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      Sustainable supply chain management under big data: a bibliometric analysis

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      Journal of Enterprise Information Management
      Emerald

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          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.

          Related collections

          Most cited references56

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          Bibliometric Methods in Management and Organization

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            Co-citation in the scientific literature: A new measure of the relationship between two documents

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              Do green supply chains lead to competitiveness and economic performance?

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                Author and article information

                Journal
                Journal of Enterprise Information Management
                JEIM
                Emerald
                1741-0398
                August 25 2020
                January 28 2021
                August 25 2020
                January 28 2021
                : 34
                : 1
                : 427-445
                Article
                10.1108/JEIM-12-2019-0381
                85ed4b83-ab92-4438-80fb-14f1927b4375
                © 2021

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