Digital Twin in Supply Chain Management: A Comprehensive Bibliometric Review

Gulsah Hancerliogullari Koksalmis; Emrah Koksalmis

doi:10.1007/978-3-032-08147-6_2

Digital Twin in Supply Chain Management: A Comprehensive Bibliometric Review

Gulsah Hancerliogullari Koksalmis^*
, Emrah Koksalmis

^*Corresponding author for this work

Department of Industrial Engineering

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

The incorporation of Digital Twin (DT) technology into Supply Chain Management (SCM) represents a paradigm shift, offering enhanced efficiency, resilience, and strategic insights for managing global supply networks. This study provides an extensive bibliometric analysis, highlighting key trends, research themes, influential authors, and leading institutions in this dynamic domain. The analysis utilizes a dataset of scholarly publications from 2014 to 2025, sourced from the Scopus database, a reliable repository for academic research. By employing bibliometric techniques such as co-citation analysis, bibliographic coupling, collaboration mapping, and keyword co-occurrence analysis, the study identifies pivotal contributors, prominent institutions, and impactful nations based on citation metrics. The findings offer a comprehensive overview of DT applications in SCM, equipping researchers, practitioners, and policymakers with actionable insights to leverage this technology for optimizing supply chain performance.

Original language	English
Title of host publication	International Series in Operations Research and Management Science
Publisher	Springer
Pages	7-22
Number of pages	16
DOIs	https://doi.org/10.1007/978-3-032-08147-6_2
Publication status	Published - 2025

Publication series

Name	International Series in Operations Research and Management Science
Volume	375
ISSN (Print)	0884-8289
ISSN (Electronic)	2214-7934

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Keywords

Bibliometric analysis
Digital twin
Scopus
Supply chain management
VOSviewer

Access to Document

10.1007/978-3-032-08147-6_2

Cite this

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abstract = "The incorporation of Digital Twin (DT) technology into Supply Chain Management (SCM) represents a paradigm shift, offering enhanced efficiency, resilience, and strategic insights for managing global supply networks. This study provides an extensive bibliometric analysis, highlighting key trends, research themes, influential authors, and leading institutions in this dynamic domain. The analysis utilizes a dataset of scholarly publications from 2014 to 2025, sourced from the Scopus database, a reliable repository for academic research. By employing bibliometric techniques such as co-citation analysis, bibliographic coupling, collaboration mapping, and keyword co-occurrence analysis, the study identifies pivotal contributors, prominent institutions, and impactful nations based on citation metrics. The findings offer a comprehensive overview of DT applications in SCM, equipping researchers, practitioners, and policymakers with actionable insights to leverage this technology for optimizing supply chain performance.",

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doi = "10.1007/978-3-032-08147-6\_2",

language = "English",

series = "International Series in Operations Research and Management Science",

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Digital Twin in Supply Chain Management: A Comprehensive Bibliometric Review. / Koksalmis, Gulsah Hancerliogullari; Koksalmis, Emrah.
International Series in Operations Research and Management Science. Springer, 2025. p. 7-22 (International Series in Operations Research and Management Science; Vol. 375).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - Digital Twin in Supply Chain Management

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AU - Koksalmis, Emrah

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PY - 2025

Y1 - 2025

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KW - Bibliometric analysis

KW - Digital twin

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KW - Supply chain management

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Digital Twin in Supply Chain Management: A Comprehensive Bibliometric Review

Abstract

Publication series

Bibliographical note

Keywords

Access to Document

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Cite this