Risk assessment of electric vehicle supply chain based on fuzzy synthetic evaluation. (1st September 2019)

• Record Type: Journal Article
• Authors: Wu, Yunna; Jia, Weibing; Li, Lingwenying; Song, Zixin; Xu, Chuanbo; Liu, Fangtong
• Is Part Of: Energy. Volume 182(2019)
• Page Start: 397
• Page End: 411
• Publication Date: 2019-09-01
• Subjects: Electric vehicle -- Supply chain -- Risk assessment -- Hesitant fuzzy linguistic term set -- Fuzzy synthetic evaluation; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2019.06.007
• Languages: English
• ISSNs: 0360-5442

Abstract

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. Highlights: Risk assessment is carried out in the field of electric vehicle supply chain. A risk assessment index system of electric vehicle supply chain is established. A risk assessment model is established based on fuzzy theories. An empirical study of China's electric vehicle supply chain is provided. Risk prevention suggestions are put forward based on the obtained results.