Risk assessment of electric vehicle supply chain based on fuzzy synthetic evaluation
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 s...
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Veröffentlicht in: | Energy (Oxford) 2019-09, Vol.182, p.397-411 |
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creator | Wu, Yunna Jia, Weibing Li, Lingwenying Song, Zixin Xu, Chuanbo Liu, Fangtong |
description | 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.
•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. |
doi_str_mv | 10.1016/j.energy.2019.06.007 |
format | Article |
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•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.</description><identifier>ISSN: 0360-5442</identifier><identifier>EISSN: 1873-6785</identifier><identifier>DOI: 10.1016/j.energy.2019.06.007</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Assembly lines ; Electric vehicle ; Electric vehicles ; Evaluation ; Fuzzy sets ; Fuzzy synthetic evaluation ; Hesitant fuzzy linguistic term set ; Risk analysis ; Risk assessment ; Risk factors ; Risk levels ; Risk management ; Supply chain ; Supply chains</subject><ispartof>Energy (Oxford), 2019-09, Vol.182, p.397-411</ispartof><rights>2019 Elsevier Ltd</rights><rights>Copyright Elsevier BV Sep 1, 2019</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c392t-545bef594bf99a95f15a1ded66e3c87c138a18684866b2b4ed0b900a5a72327a3</citedby><cites>FETCH-LOGICAL-c392t-545bef594bf99a95f15a1ded66e3c87c138a18684866b2b4ed0b900a5a72327a3</cites><orcidid>0000-0001-5214-9964</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0360544219311296$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids></links><search><creatorcontrib>Wu, Yunna</creatorcontrib><creatorcontrib>Jia, Weibing</creatorcontrib><creatorcontrib>Li, Lingwenying</creatorcontrib><creatorcontrib>Song, Zixin</creatorcontrib><creatorcontrib>Xu, Chuanbo</creatorcontrib><creatorcontrib>Liu, Fangtong</creatorcontrib><title>Risk assessment of electric vehicle supply chain based on fuzzy synthetic evaluation</title><title>Energy (Oxford)</title><description>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.
•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.</description><subject>Assembly lines</subject><subject>Electric vehicle</subject><subject>Electric vehicles</subject><subject>Evaluation</subject><subject>Fuzzy sets</subject><subject>Fuzzy synthetic evaluation</subject><subject>Hesitant fuzzy linguistic term set</subject><subject>Risk analysis</subject><subject>Risk assessment</subject><subject>Risk factors</subject><subject>Risk levels</subject><subject>Risk management</subject><subject>Supply chain</subject><subject>Supply chains</subject><issn>0360-5442</issn><issn>1873-6785</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNp9kE1LxDAQhoMouK7-Aw8Bz61J2qbJRZDFL1gQZD2HNJ26qd10TdqF7q83Sz17msvzvjPzIHRLSUoJ5fdtCg7815QyQmVKeEpIeYYWVJRZwktRnKMFyThJijxnl-gqhJYQUggpF2jzYcM31iFACDtwA-4bDB2YwVuDD7C1pgMcxv2-m7DZautwpQPUuHe4GY_HCYfJDVsYIg0H3Y16sL27RheN7gLc_M0l-nx-2qxek_X7y9vqcZ2YTLIhnlNU0BQyrxoptSwaWmhaQ805ZEaUhmZCU8FFLjivWJVDTSpJiC50yTJW6myJ7ubeve9_RgiDavvRu7hSMVZmVLKcykjlM2V8H4KHRu293Wk_KUrUyZ9q1exPnfwpwlX0F2MPcwziBwcLXgVjwRmorY9-VN3b_wt-AUBte_I</recordid><startdate>20190901</startdate><enddate>20190901</enddate><creator>Wu, Yunna</creator><creator>Jia, Weibing</creator><creator>Li, Lingwenying</creator><creator>Song, Zixin</creator><creator>Xu, Chuanbo</creator><creator>Liu, Fangtong</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7ST</scope><scope>7TB</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>KR7</scope><scope>L7M</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0001-5214-9964</orcidid></search><sort><creationdate>20190901</creationdate><title>Risk assessment of electric vehicle supply chain based on fuzzy synthetic evaluation</title><author>Wu, Yunna ; Jia, Weibing ; Li, Lingwenying ; Song, Zixin ; Xu, Chuanbo ; Liu, Fangtong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c392t-545bef594bf99a95f15a1ded66e3c87c138a18684866b2b4ed0b900a5a72327a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Assembly lines</topic><topic>Electric vehicle</topic><topic>Electric vehicles</topic><topic>Evaluation</topic><topic>Fuzzy sets</topic><topic>Fuzzy synthetic evaluation</topic><topic>Hesitant fuzzy linguistic term set</topic><topic>Risk analysis</topic><topic>Risk assessment</topic><topic>Risk factors</topic><topic>Risk levels</topic><topic>Risk management</topic><topic>Supply chain</topic><topic>Supply chains</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wu, Yunna</creatorcontrib><creatorcontrib>Jia, Weibing</creatorcontrib><creatorcontrib>Li, Lingwenying</creatorcontrib><creatorcontrib>Song, Zixin</creatorcontrib><creatorcontrib>Xu, Chuanbo</creatorcontrib><creatorcontrib>Liu, Fangtong</creatorcontrib><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Environment Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Environment Abstracts</collection><jtitle>Energy (Oxford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wu, Yunna</au><au>Jia, Weibing</au><au>Li, Lingwenying</au><au>Song, Zixin</au><au>Xu, Chuanbo</au><au>Liu, Fangtong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Risk assessment of electric vehicle supply chain based on fuzzy synthetic evaluation</atitle><jtitle>Energy (Oxford)</jtitle><date>2019-09-01</date><risdate>2019</risdate><volume>182</volume><spage>397</spage><epage>411</epage><pages>397-411</pages><issn>0360-5442</issn><eissn>1873-6785</eissn><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.
•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.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.energy.2019.06.007</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0001-5214-9964</orcidid></addata></record> |
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subjects | Assembly lines Electric vehicle Electric vehicles Evaluation Fuzzy sets Fuzzy synthetic evaluation Hesitant fuzzy linguistic term set Risk analysis Risk assessment Risk factors Risk levels Risk management Supply chain Supply chains |
title | Risk assessment of electric vehicle supply chain based on fuzzy synthetic evaluation |
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