IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v182y2019icp397-411.html
   My bibliography  Save this article

Risk assessment of electric vehicle supply chain based on fuzzy synthetic evaluation

Author

Listed:
  • Wu, Yunna
  • Jia, Weibing
  • Li, Lingwenying
  • Song, Zixin
  • Xu, Chuanbo
  • Liu, Fangtong

Abstract

In recent years, electric vehicles have witnessed rapid development. However, with the characteristic of numerous complexity links, there are many uncertainties exist in the supply chain which will cause high risks to the electric vehicles. Thus, carrying out a risk assessment is essential for the supply chain. The purpose of this paper is to identify and assess the potential risk factors for China's electric vehicle supply chain under uncertain circumstance. Firstly, this paper establishes a risk assessment index system for electric vehicle supply chain, which consists of three aspects and associated 15 indexes. Secondly, a combined hesitant fuzzy linguistic term set with fuzzy synthetic evaluation is developed. Thirdly, the risk assessment on China's electric vehicle supply chain is conducted. The results show that the risk level of the electric vehicle supply chains in China is between “general” and “high”. And the technical aspect and market aspect should be noted, mainly involving the information sharing risk and the assembly line setting risk. This paper can help managers of electric vehicle supply chain not only identify potential risks but also develop appropriate risk prevention measures.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:energy:v:182:y:2019:i:c:p:397-411
    DOI: 10.1016/j.energy.2019.06.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219311296
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2019.06.007?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.

    Citations

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


    Cited by:

    1. Liu, Xinglei & Liu, Jun & Ren, Kezheng & Liu, Xiaoming & Liu, Jiacheng, 2022. "An integrated fuzzy multi-energy transaction evaluation approach for energy internet markets considering judgement credibility and variable rough precision," Energy, Elsevier, vol. 261(PB).
    2. Guangpeng Wang & Yong Liu & Ziying Hu & Yanli Lyu & Guoming Zhang & Jifu Liu & Yun Liu & Yu Gu & Xichen Huang & Hao Zheng & Qingyan Zhang & Zongze Tong & Chang Hong & Lianyou Liu, 2020. "Flood Risk Assessment Based on Fuzzy Synthetic Evaluation Method in the Beijing-Tianjin-Hebei Metropolitan Area, China," Sustainability, MDPI, vol. 12(4), pages 1-30, February.
    3. Sandeep Jagani & Erika Marsillac & Paul Hong, 2024. "The Electric Vehicle Supply Chain Ecosystem: Changing Roles of Automotive Suppliers," Sustainability, MDPI, vol. 16(4), pages 1-19, February.
    4. 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.
    5. Fan Zhang & Hongxia Yang & Shengbin Li, 2024. "A Multi-Project Evaluation of Engineering Students’ Performance for Online PBL: Taking the Sustainable Decision Analysis Course as an Example," Sustainability, MDPI, vol. 16(4), pages 1-20, February.
    6. Francisco Rodrigues Lima-Junior & Mery Ellen Brandt de Oliveira & Carlos Henrique Lopes Resende, 2023. "An Overview of Applications of Hesitant Fuzzy Linguistic Term Sets in Supply Chain Management: The State of the Art and Future Directions," Mathematics, MDPI, vol. 11(13), pages 1-40, June.
    7. Wu, Yunna & Zhang, Ting, 2021. "Risk assessment of offshore wave-wind-solar-compressed air energy storage power plant through fuzzy comprehensive evaluation model," Energy, Elsevier, vol. 223(C).
    8. Nishat Alam Choudhary & Shalabh Singh & Tobias Schoenherr & M. Ramkumar, 2023. "Risk assessment in supply chains: a state-of-the-art review of methodologies and their applications," Annals of Operations Research, Springer, vol. 322(2), pages 565-607, March.
    9. Shuo Gao & Ming Kim Lim & Renlu Qiao & Chensi Shen & Chentao Li & Li Xia, 2022. "Identifying critical failure factors of green supply chain management in China’s SMEs with a hierarchical cause–effect model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(4), pages 5641-5666, April.
    10. Qingyou Yan & Meijuan Zhang & Wei Li & Guangyu Qin, 2020. "Risk Assessment of New Energy Vehicle Supply Chain Based on Variable Weight Theory and Cloud Model: A Case Study in China," Sustainability, MDPI, vol. 12(8), pages 1-21, April.
    11. E, Jiaqiang & Zeng, Yan & Jin, Yu & Zhang, Bin & Huang, Zhonghua & Wei, Kexiang & Chen, Jingwei & Zhu, Hao & Deng, Yuanwang, 2020. "Heat dissipation investigation of the power lithium-ion battery module based on orthogonal experiment design and fuzzy grey relation analysis," Energy, Elsevier, vol. 211(C).
    12. Han, Jie & Jiang, Cailou & Liu, Rong, 2023. "Does intelligent transformation trigger technology innovation in China's NEV enterprises?," Energy, Elsevier, vol. 270(C).
    13. Gerda Žigienė & Egidijus Rybakovas & Rimgailė Vaitkienė & Vaidas Gaidelys, 2022. "Setting the Grounds for the Transition from Business Analytics to Artificial Intelligence in Solving Supply Chain Risk," Sustainability, MDPI, vol. 14(19), pages 1-23, September.
    14. Qinghua Mao & Mengxin Guo & Jian Lv & Jinjin Chen & Pengzhen Xie & Meng Li, 2022. "A Risk Assessment Framework of Hybrid Offshore Wind–Solar PV Power Plants under a Probabilistic Linguistic Environment," Sustainability, MDPI, vol. 14(7), pages 1-29, April.
    15. Jiskani, Izhar Mithal & Cai, Qingxiang & Zhou, Wei & Lu, Xiang, 2020. "Assessment of risks impeding sustainable mining in Pakistan using fuzzy synthetic evaluation," Resources Policy, Elsevier, vol. 69(C).
    16. Kumar, Rajeev Ranjan & Guha, Pritha & Chakraborty, Abhishek, 2022. "Comparative assessment and selection of electric vehicle diffusion models: A global outlook," Energy, Elsevier, vol. 238(PC).
    17. Latino, Carmelo & Pelizzon, Loriana & Riedel, Max, 2023. "How to green the European Auto ABS market? A literature survey," SAFE Working Paper Series 391, Leibniz Institute for Financial Research SAFE.
    18. 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).
    19. Panah, Payam Ghaebi & Bornapour, Mosayeb & Hemmati, Reza & Guerrero, Josep M., 2021. "Charging station Stochastic Programming for Hydrogen/Battery Electric Buses using Multi-Criteria Crow Search Algorithm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    20. Gao, Jianwei & Guo, Fengjia & Li, Xiangzhen & Huang, Xin & Men, Huijuan, 2021. "Risk assessment of offshore photovoltaic projects under probabilistic linguistic environment," Renewable Energy, Elsevier, vol. 163(C), pages 172-187.
    21. Tiancheng Cao & Wenxin Mu & Juanqiong Gou & Liyu Peng, 2020. "A Study of Risk Relevance Reasoning Based on a Context Ontology of Railway Accidents," Risk Analysis, John Wiley & Sons, vol. 40(8), pages 1589-1611, 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:energy:v:182:y:2019:i:c:p:397-411. 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.

    We have no bibliographic references for this item. You can help adding them by using 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/energy .

    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.