Ahmet Faruk Aysan , Serhat Yüksel , Serkan Eti , Hasan Dinçer , Mahmut Selami Akin , Hakan Kalkavan , Alexey Mikhaylov
{"title":"用于电动汽车需求分析的技术接受和使用统一理论及模糊人工智能模型","authors":"Ahmet Faruk Aysan , Serhat Yüksel , Serkan Eti , Hasan Dinçer , Mahmut Selami Akin , Hakan Kalkavan , Alexey Mikhaylov","doi":"10.1016/j.dajour.2024.100455","DOIUrl":null,"url":null,"abstract":"<div><p>This study aims to reveal consumers’ intention to purchase Electric Vehicles (EVs) based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model. A hybrid fuzzy decision-making model with three stages is proposed. First, the experts’ weights are computed using an artificial intelligence methodology. Second, eight UTAUT-based indicators are examined using a T-Spherical TOPSIS-based DEMATEL (TOP-DEMATEL) methodology. The criteria are weighted by using multi-SWARA (M-SWARA) methodology. Third, an evaluation is conducted for the seven emerging countries by considering a Spherical Fuzzy (SF) Additive Ratio Assessment (ARAS) technique. The main contribution of this study is that a new decision-making methodology can identify more significant determinants of intention to use EVs. The methodological contribution of this study is integrating artificial intelligence methodology with fuzzy decision-making theory. The findings demonstrate that environmental factors play the most significant role in the intention to use EVs. Additionally, performance expectancy is also another critical determinant. We also find environmental issues should also be given importance in the production process of EVs. Using fossil fuels while producing these vehicles will significantly reduce users’ confidence. This phenomenon will cause consumers with environmental awareness not to purchase these vehicles.</p></div>","PeriodicalId":100357,"journal":{"name":"Decision Analytics Journal","volume":"11 ","pages":"Article 100455"},"PeriodicalIF":0.0000,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772662224000596/pdfft?md5=3e798a210b78955f5feb468d42954c8a&pid=1-s2.0-S2772662224000596-main.pdf","citationCount":"0","resultStr":"{\"title\":\"A unified theory of acceptance and use of technology and fuzzy artificial intelligence model for electric vehicle demand analysis\",\"authors\":\"Ahmet Faruk Aysan , Serhat Yüksel , Serkan Eti , Hasan Dinçer , Mahmut Selami Akin , Hakan Kalkavan , Alexey Mikhaylov\",\"doi\":\"10.1016/j.dajour.2024.100455\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This study aims to reveal consumers’ intention to purchase Electric Vehicles (EVs) based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model. A hybrid fuzzy decision-making model with three stages is proposed. First, the experts’ weights are computed using an artificial intelligence methodology. Second, eight UTAUT-based indicators are examined using a T-Spherical TOPSIS-based DEMATEL (TOP-DEMATEL) methodology. The criteria are weighted by using multi-SWARA (M-SWARA) methodology. Third, an evaluation is conducted for the seven emerging countries by considering a Spherical Fuzzy (SF) Additive Ratio Assessment (ARAS) technique. The main contribution of this study is that a new decision-making methodology can identify more significant determinants of intention to use EVs. The methodological contribution of this study is integrating artificial intelligence methodology with fuzzy decision-making theory. The findings demonstrate that environmental factors play the most significant role in the intention to use EVs. Additionally, performance expectancy is also another critical determinant. We also find environmental issues should also be given importance in the production process of EVs. Using fossil fuels while producing these vehicles will significantly reduce users’ confidence. This phenomenon will cause consumers with environmental awareness not to purchase these vehicles.</p></div>\",\"PeriodicalId\":100357,\"journal\":{\"name\":\"Decision Analytics Journal\",\"volume\":\"11 \",\"pages\":\"Article 100455\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2772662224000596/pdfft?md5=3e798a210b78955f5feb468d42954c8a&pid=1-s2.0-S2772662224000596-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Decision Analytics Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772662224000596\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Decision Analytics Journal","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772662224000596","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A unified theory of acceptance and use of technology and fuzzy artificial intelligence model for electric vehicle demand analysis
This study aims to reveal consumers’ intention to purchase Electric Vehicles (EVs) based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model. A hybrid fuzzy decision-making model with three stages is proposed. First, the experts’ weights are computed using an artificial intelligence methodology. Second, eight UTAUT-based indicators are examined using a T-Spherical TOPSIS-based DEMATEL (TOP-DEMATEL) methodology. The criteria are weighted by using multi-SWARA (M-SWARA) methodology. Third, an evaluation is conducted for the seven emerging countries by considering a Spherical Fuzzy (SF) Additive Ratio Assessment (ARAS) technique. The main contribution of this study is that a new decision-making methodology can identify more significant determinants of intention to use EVs. The methodological contribution of this study is integrating artificial intelligence methodology with fuzzy decision-making theory. The findings demonstrate that environmental factors play the most significant role in the intention to use EVs. Additionally, performance expectancy is also another critical determinant. We also find environmental issues should also be given importance in the production process of EVs. Using fossil fuels while producing these vehicles will significantly reduce users’ confidence. This phenomenon will cause consumers with environmental awareness not to purchase these vehicles.