Quantitative models for managing supply chain risks: A review

Behnam Fahimnia*, Christopher S. Tang, Hoda Davarzani, Joseph Sarkis

*Corresponding author for this work

Research output: Contribution to journalReview ArticleScientificpeer-review

203 Citations (Scopus)

Abstract

As supply chain risk management has transitioned from an emerging topic to a growing research area, there is a need to classify different types of research and examine the general trends of this research area. This helps identify fertile research streams with great potential for further examination. This paper presents a systematic review of the quantitative and analytical models (i.e. mathematical, optimization and simulation modeling efforts) for managing supply chain risks. We use bibliometric and network analysis tools to generate insights that have not been captured in the previous reviews on the topic. In particular, we complete a systemic mapping of the literature that identifies the key research clusters/topics, interrelationships, and generative research areas that have provided the field with the foundational knowledge, concepts, theories, tools, and techniques. Some of our findings include (1) quantitative analysis of supply chain risk is expanding rapidly; (2) European journals are the more popular research outlets for the dissemination of the knowledge developed by researchers in United States and Asia; and (3) sustainability risk analysis is an emerging and fast evolving research topic.

Original languageEnglish
Peer-reviewed scientific journalEuropean Journal of Operational Research
Volume247
Issue number1
Pages (from-to)1-15
Number of pages15
ISSN0377-2217
DOIs
Publication statusPublished - 16.11.2015
MoE publication typeA2 Review article in a scientific journal

Keywords

  • 512 Business and Management
  • Supply Chain Risk
  • Uncertainty
  • Quantitative Model
  • Review
  • Bibliometrics and network analysis

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