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The impact of learning and short-term experience on preferences for electric vehicles

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  • Aravena, C.
  • Denny, E.

Abstract

The transport sector is a key contributor of global greenhouse gas emissions and electric vehicles have become a focus in striving to achieve decarbonisation and efficiency in the sector. This study uses a stated preference methodology, specifically choice experiments, to investigate the attitudes and preferences of potential buyers for a number of technical, environmental and policy attributes of electric vehicles in Ireland. We specifically focus on whether learning through provision of information and a brief vehicle experience affects preferences and welfare measures. Previous studies have examined the role of lengthy electric vehicle demonstration trials, for example 3 month trials, on preferences. This paper addresses a gap in the literature by considering the role of much shorter scale experience (minutes rather than months) on attitudes which more closely represents the experience that a potential purchaser will have at the point of investment. Using random parameter models, our results show that people are willing to pay more for certain technical and environmental features of electric vehicles, however, policy measures such as preferential parking rates are seen to have a non-significant effect on utility of participants. The learning process increases the significance of the environmental component, and produces significantly higher willingness to pay for increased battery range and vehicle size.

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  • Aravena, C. & Denny, E., 2021. "The impact of learning and short-term experience on preferences for electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
  • Handle: RePEc:eee:rensus:v:152:y:2021:i:c:s136403212100931x
    DOI: 10.1016/j.rser.2021.111656
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    References listed on IDEAS

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    Cited by:

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    2. Peng, Qiao & Liu, Weilong & Zhang, Yong & Zeng, Shihong & Graham, Byron, 2023. "Generation planning for power companies with hybrid production technologies under multiple renewable energy policies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 176(C).
    3. Tan, Yang & Fukuda, Hiroatsu & Li, Zhang & Wang, Shuai & Gao, Weijun & Liu, Zhonghui, 2022. "Does the public support the construction of battery swapping station for battery electric vehicles? - Data from Hangzhou, China," Energy Policy, Elsevier, vol. 163(C).
    4. Yang, Zaoli & Li, Qin & Yan, Yamin & Shang, Wen-Long & Ochieng, Washington, 2022. "Examining influence factors of Chinese electric vehicle market demand based on online reviews under moderating effect of subsidy policy," Applied Energy, Elsevier, vol. 326(C).
    5. Sun, Ya-Fang & Zhang, Yue-Jun & Su, Bin, 2022. "How does global transport sector improve the emissions reduction performance? A demand-side analysis," Applied Energy, Elsevier, vol. 311(C).
    6. Grangeia, Carolina & Santos, Luan & Ferreira, Daniel Viana & Guimarães, Raphael & de Magalhães Ozorio, Luiz & Tavares, Arthur, 2023. "Energy transition scenarios in the transportation sector in Brazil: Contributions from the electrical mobility," Energy Policy, Elsevier, vol. 174(C).
    7. Meilinda Fitriani Nur Maghfiroh & Andante Hadi Pandyaswargo & Hiroshi Onoda, 2021. "Current Readiness Status of Electric Vehicles in Indonesia: Multistakeholder Perceptions," Sustainability, MDPI, vol. 13(23), pages 1-25, November.

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    More about this item

    Keywords

    Choice experiment; Electric vehicles; Ireland; Learning and experience effect; Price vector; Stable preferences;
    All these keywords.

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • R49 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Other

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