IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v80y2023ics0301420722006687.html
   My bibliography  Save this article

Structural characteristics and disruption ripple effect in a meso-level electric vehicle Lithium-ion battery supply chain network

Author

Listed:
  • Mu, Dong
  • Ren, Huanyu
  • Wang, Chao
  • Yue, Xiongping
  • Du, Jianbang
  • Ghadimi, Pezhman

Abstract

Lithium-ion batteries (LIBs) have attracted widespread attention due to their crucial role in determining the performance of electric vehicles (EVs). The global EV LIB supply chain network is susceptible to disruptions as the activities of relevant firms are increasingly international, intricate, and interdependent. Existing research on the disruption risks in the EV LIB supply chain network is limited, and the detected threats rely on macro-level analyses of international trade data. To fill this gap, this study constructs a meso-level EV LIB supply chain network based on the supplier-buyer relationship data of significant EV LIB firms from 2016 to 2020. The hidden disruption risks are investigated regarding supply chain network structural characteristics and disruption ripple effects. First, the evolution of critical structural characteristics of the EV LIB supply network is presented to identify the systematic disruption risks. Second, the scale and persistence of the disruption ripple effect in two realistic scenarios, i.e., single-firm disruption and interfirm transaction breakdown, are dynamically assessed. The results show that the global EV LIB supply chain network has a hub-and-spoke structure with a “robust yet fragile” characteristic and is dominated by focal battery manufacturers from China, Japan, and South Korea. In addition, hidden risky sources among EV LIB firms and interfirm transactions are identified. The results can support EV LIB-related firms by better understanding the supply chain network characteristics to cope with the ripple effects of disruptions.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:jrpoli:v:80:y:2023:i:c:s0301420722006687
    DOI: 10.1016/j.resourpol.2022.103225
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420722006687
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2022.103225?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. Zhao, Yiran & Gao, Xiangyun & An, Haizhong & Xi, Xian & Sun, Qingru & Jiang, Meihui, 2020. "The effect of the mined cobalt trade dependence Network's structure on trade price," Resources Policy, Elsevier, vol. 65(C).
    2. Lior Menzly & Oguzhan Ozbas, 2010. "Market Segmentation and Cross‐predictability of Returns," Journal of Finance, American Finance Association, vol. 65(4), pages 1555-1580, August.
    3. 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).
    4. Kartik Anand & Ben Craig & Goetz von Peter, 2015. "Filling in the blanks: network structure and interbank contagion," Quantitative Finance, Taylor & Francis Journals, vol. 15(4), pages 625-636, April.
    5. Dixit, Vijaya & Verma, Priyanka & Tiwari, Manoj Kumar, 2020. "Assessment of pre and post-disaster supply chain resilience based on network structural parameters with CVaR as a risk measure," International Journal of Production Economics, Elsevier, vol. 227(C).
    6. Alexandre Dolgui & Dmitry Ivanov, 2021. "Ripple effect and supply chain disruption management: new trends and research directions," International Journal of Production Research, Taylor & Francis Journals, vol. 59(1), pages 102-109, January.
