IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v634y2024ics0378437123010336.html
   My bibliography  Save this article

Cascading failure resilience analysis and recovery of automotive manufacturing supply chain networks considering enterprise roles

Author

Listed:
  • Fu, Xiuwen
  • Xu, Xiaojie
  • Li, Wenfeng

Abstract

With the rapid development of global trade, the member enterprises in the automotive manufacturing supply chain are widely spread around the world. As a result, the scale of the automotive manufacturing supply chain network has become increasingly large, and the structure has become more complex. At the same time, the connection between enterprises is becoming closer. On one hand, the close business relationships between enterprises and the vast network structure accelerate the operation efficiency of the automotive manufacturing supply chain network. On the other hand, it also exposes the entire network system to high risks of cascading failures when facing disruptions due to enterprise production interruptions. Therefore, this work aims to establish a realistic cascading failure model for the automotive manufacturing supply chain network to explore its cascading failure characteristics. Based on this model, a two-stage recovery strategy is proposed to enhance the network’s cascading failure resilience. Experimental results demonstrate the following findings: (1) underload nodes that emerge after load redistribution are the main cause of cascading failure resilience degradation in automotive manufacturing supply chain networks; (2) cascading failure resilience is negatively correlated with the load-exponential coefficient, the capacity lower-limit coefficient, and the attenuation-tolerance coefficient; (3) among four different types of attacks, cascading failures caused by the high eigenvector centrality attack strategy and the high degree attack strategy impose the most severe damage on the automotive manufacturing supply chain network; (4) the proposed two-stage recovery strategy can significantly improve the cascading failure resilience of the automotive manufacturing supply chain network.

