Big data analytics in supply chain management: A state-of-the-art literature review

Truong Nguyen, Li Zhou, Virginia Spiegler, Petros Ieromonachou, Yong Lin

Research output: Contribution to journalArticlepeer-review

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Abstract

The rapidly growing interest from both academics and practitioners in the application of big data analytics (BDA) in supply chain management (SCM) has urged the need for review of up-to-date research development in order to develop a new agenda. This review responds to the call by proposing a novel classification framework that provides a full picture of current literature on where and how BDA has been applied within the SCM context. The classification framework is structurally based on the content analysis method of Mayring (2008), addressing four research questions: (1) in what areas of SCM is BDA being applied? (2) At what level of analytics is BDA used in these SCM areas? (3) What types of BDA models are used in SCM? (4) What BDA techniques are employed to develop these models? The discussion tackling these four questions reveals a number of research gaps, which leads to future research directions.
Original languageEnglish
Pages (from-to)254-264
JournalComputers & Operations Research
Volume98
Issue number10
DOIs
Publication statusPublished - 1 Oct 2018

Keywords

  • big data
  • Literature review
  • big data analytics
  • supply chain management
  • research directions

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