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Sustainable supply chain management under big data: a bibliometric analysis

Xinyi Zhang (Shandong University, Weihai, China)
Yanni Yu (Shandong University, Weihai, China)
Ning Zhang (Shandong University, Weihai, China)

Journal of Enterprise Information Management

ISSN: 1741-0398

Article publication date: 25 August 2020

Issue publication date: 28 January 2021

2198

Abstract

Purpose

This study aims to provide a literature review and bibliometric analysis of sustainable supply chain management using big data. We reviewed the literature on sustainable supply chain management under big data from 2012 to 2019 and extracted 777 articles.

Design/methodology/approach

We conducted quantitative analysis and data network visualization of the chosen literature, including authors, journals, countries, research institutions and citations.

Findings

We discovered that the development of this interdisciplinary field has gained increasing popularity among researchers around the world, such as China and the US publishing the most articles and Western states having more cooperation, which indicates this research topic is growing in significance globally.

Originality/value

Scientific and technological revolutions such as big data have been incorporated in various industries. Modern supply chain management has also been combined with the advances in data science to achieve sustainability goals. No studies have reviewed the sustainable supply chain management based on big data. This study fills this gap.

Keywords

Acknowledgements

This work is supported by National Natural Science Foundation of China (NSFC), (grant number: 71974112, 91746112, and 71822402).

Citation

Zhang, X., Yu, Y. and Zhang, N. (2021), "Sustainable supply chain management under big data: a bibliometric analysis", Journal of Enterprise Information Management, Vol. 34 No. 1, pp. 427-445. https://doi.org/10.1108/JEIM-12-2019-0381

Publisher

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Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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