    7. Lu, Bin & Liu, Jingru & Yang, Jianxin, 2017. "Substance flow analysis of lithium for sustainable management in mainland China: 2007–2014," Resources, Conservation & Recycling, Elsevier, vol. 119(C), pages 109-116.
    8. Lauren Cohen & Andrea Frazzini, 2008. "Economic Links and Predictable Returns," Journal of Finance, American Finance Association, vol. 63(4), pages 1977-2011, August.
    9. Felipe, Ángel & Ortuño, M. Teresa & Righini, Giovanni & Tirado, Gregorio, 2014. "A heuristic approach for the green vehicle routing problem with multiple technologies and partial recharges," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 111-128.
    10. Kumar, Rajeev Ranjan & Chakraborty, Abhishek & Mandal, Prasenjit, 2021. "Promoting electric vehicle adoption: Who should invest in charging infrastructure?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    11. Nikolay Osadchiy & Vishal Gaur & Sridhar Seshadri, 2016. "Systematic Risk in Supply Chain Networks," Management Science, INFORMS, vol. 62(6), pages 1755-1777, June.
    12. Hiroyasu Inoue & Yasuyuki Todo, 2019. "Firm-level propagation of shocks through supply-chain networks," Nature Sustainability, Nature, vol. 2(9), pages 841-847, September.
    13. 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.
    14. Hosseini, Seyedmohsen & Ivanov, Dmitry & Dolgui, Alexandre, 2019. "Review of quantitative methods for supply chain resilience analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 285-307.
    15. 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).
    16. Liu, Sen & Dong, Zhiliang & Ding, Chao & Wang, Tian & Zhang, Yichi, 2020. "Do you need cobalt ore? Estimating potential trade relations through link prediction," Resources Policy, Elsevier, vol. 66(C).
    17. Zhao, Laijun & Zhao, Yue & Hu, Qingmi & Li, Huiyong & Stoeter, Johan, 2018. "Evaluation of consolidation center cargo capacity and loctions for China railway express," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 117(C), pages 58-81.
    18. Paul F. Skilton & Ednilson Bernardes, 2015. "Competition network structure and product market entry," Strategic Management Journal, Wiley Blackwell, vol. 36(11), pages 1688-1696, November.
    19. Sun, Xin & Hao, Han & Zhao, Fuquan & Liu, Zongwei, 2017. "Tracing global lithium flow: A trade-linked material flow analysis," Resources, Conservation & Recycling, Elsevier, vol. 124(C), pages 50-61.
    20. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    21. Bombelli, Alessandro & Santos, Bruno F. & Tavasszy, Lóránt, 2020. "Analysis of the air cargo transport network using a complex network theory perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    22. 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.
    23. Hao, Han & Liu, Zongwei & Zhao, Fuquan & Geng, Yong & Sarkis, Joseph, 2017. "Material flow analysis of lithium in China," Resources Policy, Elsevier, vol. 51(C), pages 100-106.
    24. Wang, Jiepeng & Zhou, Hong & Jin, Xiaodan, 2021. "Risk transmission in complex supply chain network with multi-drivers," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    25. Chen, Guang & Kong, Rui & Wang, Yixin, 2020. "Research on the evolution of lithium trade communities based on the complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    26. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liang Xu & Shanyi Wang & Lei Xi & Yunlong Li & Jianmin Gao, 2024. "A Review of Thermal Management and Heat Transfer of Lithium-Ion Batteries," Energies, MDPI, vol. 17(16), pages 1-36, August.

