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Who is more likely to buy electric vehicles?

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  • Naseri, Hamed
  • Waygood, E.O.D.
  • Patterson, Zachary
  • Wang, Bobin

Abstract

To promote electric vehicles, it is vital to know what impacts the preferences for electric vehicles over conventional fuel-based cars. To address this, a discrete choice experiment is developed and integrated into a survey. An online survey was conducted in Canada with 2062 valid responses. Different labels are designed for the survey to determine the most effective GHG information framing to increase the influence of such information on decisions. In this study, the influence of lifecycle emissions is considered. Three ensemble learning techniques are applied and they are compared based on prediction accuracy, and the most accurate technique is applied to determine the relative influence of variables on the intention to buy electric vehicles. Further, the interaction of variables is investigated using xgbfir. Subsequently, Accumulated Local Effect (ALE) is employed to examine the influence direction of top variables on the electric vehicle purchase likelihood. The results suggest that environmental attitudes and purchase price are the most influential parameters on the intention to buy electric vehicles. Moreover, those who are extremely worried about climate change, do not own a car, and self-identified as being at the top of the climate change stage of change are more likely to buy electric vehicles.

Suggested Citation

  • Naseri, Hamed & Waygood, E.O.D. & Patterson, Zachary & Wang, Bobin, 2024. "Who is more likely to buy electric vehicles?," Transport Policy, Elsevier, vol. 155(C), pages 15-28.
    • Handle: RePEc:eee:trapol:v:155:y:2024:i:c:p:15-28
    DOI: 10.1016/j.tranpol.2024.06.013
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    References listed on IDEAS

    as
    1. Shoki Kosai & Sazalina Zakaria & Hang Seng Che & Md Hasanuzzaman & Nasrudin Abd Rahim & Chiakwang Tan & Radin Diana R. Ahmad & Ahmad Rosly Abbas & Katsuyuki Nakano & Eiji Yamasue & Wei Kian Woon & Amm, 2022. "Estimation of Greenhouse Gas Emissions of Petrol, Biodiesel and Battery Electric Vehicles in Malaysia Based on Life Cycle Approach," Sustainability, MDPI, vol. 14(10), pages 1-12, May.
    2. Marco Boeri & Daniel Saure & Alexander Schacht & Elisabeth Riedl & Brett Hauber, 2020. "Modeling Heterogeneity in Patients’ Preferences for Psoriasis Treatments in a Multicountry Study: A Comparison Between Random-Parameters Logit and Latent Class Approaches," PharmacoEconomics, Springer, vol. 38(6), pages 593-606, June.
    3. Austmann, Leonhard M., 2021. "Drivers of the electric vehicle market: A systematic literature review of empirical studies," Finance Research Letters, Elsevier, vol. 41(C).
    4. Jeon, Hongjun & Seo, Wonchul & Park, Eunjeong & Choi, Sungchul, 2020. "Hybrid machine learning approach for popularity prediction of newly released contents of online video streaming services," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    5. Ramos-Real, Francisco J. & Ramírez-Díaz, Alfredo & Marrero, Gustavo A. & Perez, Yannick, 2018. "Willingness to pay for electric vehicles in island regions: The case of Tenerife (Canary Islands)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 140-149.
    6. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    7. Barros, Victor & Cruz, Carlos Oliveira & Júdice, Tomás & Sarmento, Joaquim Miranda, 2021. "Is taxation being effectively used to promote public transport in Europe?," Transport Policy, Elsevier, vol. 114(C), pages 215-224.
    8. Hardman, Scott, 2019. "Understanding the impact of reoccurring and non-financial incentives on plug-in electric vehicle adoption – A review," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 1-14.
    9. William F. Lamb & Michael Grubb & Francesca Diluiso & Jan C. Minx, 2022. "Countries with sustained greenhouse gas emissions reductions: an analysis of trends and progress by sector," Climate Policy, Taylor & Francis Journals, vol. 22(1), pages 1-17, January.
    10. Ziwen Ling & Christopher R. Cherry & Yi Wen, 2021. "Determining the Factors That Influence Electric Vehicle Adoption: A Stated Preference Survey Study in Beijing, China," Sustainability, MDPI, vol. 13(21), pages 1-22, October.
    11. Hidrue, Michael K. & Parsons, George R. & Kempton, Willett & Gardner, Meryl P., 2011. "Willingness to pay for electric vehicles and their attributes," Resource and Energy Economics, Elsevier, vol. 33(3), pages 686-705, September.
    12. Bas, Javier & Cirillo, Cinzia & Cherchi, Elisabetta, 2021. "Classification of potential electric vehicle purchasers: A machine learning approach," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    13. Daniel W. Apley & Jingyu Zhu, 2020. "Visualizing the effects of predictor variables in black box supervised learning models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(4), pages 1059-1086, September.
    14. Katarzyna Sobiech-Grabka & Anna Stankowska & Krzysztof Jerzak, 2022. "Determinants of Electric Cars Purchase Intention in Poland: Personal Attitudes v. Economic Arguments," Energies, MDPI, vol. 15(9), pages 1-26, April.
    15. Hamed Naseri & E. Owen D. Waygood & Bobin Wang & Zachary Patterson & Ricardo A. Daziano, 2021. "A Novel Feature Selection Technique to Better Predict Climate Change Stage of Change," Sustainability, MDPI, vol. 14(1), pages 1-23, December.
    16. Plananska, Jana & Gamma, Karoline, 2022. "Product bundling for accelerating electric vehicle adoption: A mixed-method empirical analysis of Swiss customers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    17. Zulfiqar Ali Lashari & Joonho Ko & Junseok Jang, 2021. "Consumers’ Intention to Purchase Electric Vehicles: Influences of User Attitude and Perception," Sustainability, MDPI, vol. 13(12), pages 1-14, June.
    18. Junyi Shen, 2009. "Latent class model or mixed logit model? A comparison by transport mode choice data," Applied Economics, Taylor & Francis Journals, vol. 41(22), pages 2915-2924.
    19. Abotalebi, Elnaz & Scott, Darren M. & Ferguson, Mark R., 2019. "Why is electric vehicle uptake low in Atlantic Canada? A comparison to leading adoption provinces," Journal of Transport Geography, Elsevier, vol. 74(C), pages 289-298.
    20. Zhu, Siying & Zhu, Feng, 2019. "Cycling comfort evaluation with instrumented probe bicycle," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 217-231.
    21. Hardman, Scott, 2019. "Understanding the Impact of Reoccurring and Non-Financial Incentives on Plug-in Electric Vehicle Adoption – A Review," Institute of Transportation Studies, Working Paper Series qt7v13w987, Institute of Transportation Studies, UC Davis.
    22. Lim, Sijeong & Dolsak, Nives & Prakash, Aseem & Tanaka, Seiki, 2022. "Distributional concerns and public opinion: EV subsidies in the U.S. and Japan," Energy Policy, Elsevier, vol. 164(C).
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