Discrete-event simulation in logistics and supply chain management: a scientometric perspective

This paper has been designed in the form of a systematic literature review intended for evaluating the state-of-the-art of discrete-event simulation (DES) usage in the logistics and supply chain management fields under a scientometric perspective. With this primary aim in mind, 127 papers published between 2009 and 2022 are analysed, with the specific purposes of: 1) providing an overview of DES studies in logistics and supply chain management, map the main topics covered within this stream of literature and their evolution in time; 2) providing a robust ranking of the journals and authors in the field; 3) evaluating the rigor in the implementation of DES models in the logistics and supply chain management literature; and finally 4) correlating, through statistical elaborations, all the previous aspects to the success of these papers, measured as the citations received per year, taking inspiration from scientometric disciplines.

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Publication Details

Journal
Production & Manufacturing Research
Published
2024-10-16
DOI
https://doi.org/10.1080/21693277.2024.2415038
Citations
3
Primary Topic
Business Process Modeling and Analysis
Type
article
Field-Weighted Citation Impact
1.59
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article

Discrete-event simulation in logistics and supply chain management: a scientometric perspective

Giorgia Casella, Eleonora Bottani
3 citations
Production & Manufacturing Research
Business Process Modeling and Analysis
1.59
article

Discrete-event simulation in logistics and supply chain management: a scientometric perspective

Giorgia Casella, Eleonora Bottani
article en
3 citations

Abstract

This paper has been designed in the form of a systematic literature review intended for evaluating the state-of-the-art of discrete-event simulation (DES) usage in the logistics and supply chain management fields under a scientometric perspective. With this primary aim in mind, 127 papers published between 2009 and 2022 are analysed, with the specific purposes of: 1) providing an overview of DES studies in logistics and supply chain management, map the main topics covered within this stream of literature and their evolution in time; 2) providing a robust ranking of the journals and authors in the field; 3) evaluating the rigor in the implementation of DES models in the logistics and supply chain management literature; and finally 4) correlating, through statistical elaborations, all the previous aspects to the success of these papers, measured as the citations received per year, taking inspiration from scientometric disciplines.

Production & Manufacturing ResearchVol. 12(1)
University of Parma (IT)
Decent work and economic growth
Openalex Percentile: Top 13%
Business Process Modeling and Analysis
1.59
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