    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. Shao, Liuguo & Kou, Wenwen & Zhang, Hua, 2022. "The evolution of the global cobalt and lithium trade pattern and the impacts of the low-cobalt technology of lithium batteries based on multiplex network," Resources Policy, Elsevier, vol. 76(C).
    2. Hu, Xiaoqian & Wang, Chao & Lim, Ming K. & Chen, Wei-Qiang & Teng, Limin & Wang, Peng & Wang, Heming & Zhang, Chao & Yao, Cuiyou & Ghadimi, Pezhman, 2023. "Critical systemic risk sources in global lithium-ion battery supply networks: Static and dynamic network perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
    3. Chen, Jinyu & Luo, Qian & Sun, Xin & Zhang, Zitao & Dong, Xuesong, 2023. "The impact of renewable energy consumption on lithium trade patterns: An industrial chain perspective," Resources Policy, Elsevier, vol. 85(PA).
    4. Hao, Hongchang & Xing, Wanli & Wang, Anjian & Song, Hao & Han, Yawen & Zhao, Pei & Xie, Ziqi & Chen, Xuemei, 2022. "Multi-layer networks research on analyzing supply risk transmission of lithium industry chain," Resources Policy, Elsevier, vol. 79(C).
    5. Gustavo Peralta, 2016. "The Nature of Volatility Spillovers across the International Capital Markets," CNMV Working Papers CNMV Working Papers no. 6, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
    6. Tang, Qianyong & Li, Huajiao & Qi, Yajie & Li, Yang & Liu, Haiping & Wang, Xingxing, 2023. "The reliability of the trade dependence network in the tungsten industry chain based on percolation," Resources Policy, Elsevier, vol. 82(C).
    7. Yang, Ping & Gao, Xiangyun & Zhao, Yiran & Jia, Nanfei & Dong, Xiaojuan, 2021. "Lithium resource allocation optimization of the lithium trading network based on material flow," Resources Policy, Elsevier, vol. 74(C).
    8. Shi, Huai-Long & Chen, Huayi, 2024. "Understanding co-movements based on heterogeneous information associations," International Review of Financial Analysis, Elsevier, vol. 94(C).
    9. Li, Guo & Xue, Jing & Li, Na & Ivanov, Dmitry, 2022. "Blockchain-supported business model design, supply chain resilience, and firm performance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    10. Liu, Bin & Xiao, Wen & Zhu, Xingting, 2023. "How does inter-industry spillover improve the performance of volatility forecasting?," The North American Journal of Economics and Finance, Elsevier, vol. 65(C).
    11. Balan Sundarakani & Okey Peter Onyia, 2021. "Fast, furious and focused approach to Covid-19 response: an examination of the financial and business resilience of the UAE logistics industry," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 26(4), pages 237-258, December.
    12. Yu, Yu & Ma, Daipeng & Zhu, Weiwei, 2023. "Resilience assessment of international cobalt trade network," Resources Policy, Elsevier, vol. 83(C).
    13. Liu, Meng & Li, Huajiao & Zhou, Jinsheng & Feng, Sida & Wang, Yanli & Wang, Xingxing, 2022. "Analysis of material flow among multiple phases of cobalt industrial chain based on a complex network," Resources Policy, Elsevier, vol. 77(C).
    14. Jin, Pengfei & Wang, Saige & Meng, Zheng & Chen, Bin, 2023. "China's lithium supply chains: Network evolution and resilience assessment," Resources Policy, Elsevier, vol. 87(PB).
    15. Xiongping Yue & Dong Mu & Chao Wang & Huanyu Ren & Jianbang Du & Pezhman Ghadimi, 2024. "Disruption risks to Chinese overseas flat panel display supply networks under China’s zero-COVID policy," Operations Management Research, Springer, vol. 17(2), pages 406-437, June.
    16. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry, 2023. "Efficient resilience portfolio design in the supply chain with consideration of preparedness and recovery investments," Omega, Elsevier, vol. 117(C).
    17. Wang, Jiepeng & Zhou, Hong & Sun, Xinlei & Yuan, Yufei, 2023. "A novel supply chain network evolving model under random and targeted disruptions," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    18. Alam, Md Fahim Bin & Tushar, Saifur Rahman & Ahmed, Tazim & Karmaker, Chitra Lekha & Bari, A.B.M. Mainul & de Jesus Pacheco, Diego Augusto & Nayyar, Anand & Islam, Abu Reza Md Towfiqul, 2024. "Analysis of the enablers to deal with the ripple effect in food grain supply chains under disruption: Implications for food security and sustainability," International Journal of Production Economics, Elsevier, vol. 270(C).
    19. Ivanov, Dmitry, 2023. "Intelligent digital twin (iDT) for supply chain stress-testing, resilience, and viability," International Journal of Production Economics, Elsevier, vol. 263(C).
    20. Esther Eiling & Raymond Kan & Ali Sharifkhani, 2018. "Sectoral Labor Reallocation and Return Predictability," Working Papers 2018-006, Human Capital and Economic Opportunity Working Group.

    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:jrpoli:v:80:y:2023:i:c:s0301420722006687. 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.elsevier.com/locate/inca/30467 .

    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.