IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i19p12211-d925898.html
   My bibliography  Save this article

Brittleness Evolution Model of the Supply Chain Network Based on Adaptive Agent Graph Theory under the COVID-19 Pandemic

Author

Listed:
  • Wei Cao

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Xifu Wang

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

Abstract

The triggering of supply chain brittleness has a significant impact on enterprise benefits under attack from the COVID-19 pandemic. The complexity of the supply chain system, the uncertainty of the COVID-19 pandemic, and demand uncertainty have made the triggering and propagation of supply chain brittleness complicated. In this study, a brittleness evolution model based on adaptive agent graph theory has been constructed. The parameters of brittleness evolution, including brittleness entropy and the vertex state value, have been quantitatively designed, and the brittleness evolution model in which the adaptability of nodes is considered and is not considered is constructed. A simulation algorithm based on the integrated scheduling model of the supply chain has been established. Finally, the practicability of the proposed model and algorithm is demonstrated via a case study of an electronic supply chain network. The results indicate that the proposed model and algorithm can effectively analyze the brittleness evolution law of the supply chain under the impact of the COVID-19 pandemic, including the evolution law of the vertex state, the brittleness entropy of the vertex, the global entropy of brittleness, the seasonal evolution law of the supply chain brittleness, and the evolution law of the brittleness behavior.