Suggested Citation

  • Fu, Xiuwen & Xu, Xiaojie & Li, Wenfeng, 2024. "Cascading failure resilience analysis and recovery of automotive manufacturing supply chain networks considering enterprise roles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 634(C).
    • Handle: RePEc:eee:phsmap:v:634:y:2024:i:c:s0378437123010336
    DOI: 10.1016/j.physa.2023.129478
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437123010336
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2023.129478?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Duan, Dong-Li & Ling, Xiao-Dong & Wu, Xiao-Yue & OuYang, Di-Hua & Zhong, Bin, 2014. "Critical thresholds for scale-free networks against cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 252-258.
    2. Hao, Hongchang & Ma, Zhe & Wang, Anjian & Xing, Wanli & Song, Hao & Zhao, Pei & Wei, Jiangqiao & Zheng, Shuxian, 2023. "Modeling and assessing the robustness of the lithium global trade system against cascading failures," Resources Policy, Elsevier, vol. 85(PB).
    3. Clinton Free & Angela Hecimovic, 2021. "Global supply chains after COVID-19: the end of the road for neoliberal globalisation?," Accounting, Auditing & Accountability Journal, Emerald Group Publishing Limited, vol. 34(1), pages 58-84, September.
    4. Yang, Qihui & Scoglio, Caterina M. & Gruenbacher, Don M., 2021. "Robustness of supply chain networks against underload cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    5. Shi, Xiaoqiu & Long, Wei & Li, Yanyan & Deng, Dingshan, 2022. "Robustness of interdependent supply chain networks against both functional and structural cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    6. Liu, Honglu & Tian, Zhihong & Huang, Anqiang & Yang, Zaili, 2018. "Analysis of vulnerabilities in maritime supply chains," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 475-484.
    7. Geng, Liang & Xiao, Renbin, 2017. "Outer synchronization and parameter identification approach to the resilient recovery of supply network with uncertainty," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 407-421.
    8. Goldbeck, Nils & Angeloudis, Panagiotis & Ochieng, Washington, 2020. "Optimal supply chain resilience with consideration of failure propagation and repair logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    9. Kevin P. Scheibe & Jennifer Blackhurst, 2018. "Supply chain disruption propagation: a systemic risk and normal accident theory perspective," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 43-59, January.
    10. HOSSAIN, Niamat Ullah Ibne & Amrani, Safae El & Jaradat, Raed & Marufuzzaman, Mohammad & Buchanan, Randy & Rinaudo, Christina & Hamilton, Michael, 2020. "Modeling and assessing interdependencies between critical infrastructures using Bayesian network: A case study of inland waterway port and surrounding supply chain network," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    11. Zhao, Peixin & Yin, Shengnan & Han, Xue & Li, Zhuyue, 2021. "Research on lean supply chain network model based on node removal," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    12. Wang, Yingcong & Xiao, Renbin, 2016. "An ant colony based resilience approach to cascading failures in cluster supply network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 150-166.
    13. Xuerou Sheng & Leping Chen & Xueliang Yuan & Yuzhou Tang & Qian Yuan & Rong Chen & Qingsong Wang & Qiao Ma & Jian Zuo & Hongwei Liu, 2023. "Green supply chain management for a more sustainable manufacturing industry in China: a critical review," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(2), pages 1151-1183, February.
    14. Fu, Xiuwen & Li, Qing & Li, Wenfeng, 2023. "Modeling and analysis of industrial IoT reliability to cascade failures: An information-service coupling perspective," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    15. repec:eme:aaaj00:aaaj-06-2020-4634 is not listed on IDEAS
    16. Tang, Liang & Jing, Ke & He, Jie & Stanley, H. Eugene, 2016. "Complex interdependent supply chain networks: Cascading failure and robustness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 58-69.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yang, Qihui & Scoglio, Caterina M. & Gruenbacher, Don M., 2021. "Robustness of supply chain networks against underload cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    2. Li, Zhuyue & Zhao, Peixin & Han, Xue, 2022. "Agri-food supply chain network disruption propagation and recovery based on cascading failure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    3. Jing, Ke & Du, Xinru & Shen, Lixin & Tang, Liang, 2019. "Robustness of complex networks: Cascading failure mechanism by considering the characteristics of time delay and recovery strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    4. Nocera, Fabrizio & Contento, Alessandro & Gardoni, Paolo, 2024. "Risk analysis of supply chains: The role of supporting structures and infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    5. Zarghami, Seyed Ashkan & Dumrak, Jantanee, 2021. "Unearthing vulnerability of supply provision in logistics networks to the black swan events: Applications of entropy theory and network analysis," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    6. Li, Siping & Zhou, Yaoming, 2024. "Integrating equity and efficiency into urban logistics resilience under emergency lockdowns," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    7. Yu, Yu & Ma, Daipeng & Wang, Yong, 2024. "Structural resilience evolution and vulnerability assessment of semiconductor materials supply network in the global semiconductor industry," International Journal of Production Economics, Elsevier, vol. 270(C).
    8. Dmitry Ivanov, 2022. "Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 1411-1431, December.
    9. Mu, Dong & Ren, Huanyu & Wang, Chao & Yue, Xiongping & Du, Jianbang & Ghadimi, Pezhman, 2023. "Structural characteristics and disruption ripple effect in a meso-level electric vehicle Lithium-ion battery supply chain network," Resources Policy, Elsevier, vol. 80(C).
    10. Bai, Xiwen & Ma, Zhongjun & Zhou, Yaoming, 2023. "Data-driven static and dynamic resilience assessment of the global liner shipping network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    11. Dui, Hongyan & Zheng, Xiaoqian & Wu, Shaomin, 2021. "Resilience analysis of maritime transportation systems based on importance measures," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    12. Shi, Xiaoqiu & Long, Wei & Li, Yanyan & Deng, Dingshan, 2022. "Robustness of interdependent supply chain networks against both functional and structural cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    13. Ivanov, Dmitry & Dolgui, Alexandre, 2021. "OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications," International Journal of Production Economics, Elsevier, vol. 232(C).
    14. Schmidt, Christoph G. & Wuttke, David A. & Heese, H. Sebastian & Wagner, Stephan M., 2023. "Antecedents of public reactions to supply chain glitches," International Journal of Production Economics, Elsevier, vol. 259(C).
    15. Matthias Klumpp & Dominic Loske, 2021. "Sustainability and Resilience Revisited: Impact of Information Technology Disruptions on Empirical Retail Logistics Efficiency," Sustainability, MDPI, vol. 13(10), pages 1-20, May.
    16. Tang, Liang & Jing, Ke & He, Jie & Stanley, H. Eugene, 2016. "Robustness of assembly supply chain networks by considering risk propagation and cascading failure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 459(C), pages 129-139.
    17. Basu R, Jothi & Abdulrahman, Muhammad D. & Yuvaraj, M., 2023. "Improving agility and resilience of automotive spares supply chain: The additive manufacturing enabled truck model," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    18. Laura M. Canevari‐Luzardo & Frans Berkhout & Mark Pelling, 2020. "A relational view of climate adaptation in the private sector: How do value chain interactions shape business perceptions of climate risk and adaptive behaviours?," Business Strategy and the Environment, Wiley Blackwell, vol. 29(2), pages 432-444, February.
    19. Ghanei, Shima & Contreras, Ivan & Cordeau, Jean-François, 2023. "A two-stage stochastic collaborative intertwined supply network design problem under multiple disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    20. Antonio Zavala-Alcívar & María-José Verdecho & Juan-José Alfaro-Saiz, 2020. "A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain," Sustainability, MDPI, vol. 12(16), pages 1-38, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:634:y:2024:i:c:s0378437123010336. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.