts the explanatory literature review involving bibliometric analysis as the primary research method to answer two research questions, namely: (1) How to optimise big data in supply chain management? and (2) What tools are most used to manage big data in supply chain management? A total of thirty-seven related papers are reviewed to answer the two research questions using the content analysis method. The paper also reveals some research gaps that lead to prospective future research directions.

Digital-Era Resilience: Navigating Logistics and Supply Chain Operations after COVID-19

“…This is especially important for areas where customer demand changes or disruptions can lead to massive product shortages [7]. Experts suggest investigating improved inventory management techniques, demand forecasting, and predictive analytics to ensure that items are regularly available to customers [39]. As a result, the primary goal of recent research should be to guarantee product availability.…”

A systematic analysis of digital supply chain, big data and manufacturing lean time in industrial companies

“…Accordingly, Alsolbi et al. (2023) argued that big data management and optimization are crucial in supply chain management (SCM).…”