AI-Enabled Supply Chain Management: A Bibliometric Analysis Using VOSviewer and RStudio Bibliometrix Software Tools
Mihaela Gabriela Belu and
Ana Maria Marinoiu ()
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Mihaela Gabriela Belu: Faculty of International Business and Economics, Bucharest University of Economic Studies, 010404 Bucharest, Romania
Ana Maria Marinoiu: Faculty of International Business and Economics, Bucharest University of Economic Studies, 010404 Bucharest, Romania
Sustainability, 2025, vol. 17, issue 5, 1-28
Abstract:
Artificial intelligence (AI) is fundamentally transforming the management of supply chain activities, offering companies the opportunity to configure resilient, transparent, and sustainable supply chains. Given its importance, this paper presents aspects of the implementation of artificial intelligence in supply chain management by performing a bibliometric analysis of 400 scientific papers published between 2010 and 2024 and indexed in the Scopus database. The analysis was based on the Bibliometrix 4.4.2 and VOSviewer 1.6.19 software to identify the most important authors and journals of interest for the researched topic. Keyword co-occurrence and co-citation analyses were used to map intellectual networks and highlight themes of interest. The research results confirm the increase in scientific interest in the field of applying AI in supply chain management, highlighting the advantages of implementing this technology in supply chain management. At the same time, the recommendations and conclusions of this paper will be useful to both academic researchers and business professionals to identify potential areas of collaboration with the aim of developing supply chain strategies that contribute to the competitiveness of companies that are part of the network.
Keywords: artificial intelligence; supply chain; supply chain management; bibliometric analysis; VOSviewer; Bibliometrix (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:5:p:2092-:d:1602158
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