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Who is more likely to buy an EV? A descriptive and integrated choice model analysis in the US Midwest

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  • Armantalab, Omid
  • Afzal, Hania
  • Hawkins, Jason

Abstract

This study uses a combined revealed and stated preference approach to analyze vehicle ownership in the US Midwest. We apply integrated choice and latent variable (ICLV) models to survey data that includes current vehicle details, future vehicle preferences, and responses to stated choice tasks. By comparing these approaches, we explore how choice varies between free selection and structured stated choice tasks, and assess the impact of latent attitudinal factors on individual choice variation. Our findings reveal that increasing awareness of electric vehicle (EV) attributes can substantially boost adoption rates. Conversely, concerns regarding long charging times are significant deterrents to EV adoption, while motivations related to environmental benefits, such as reduced air pollution and greenhouse gas (GHG) emissions, serve as strong incentives. Elasticity analysis reveals that the choice of electric vehicles is most sensitive to purchase price, with elasticities of 0.91% for small electric cars, 1.11% for large electric cars, and 0.80% for electric pickup trucks for a one percent change in price. Driving range exhibits the second-highest elasticity, underscoring the critical role of affordability and performance improvements in fostering EV adoption in the US Midwest.

Suggested Citation

  • Armantalab, Omid & Afzal, Hania & Hawkins, Jason, 2026. "Who is more likely to buy an EV? A descriptive and integrated choice model analysis in the US Midwest," Transport Policy, Elsevier, vol. 175(C).
    • Handle: RePEc:eee:trapol:v:175:y:2026:i:c:s0967070x25004202
    DOI: 10.1016/j.tranpol.2025.103877
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