Sustainable supply chain management under big data: a bibliometric analysis

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.

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Stored only when both papers are in the corpus — 110 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.