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Research on Dynamic Analysis and Mitigation Strategies of Supply Chains under Different Disruption Risks

Author

Listed:
  • Qing Zhang

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China)

  • Weiguo Fan

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China)

  • Jianchang Lu

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China)

  • Siqian Wu

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China)

  • Xuechao Wang

    (Sustainable Process Integration Laboratory—SPIL, NETME Centre, Faculty of Mechanical Engineering, Brno University of Technology—VUT Brno, Technická 2896/2, 616 69 Brno, Czech Republic)

Abstract

Due to the globalization of supply and production, supply chain management has tightened the connection between upstream and downstream enterprises. Although this modern strategy has significantly improved the efficiency of enterprises, the increasingly complex relationship between nodes also makes the supply chain system more vulnerable and unstable. As a result, the interruption of any node location in the supply chain will spread to other nodes via their diffusion, which could cause irreparable damage to the entire supply chain. Therefore, under this realistic background, only by quantitatively analyzing the specific impact on the supply chain of interruption events in different locations we can formulate active and effective mitigation strategies to achieve the effective recovery of node enterprises from interruption accidents. In this study, the system dynamics method was used to simulate the changes in inventory level, order accumulation, and profit level caused by disruption of supply, production, and sales of different node companies. The results show that the closer the node enterprise to the interruption source, the greater the risk of loss. Due to the conduction effect of the supply chain system, the risk spreads to other node enterprises. Based on the above results, corresponding mitigation strategies for enterprises to cope with different node interruptions are proposed to improve the overall efficiency and operational capabilities of the enterprise.

Suggested Citation

  • Qing Zhang & Weiguo Fan & Jianchang Lu & Siqian Wu & Xuechao Wang, 2021. "Research on Dynamic Analysis and Mitigation Strategies of Supply Chains under Different Disruption Risks," Sustainability, MDPI, vol. 13(5), pages 1-29, February.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:5:p:2462-:d:505402
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    References listed on IDEAS

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    1. Fangruo Chen, 2000. "Editorial Objectives Supply Chain Management," Management Science, INFORMS, vol. 46(9), pages 1-1, September.
    2. Florian Lücker & Ralf W. Seifert & Işık Biçer, 2019. "Roles of inventory and reserve capacity in mitigating supply chain disruption risk," International Journal of Production Research, Taylor & Francis Journals, vol. 57(4), pages 1238-1249, February.
    3. Zhu, Stuart X., 2015. "Analysis of dual sourcing strategies under supply disruptions," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 191-203.
    4. Sanjoy Kumar Paul & Shams Rahman, 2018. "A quantitative and simulation model for managing sudden supply delay with fuzzy demand and safety stock," International Journal of Production Research, Taylor & Francis Journals, vol. 56(13), pages 4377-4395, July.
    5. Gonul Kochan, Cigdem & Nowicki, David R. & Sauser, Brian & Randall, Wesley S., 2018. "Impact of cloud-based information sharing on hospital supply chain performance: A system dynamics framework," International Journal of Production Economics, Elsevier, vol. 195(C), pages 168-185.
    6. Yumei Hou & Qiang Zhang, 2009. "The Optimal Inventory Control Of A System With Random Lead Time Where Random Supply Interruptions Affect The Replenishment," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 26(04), pages 533-557.
    7. Nader Azad & Georgios Saharidis & Hamid Davoudpour & Hooman Malekly & Seyed Yektamaram, 2013. "Strategies for protecting supply chain networks against facility and transportation disruptions: an improved Benders decomposition approach," Annals of Operations Research, Springer, vol. 210(1), pages 125-163, November.
    8. Song Xu & Xiaotong Zhang & Lipan Feng & Wenting Yang, 2020. "Disruption risks in supply chain management: a literature review based on bibliometric analysis," International Journal of Production Research, Taylor & Francis Journals, vol. 58(11), pages 3508-3526, June.
    9. Wu, Yunna & Jia, Weibing & Li, Lingwenying & Song, Zixin & Xu, Chuanbo & Liu, Fangtong, 2019. "Risk assessment of electric vehicle supply chain based on fuzzy synthetic evaluation," Energy, Elsevier, vol. 182(C), pages 397-411.
    10. Wang, Hua & Gu, Tao & Jin, Maozhu & Zhao, Rong & Wang, Guanxiang, 2018. "The complexity measurement and evolution analysis of supply chain network under disruption risks," Chaos, Solitons & Fractals, Elsevier, vol. 116(C), pages 72-78.
    11. John D. Sterman, 1989. "Modeling Managerial Behavior: Misperceptions of Feedback in a Dynamic Decision Making Experiment," Management Science, INFORMS, vol. 35(3), pages 321-339, March.
    12. Wilson, Martha C., 2007. "The impact of transportation disruptions on supply chain performance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(4), pages 295-320, July.
    13. Mahdi Bashiri & Benny Tjahjono & Jordon Lazell & Jennifer Ferreira & Tomy Perdana, 2021. "The Dynamics of Sustainability Risks in the Global Coffee Supply Chain: A Case of Indonesia–UK," Sustainability, MDPI, vol. 13(2), pages 1-20, January.
    14. Sterman, John D., 1989. "Misperceptions of feedback in dynamic decision making," Organizational Behavior and Human Decision Processes, Elsevier, vol. 43(3), pages 301-335, June.
    15. Ahmadi-Javid, Amir & Hoseinpour, Pooya, 2019. "Service system design for managing interruption risks: A backup-service risk-mitigation strategy," European Journal of Operational Research, Elsevier, vol. 274(2), pages 417-431.
    16. Wang, Xiaojun & Chan, Hing Kai & Yee, Rachel W.Y. & Diaz-Rainey, Ivan, 2012. "A two-stage fuzzy-AHP model for risk assessment of implementing green initiatives in the fashion supply chain," International Journal of Production Economics, Elsevier, vol. 135(2), pages 595-606.
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    1. Katsoras, Efthymios & Georgiadis, Patroklos, 2022. "An integrated System Dynamics model for Closed Loop Supply Chains under disaster effects: The case of COVID-19," International Journal of Production Economics, Elsevier, vol. 253(C).
    2. Benjamin Korder & Julien Maheut & Matthias Konle, 2024. "Simulation Methods and Digital Strategies for Supply Chains Facing Disruptions: Insights from a Systematic Literature Review," Sustainability, MDPI, vol. 16(14), pages 1-31, July.
    3. Manel Elmsalmi & Wafik Hachicha & Awad M. Aljuaid, 2021. "Modeling Sustainable Risks Mitigation Strategies Using a Morphological Analysis-Based Approach: A Real Case Study," Sustainability, MDPI, vol. 13(21), pages 1-17, November.
    4. Efthymios Katsoras & Patroklos Georgiadis, 2022. "A Dynamic Analysis for Mitigating Disaster Effects in Closed Loop Supply Chains," Sustainability, MDPI, vol. 14(9), pages 1-20, April.
    5. Fahim ul Amin & Qian-Li Dong & Katarzyna Grzybowska & Zahid Ahmed & Bo-Rui Yan, 2022. "A Novel Fuzzy-Based VIKOR–CRITIC Soft Computing Method for Evaluation of Sustainable Supply Chain Risk Management," Sustainability, MDPI, vol. 14(5), pages 1-15, February.

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