Suggested Citation

  • Wei Cao & Xifu Wang, 2022. "Brittleness Evolution Model of the Supply Chain Network Based on Adaptive Agent Graph Theory under the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(19), pages 1-24, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12211-:d:925898
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/19/12211/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/19/12211/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wagner, Stephan M. & Neshat, Nikrouz, 2010. "Assessing the vulnerability of supply chains using graph theory," International Journal of Production Economics, Elsevier, vol. 126(1), pages 121-129, July.
    2. Abhijit Majumdar & Sanjib Kumar Sinha & Mahesh Shaw & K. Mathiyazhagan, 2021. "Analysing the vulnerability of green clothing supply chains in South and Southeast Asia using fuzzy analytic hierarchy process," International Journal of Production Research, Taylor & Francis Journals, vol. 59(3), pages 752-771, February.
    3. Elwood, Alan, 2021. "Supply chain resilience," Journal of Business Continuity & Emergency Planning, Henry Stewart Publications, vol. 15(1), pages 65-77, September.
    4. Haixia Bai & Wenxue Ran, 2022. "Analysis of the Vulnerability and Resilience of the Tourism Supply Chain under the Uncertain Environment of COVID-19: Case Study Based on Lijiang," Sustainability, MDPI, vol. 14(5), pages 1-20, February.
    5. Nai-Ru Xu & Jia-Bao Liu & De-Xun Li & Jun Wang, 2016. "Research on Evolutionary Mechanism of Agile Supply Chain Network via Complex Network Theory," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-9, January.
    6. Chris Shughrue & Karen C. Seto, 2018. "Systemic vulnerabilities of the global urban-industrial network to hazards," Climatic Change, Springer, vol. 151(2), pages 173-187, November.
    7. Nadia M. Viljoen & Johan W. Joubert, 2018. "The Road most Travelled: The Impact of Urban Road Infrastructure on Supply Chain Network Vulnerability," Networks and Spatial Economics, Springer, vol. 18(1), pages 85-113, March.
    8. Fei Ma & Huifeng Xue & Kum Fai Yuen & Qipeng Sun & Shumei Zhao & Yanxia Zhang & Kai Huang, 2020. "Assessing the Vulnerability of Logistics Service Supply Chain Based on Complex Network," Sustainability, MDPI, vol. 12(5), pages 1-18, March.
    9. Nakatani, Jun & Tahara, Kiyotaka & Nakajima, Kenichi & Daigo, Ichiro & Kurishima, Hideaki & Kudoh, Yuki & Matsubae, Kazuyo & Fukushima, Yasuhiro & Ihara, Tomohiko & Kikuchi, Yasunori & Nishijima, Asak, 2018. "A graph theory-based methodology for vulnerability assessment of supply chains using the life cycle inventory database," Omega, Elsevier, vol. 75(C), pages 165-181.
    10. Naghshineh, Bardia & Carvalho, Helena, 2022. "The implications of additive manufacturing technology adoption for supply chain resilience: A systematic search and review," International Journal of Production Economics, Elsevier, vol. 247(C).
    11. Salomée Ruel & Sabry Shaaban & Margaux Ducros, 2019. "Supply chain vulnerability: contributions from an edifying case study," Post-Print hal-02903549, HAL.
    12. Mohammad Ali Yamin, 2021. "Investigating the Drivers of Supply Chain Resilience in the Wake of the COVID-19 Pandemic: Empirical Evidence from an Emerging Economy," Sustainability, MDPI, vol. 13(21), pages 1-16, October.
    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. Jiakuan Chen & Haoyu Wen, 2023. "The application of complex network theory for resilience improvement of knowledge-intensive supply chains," Operations Management Research, Springer, vol. 16(3), pages 1140-1161, September.
    2. Seyyed Mohammad Seyyed Alizadeh Ganji & Mohammad Hayati, 2016. "Identifying and Assessing the Risks in the Supply Chain," Modern Applied Science, Canadian Center of Science and Education, vol. 10(6), pages 1-74, June.
    3. Zsuzsanna Bacsi & Mária Fekete-Farkas & Muhammad Imam Ma’ruf, 2023. "A Graph-Based Network Analysis of Global Coffee Trade—The Impact of COVID-19 on Trade Relations in 2020," Sustainability, MDPI, vol. 15(4), pages 1-32, February.
    4. Eunji Oh & M. Minsuk Shin, 2020. "Study Abroad in Support of Higher Education Sustainability: An Application of Service Trade Strategies," Sustainability, MDPI, vol. 12(6), pages 1-23, March.
    5. Fangzhong Qi & Leilei Zhang & Kexiang Zhuo & Xiuyan Ma, 2022. "Early Warning for Manufacturing Supply Chain Resilience Based on Improved Grey Prediction Model," Sustainability, MDPI, vol. 14(20), pages 1-16, October.
    6. Lorenzo Bruno Prataviera & Alessandro Creazza & Marco Melacini & Fabrizio Dallari, 2022. "Heading for Tomorrow: Resilience Strategies for Post-COVID-19 Grocery Supply Chains," Sustainability, MDPI, vol. 14(4), pages 1-17, February.
    7. Huimin Liu & Yupeng Shi & Xuze Yang & Wentao Zhang, 2023. "The Role of Business Environment and Digital Government in Mitigating Supply Chain Vulnerability—Evidence from the COVID-19 Shock," Sustainability, MDPI, vol. 15(3), pages 1-15, January.
    8. Maureen S. Golan & Laura H. Jernegan & Igor Linkov, 2020. "Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic," Environment Systems and Decisions, Springer, vol. 40(2), pages 222-243, June.
    9. Vijay Pereira & Umesh Bamel, 2023. "Charting the managerial and theoretical evolutionary path of AHP using thematic and systematic review: a decadal (2012–2021) study," Annals of Operations Research, Springer, vol. 326(2), pages 635-651, July.
    10. Björn Häckel & Florian Hänsch & Michael Hertel & Jochen Übelhör, 2019. "Assessing IT availability risks in smart factory networks," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 523-558, December.
    11. Jarmila Horváthová & Martina Mokrišová & Martin Bača, 2023. "Bankruptcy Prediction for Sustainability of Businesses: The Application of Graph Theoretical Modeling," Mathematics, MDPI, vol. 11(24), pages 1-20, December.
    12. Hatem Elleuch & Wafik Hachicha & Habib Chabchoub, 2014. "A combined approach for supply chain risk management: description and application to a real hospital pharmaceutical case study," Journal of Risk Research, Taylor & Francis Journals, vol. 17(5), pages 641-663, May.
    13. Manu Sharma & Deepak Kaushal & Sudhanshu Joshi, 2023. "Strategic measures for enhancing resiliency in knowledge base supply chains: an emerging economy perspective," Operations Management Research, Springer, vol. 16(3), pages 1185-1205, September.
    14. Joon-Seok Kim & Nina Shin, 2021. "Planning for Railway Station Network Sustainability Based on Node–Place Analysis of Local Stations," Sustainability, MDPI, vol. 13(9), pages 1-12, April.
    15. Masato Abe & Linghe Ye, 2013. "Building Resilient Supply Chains against Natural Disasters: The Cases of Japan and Thailand," Global Business Review, International Management Institute, vol. 14(4), pages 567-586, December.
    16. 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).
    17. Tomas Cherkos Kassaneh & Ettore Bolisani & Juan-Gabriel Cegarra-Navarro, 2021. "Knowledge Management Practices for Sustainable Supply Chain Management: A Challenge for Business Education," Sustainability, MDPI, vol. 13(5), pages 1-15, March.
    18. Chowdhury, Md. Maruf Hossan & Quaddus, Mohammed A., 2015. "A multiple objective optimization based QFD approach for efficient resilient strategies to mitigate supply chain vulnerabilities: The case of garment industry of Bangladesh☆,☆☆☆This manuscript was pro," Omega, Elsevier, vol. 57(PA), pages 5-21.
    19. Xu Xu & Chan He, 2022. "The Effects of Network Structure Attributes on Growth Performance of Logistics Service Integrators in Logistics Service Supply Chain: Empirical Evidence," Sustainability, MDPI, vol. 14(24), pages 1-18, December.
    20. Ding, Yueting & Chen, Sai & Zheng, Yilei & Chai, Shanglei & Nie, Rui, 2022. "Resilience assessment of China's natural gas system under supply shortages: A system dynamics approach," Energy, Elsevier, vol. 247(C).

    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:gam:jsusta:v:14:y:2022:i:19:p:12211-:d:925898. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.