Adoption of electric vehicles: Which factors are really important?
Electric vehicles stand out for their ability to reduce pollution. However, electric vehicle sales have not been brisk despite their positive effects. The objective of this study is twofold: first, to determine the variables that predict the purchase of an electric vehicle from the implementation of an algorithm based on computational intelligence; second, to contrast these results with two panels of experts in consumer behavior and the automobile sector. An empirical study was carried out with 404 potential consumers in Spain with regard to their beliefs, attitudes and purchase intention. The results show that range, incentives and reliability are the most reliable predictors of purchase intention. Likewise, the experts posit that the selection of these three variables would be sufficient to know the purchase intention of potential buyers of electric vehicles. In addition, it provides useful information for policy makers and private companies for decision making in the electric vehicle marketing process.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/15568318
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Supplemental Notes:
- © 2020 Taylor & Francis Group, LLC. Abstract reprinted with permission of Taylor & Francis.
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Authors:
- Higueras-Castillo, Elena
- Guillén, Alberto
- Herrera, Luis-Javier
- Liébana-Cabanillas, Francisco
- Publication Date: 2021-8
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 799-813
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Serial:
- International Journal of Sustainable Transportation
- Volume: 15
- Issue Number: 10
- Publisher: Taylor & Francis
- ISSN: 1556-8318
- EISSN: 1556-8334
- Serial URL: http://www.tandfonline.com/loi/ujst20
Subject/Index Terms
- TRT Terms: Attitudes; Automobile ownership; Consumer behavior; Electric vehicles; Incentives; Marketing; Reliability; Vehicle range
- Geographic Terms: Spain
- Subject Areas: Economics; Energy; Highways; Vehicles and Equipment;
Filing Info
- Accession Number: 01784581
- Record Type: Publication
- Files: TRIS
- Created Date: Oct 12 2021 4:53PM