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Intellectual Structure in Supply Chain Risk Management from 2000 to 2022: A Review Based on Text Mining Approach

Author

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  • Xiaoyang Liu

    (School of Marxism, Nanjing University of Science & Technology, Nanjing 210094, China)

  • Yuanyuan Zhou

    (Library Department, Nanjing Medical University, Nanjing 210029, China)

  • Song Gao

    (China Information Technology Security Evaluation Center, Beijing 100085, China)

Abstract

This study illustrates the intellectual structure of research in the domain of supply chain risk management (SCRM) from the year 2000 to the year 2022. This paper employs a bibliometric analysis to investigate the foundations of the discipline and a quantitative approach to uncover the evolution of research in SCRM. Firstly, CiteSpace is used to evaluate and show the intellectual structure of this sector. With its help, we establish cooperation networks of institutions and countries, networks of different terms and keywords, and cooperation relations among writers. The process involves the extraction of certain useful information, such as core terms, leading authors, and major institutions. Secondly, with the help of the latent Dirichlet allocation technology, we look at the progression of the subject matter about the management of risks associated with supply chains. The outcome of this review provides a foundation for understanding developing patterns and new changes in the industry, and it is significant for future research on supply chain risk management. Our study not only updates the review of SCRM but also illustrates the possibility to objectively review literature with the support of text mining technology, using our newly developed framework. This framework can also be easily applied to other research fields.

Suggested Citation

  • Xiaoyang Liu & Yuanyuan Zhou & Song Gao, 2022. "Intellectual Structure in Supply Chain Risk Management from 2000 to 2022: A Review Based on Text Mining Approach," Sustainability, MDPI, vol. 14(23), pages 1-24, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:16245-:d:994345
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    References listed on IDEAS

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