Big Data and supply chain management: a review and bibliometric analysis

Deepa Mishra (), Angappa Gunasekaran (), Thanos Papadopoulos () and Stephen J. Childe ()
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Deepa Mishra: IIT Kanpur
Angappa Gunasekaran: University of Massachusetts Dartmouth
Thanos Papadopoulos: University of Kent
Stephen J. Childe: Plymouth University

Annals of Operations Research, 2018, vol. 270, issue 1, No 17, 313-336

Abstract: Abstract As Big Data has undergone a transition from being an emerging topic to a growing research area, it has become necessary to classify the different types of research and examine the general trends of this research area. This should allow the potential research areas that for future investigation to be identified. This paper reviews the literature on ‘Big Data and supply chain management (SCM)’, dating back to 2006 and provides a thorough insight into the field by using the techniques of bibliometric and network analyses. We evaluate 286 articles published in the past 10 years and identify the top contributing authors, countries and key research topics. Furthermore, we obtain and compare the most influential works based on citations and PageRank. Finally, we identify and propose six research clusters in which scholars could be encouraged to expand Big Data research in SCM. We contribute to the literature on Big Data by discussing the challenges of current research, but more importantly, by identifying and proposing these six research clusters and future research directions. Finally, we offer to managers different schools of thought to enable them to harness the benefits from using Big Data and analytics for SCM in their everyday work.

Keywords: Big Data; Supply chain management; Bibliometric analysis; Network analysis (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (42)

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DOI: 10.1007/s10479-016-2236-y

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