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Volume 15, Issue 1 (Spring 2025)
Disaster Prev. Manag. Know. 2025, 15(1): 104-123 |
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Eskandari M, Asghari H, Modiri M. Identifying and Prioritizing Risk Factors in Supply Chain Logistics for Crisis Management Using an Integrated Fuzzy Approach. Disaster Prev. Manag. Know. 2025; 15 (1) :104-123
URL: http://dpmk.ir/article-1-718-en.html
URL: http://dpmk.ir/article-1-718-en.html
1- Faculty of Engineering and Passive Defense, Malek Ashtar University of Technology, Tehran, Iran.
2- Department of Crisis Management, Faculty of Engineering and Passive Defense, Malek Ashtar University of Technology, Tehran, Iran.
2- Department of Crisis Management, Faculty of Engineering and Passive Defense, Malek Ashtar University of Technology, Tehran, Iran.
Abstract: (737 Views)
Background and objective Recent global events such as the COVID-19 pandemic, wars, and climate change have led to changes in demand and disruptions in the supply chain logistics, which can challenge the food supply and security. In this regard, accurate and effective identification of threats is necessary to prevent vulnerability. Therefore, this research aims to identify and evaluate the most important risk factors that threaten supply chain logistics.
Method For this purpose, Pareto analysis and an integrated fuzzy approach, including MICMAC analysis and total interpretive structural modeling, were used.
Results According to the previous studies and based on expert feedback, 16 factors were initially identified. After applying the Pareto analysis, 12 factors were selected for further analysis. Finally, natural disasters, mismanagement in supplier selection, transportation strikes, shortage of skilled personnel, and minimal fuel consumption were identified as the most important risk factors.
Conclusion The results of this study can help managers and policymakers in Iran to make correct strategic decisions and thus achieve sustainable development goals by developing and increasing the resilience of supply chain logistics.
Method For this purpose, Pareto analysis and an integrated fuzzy approach, including MICMAC analysis and total interpretive structural modeling, were used.
Results According to the previous studies and based on expert feedback, 16 factors were initially identified. After applying the Pareto analysis, 12 factors were selected for further analysis. Finally, natural disasters, mismanagement in supplier selection, transportation strikes, shortage of skilled personnel, and minimal fuel consumption were identified as the most important risk factors.
Conclusion The results of this study can help managers and policymakers in Iran to make correct strategic decisions and thus achieve sustainable development goals by developing and increasing the resilience of supply chain logistics.
Type of Study: Research |
Subject:
Special
Received: 2024/09/24 | Accepted: 2025/01/15 | ePublished: 2025/03/30
Received: 2024/09/24 | Accepted: 2025/01/15 | ePublished: 2025/03/30
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Copyright © 2025 The Author(s)" by "authors retain the copyright and full publishing rights"
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