IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i6p2733-d1615829.html
   My bibliography  Save this article

Evolution of Disruption Resilience in the Wood Forest Products Trade Network, Considering the Propagation of Disruption Risks and Underload Cascading Failure

Author

Listed:
  • Xiangyu Huang

    (College of Logistics, Central South University of Forestry and Technology, Changsha 410004, China
    Hunan Key Laboratory of Intelligent Logistics Technology, Changsha 410004, China)

  • Zhongwei Wang

    (College of Logistics, Central South University of Forestry and Technology, Changsha 410004, China
    Hunan Key Laboratory of Intelligent Logistics Technology, Changsha 410004, China)

  • Yan Pang

    (College of Logistics, Central South University of Forestry and Technology, Changsha 410004, China
    Hunan Key Laboratory of Intelligent Logistics Technology, Changsha 410004, China)

  • Wujun Tian

    (College of Computer Science and Mathematics, Central South University of Forestry and Technology, Changsha 410004, China)

Abstract

With the intensification of global resource competition, the issue of timber supply has escalated from an economic concern to a significant strategic challenge. This study focuses on the evolution of disruption resilience in the global trade network for wood forest products, aiming to reveal the patterns of resilience dynamics under disruption risks by simulating underload cascading failure phenomena. The study provides theoretical support for enhancing the security and stability of the global wood forest product supply chain. Utilizing global trade data from the UN Comtrade Database 2023, a directed weighted complex network model was constructed, spanning upstream, midstream, and downstream sectors, with trade intensity distances serving as edge weights. By developing an underload cascading failure model, the evolution of disruption resilience was simulated under various disruption scenarios from 2002 to 2023, and the long-term impacts of critical node failures on network performance were analyzed. The results demonstrate significant spatiotemporal heterogeneity in the disruption resilience of the global wood forest product trade network. The upstream network exhibits improved resilience in total node strength but reduced global efficiency. The midstream network shows marked volatility in resilience due to external shocks, such as the global financial crisis, while the downstream network remains relatively stable. Simulations reveal that failures in core nodes (e.g., China, the United States, and Germany) disproportionately degrade global efficiency and node strength, with node centrality metrics positively correlated with network performance loss. This study elucidates the evolutionary mechanisms of disruption resilience in the wood forest product trade network under risk propagation, offering actionable insights for optimizing network robustness and supply chain stability. It is recommended that policymakers promote green supply chain initiatives, accelerate afforestation projects, and enhance domestic timber self-sufficiency to reduce reliance on imported timber, thereby strengthening node resilience and fostering sustainable forest resource utilization for economic and environmental benefits.

Suggested Citation

  • Xiangyu Huang & Zhongwei Wang & Yan Pang & Wujun Tian, 2025. "Evolution of Disruption Resilience in the Wood Forest Products Trade Network, Considering the Propagation of Disruption Risks and Underload Cascading Failure," Sustainability, MDPI, vol. 17(6), pages 1-30, March.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:6:p:2733-:d:1615829
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/6/2733/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/6/2733/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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).
    2. Kim, Dong Hwan & Eisenberg, Daniel A. & Chun, Yeong Han & Park, Jeryang, 2017. "Network topology and resilience analysis of South Korean power grid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 13-24.
    3. Jianxi Gao & Baruch Barzel & Albert-László Barabási, 2016. "Erratum: Universal resilience patterns in complex networks," Nature, Nature, vol. 536(7615), pages 238-238, August.
    4. Liu, Wei & Song, Zhaoyang, 2020. "Review of studies on the resilience of urban critical infrastructure networks," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    5. Xuping Cao & Shuai Yang & Xiangmeng Huang & Juxi Tong, 2018. "Dynamic Decomposition of Factors Influencing the Export Growth of China’s Wood Forest Products," Sustainability, MDPI, vol. 10(8), pages 1-16, August.
    6. Ash, J. & Newth, D., 2007. "Optimizing complex networks for resilience against cascading failure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 673-683.
    7. B. Berche & C. von Ferber & T. Holovatch & Yu. Holovatch, 2009. "Resilience of public transport networks against attacks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(1), pages 125-137, September.
    8. Reggiani, Aura, 2013. "Network resilience for transport security: Some methodological considerations," Transport Policy, Elsevier, vol. 28(C), pages 63-68.
    9. Long, Ting & Pan, Huanxue & Dong, Chao & Qin, Tao & Ma, Ping, 2019. "Exploring the competitive evolution of global wood forest product trade based on complex network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1224-1232.
    10. 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).
    11. Lovrić, Marko & Da Re, Riccardo & Vidale, Enrico & Pettenella, Davide & Mavsar, Robert, 2018. "Social network analysis as a tool for the analysis of international trade of wood and non-wood forest products," Forest Policy and Economics, Elsevier, vol. 86(C), pages 45-66.
    12. 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).
    13. Wang, Chao & Yang, Hua & Hu, Xiaoqian & He, Xijun & Liu, Junge & Liang, Chen & Lim, Ming K., 2024. "Deciphering iron ore trade dynamics: Supply disruption risk propagation in global networks through an improved cascading failure model," Resources Policy, Elsevier, vol. 95(C).
    14. Li, Yuhong & Zobel, Christopher W. & Seref, Onur & Chatfield, Dean, 2020. "Network characteristics and supply chain resilience under conditions of risk propagation," International Journal of Production Economics, Elsevier, vol. 223(C).
    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. Xu, Peng-Cheng & Lu, Qing-Chang & Xie, Chi & Cheong, Taesu, 2024. "Modeling the resilience of interdependent networks: The role of function dependency in metro and bus systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    2. Liang, Zhenglin & Li, Yan-Fu, 2023. "Holistic Resilience and Reliability Measures for Cellular Telecommunication Networks," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    3. Liu, Qing & Yang, Yang & Ng, Adolf K.Y. & Jiang, Changmin, 2023. "An analysis on the resilience of the European port network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    4. Gopal R. Patil & B. K. Bhavathrathan, 2016. "Effect Of Traffic Demand Variation On Road Network Resilience," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 19(01n02), pages 1-18, February.
    5. Mrinal Kanti Sen & Subhrajit Dutta & Golam Kabir, 2021. "Flood Resilience of Housing Infrastructure Modeling and Quantification Using a Bayesian Belief Network," Sustainability, MDPI, vol. 13(3), pages 1-24, January.
    6. Gonçalves, L.A.P.J. & Ribeiro, P.J.G., 2020. "Resilience of urban transportation systems. Concept, characteristics, and methods," Journal of Transport Geography, Elsevier, vol. 85(C).
    7. Hadi Alizadeh & Ayyoob Sharifi, 2020. "Assessing Resilience of Urban Critical Infrastructure Networks: A Case Study of Ahvaz, Iran," Sustainability, MDPI, vol. 12(9), pages 1-20, May.
    8. Agnieszka Blokus-Dziula & Przemysław Dziula, 2024. "Risk Management Model of Urban Resilience Under a Changing Climate," Sustainability, MDPI, vol. 17(1), pages 1-23, December.
    9. Yao, Kaisen & Chen, Larry & Chen, Suren, 2025. "Time-evolving traffic resilience performance forecasting during hazardous weather toward proactive intervention," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    10. Zhang, Chao & Xu, Xin & Dui, Hongyan, 2020. "Resilience Measure of Network Systems by Node and Edge Indicators," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    11. Cats, Oded & Koppenol, Gert-Jaap & Warnier, Martijn, 2017. "Robustness assessment of link capacity reduction for complex networks: Application for public transport systems," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 544-553.
    12. Aura Reggiani, 2022. "The Architecture of Connectivity: A Key to Network Vulnerability, Complexity and Resilience," Networks and Spatial Economics, Springer, vol. 22(3), pages 415-437, September.
    13. Tian, Xu & Geng, Yong & Sarkis, Joseph & Gao, Cuixia & Sun, Xin & Micic, Tatyana & Hao, Han & Wang, Xin, 2021. "Features of critical resource trade networks of lithium-ion batteries," Resources Policy, Elsevier, vol. 73(C).
    14. Kashin Sugishita & Yasuo Asakura, 2021. "Vulnerability studies in the fields of transportation and complex networks: a citation network analysis," Public Transport, Springer, vol. 13(1), pages 1-34, March.
    15. Cerqueti, Roy & Ferraro, Giovanna & Iovanella, Antonio, 2019. "Measuring network resilience through connection patterns," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 320-329.
    16. Rocchetta, Roberto, 2022. "Enhancing the resilience of critical infrastructures: Statistical analysis of power grid spectral clustering and post-contingency vulnerability metrics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    17. Liu, Wei & Song, Zhaoyang, 2020. "Review of studies on the resilience of urban critical infrastructure networks," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    18. Henriette Heer & Lucas Streib & Ralf B Schäfer & Stefan Ruzika, 2020. "Maximising the clustering coefficient of networks and the effects on habitat network robustness," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-16, October.
    19. Lin Zhang & Jian Lu & Bai-bai Fu & Shu-bin Li, 2018. "A Review and Prospect for the Complexity and Resilience of Urban Public Transit Network Based on Complex Network Theory," Complexity, Hindawi, vol. 2018, pages 1-36, December.
    20. David J. Yu & Michael L. Schoon & Jason K. Hawes & Seungyoon Lee & Jeryang Park & P. Suresh C. Rao & Laura K. Siebeneck & Satish V. Ukkusuri, 2020. "Toward General Principles for Resilience Engineering," Risk Analysis, John Wiley & Sons, vol. 40(8), pages 1509-1537, 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:gam:jsusta:v:17:y:2025:i:6:p:2733-:d:1615829. 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.