IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v192y2024ics0301421524002805.html
   My bibliography  Save this article

Understanding consumers’ non-compensatory and heterogeneous preferences for electric vehicles

Author

Listed:
  • Huo, Jinghai
  • Kim, Eui-Jin
  • Bansal, Prateek

Abstract

Previous studies eliciting preferences for battery electric vehicles (BEVs) assume the compensatory behavior of consumers, where all attributes of available alternatives are weighted in reaching a choice. However, consumers might follow non-compensatory rules where BEVs may become unattractive beyond certain attribute thresholds (i.e., cutoffs). To investigate non-compensatory and heterogeneous BEV preferences, we estimate a latent class model with attribute cutoffs using the preferences of over 800 potential car buyers from Singapore. We distinguish between early and late BEV adopters and their behaviors, highlighting the relevance of our findings in accelerating BEV adoption across various stages. For example, while current incentives primarily target reducing upfront costs, subsidizing electricity could be particularly effective for late adopters who prioritize future savings on operational expenses. Additionally, increasing the availability of BEV models from top-selling brands could effectively drive early BEV adoption in Singapore because early adopters place higher value on the availability of BEV models from the preferred brands when it is below their cutoff.

Suggested Citation

  • Huo, Jinghai & Kim, Eui-Jin & Bansal, Prateek, 2024. "Understanding consumers’ non-compensatory and heterogeneous preferences for electric vehicles," Energy Policy, Elsevier, vol. 192(C).
  • Handle: RePEc:eee:enepol:v:192:y:2024:i:c:s0301421524002805
    DOI: 10.1016/j.enpol.2024.114260
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421524002805
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.enpol.2024.114260?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Prateek Bansal & Rajeev Ranjan Kumar & Alok Raj & Subodh Dubey & Daniel J. Graham, 2021. "Willingness to Pay and Attitudinal Preferences of Indian Consumers for Electric Vehicles," Papers 2101.08008, arXiv.org, revised May 2021.
    2. Xiong, Siqin & Yuan, Yi & Yao, Jia & Bai, Bo & Ma, Xiaoming, 2023. "Exploring consumer preferences for electric vehicles based on the random coefficient logit model," Energy, Elsevier, vol. 263(PA).
    3. Jang, Sungsoon & Choi, Jae Young, 2021. "Which consumer attributes will act crucial roles for the fast market adoption of electric vehicles?: Estimation on the asymmetrical & heterogeneous consumer preferences on the EVs," Energy Policy, Elsevier, vol. 156(C).
    4. 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.
    5. Marcucci, Edoardo & Gatta, Valerio, 2011. "Regional airport choice: Consumer behaviour and policy implications," Journal of Transport Geography, Elsevier, vol. 19(1), pages 70-84.
    6. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    7. Fanchao Liao & Eric Molin & Bert van Wee, 2017. "Consumer preferences for electric vehicles: a literature review," Transport Reviews, Taylor & Francis Journals, vol. 37(3), pages 252-275, May.
    8. Román, Concepción & Arencibia, Ana Isabel & Feo-Valero, María, 2017. "A latent class model with attribute cut-offs to analyze modal choice for freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 212-227.
    9. Kim, Junghun & Seung, Hyunchan & Lee, Jongsu & Ahn, Joongha, 2020. "Asymmetric preference and loss aversion for electric vehicles: The reference-dependent choice model capturing different preference directions," Energy Economics, Elsevier, vol. 86(C).
    10. Qian, Lixian & Huang, Youlin & Tyfield, David & Soopramanien, Didier, 2023. "Dynamic consumer preferences for electric vehicles in China: A longitudinal approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    11. Bansal, Prateek & Kumar, Rajeev Ranjan & Raj, Alok & Dubey, Subodh & Graham, Daniel J., 2021. "Willingness to pay and attitudinal preferences of Indian consumers for electric vehicles," Energy Economics, Elsevier, vol. 100(C).
    12. Cirillo, Cinzia & Liu, Yan & Maness, Michael, 2017. "A time-dependent stated preference approach to measuring vehicle type preferences and market elasticity of conventional and green vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 294-310.
    13. Swait, Joffre, 2001. "A non-compensatory choice model incorporating attribute cutoffs," Transportation Research Part B: Methodological, Elsevier, vol. 35(10), pages 903-928, November.
    14. Ardeshiri, Ali & Rashidi, Taha Hossein, 2020. "Willingness to pay for fast charging station for electric vehicles with limited market penetration making," Energy Policy, Elsevier, vol. 147(C).
    15. Glenn Bush & Sergio Colombo & Nick Hanley, 2009. "Should all Choices Count? Using the Cut-Offs Approach to Edit Responses in a Choice Experiment," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 44(3), pages 397-414, November.
    16. Mabit, Stefan L. & Cherchi, Elisabetta & Jensen, Anders F. & Jordal-Jørgensen, Jørgen, 2015. "The effect of attitudes on reference-dependent preferences: Estimation and validation for the case of alternative-fuel vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 17-28.
    17. Ma, Shao-Chao & Xu, Jin-Hua & Fan, Ying, 2019. "Willingness to pay and preferences for alternative incentives to EV purchase subsidies: An empirical study in China," Energy Economics, Elsevier, vol. 81(C), pages 197-215.
    18. Danielis, Romeo & Marcucci, Edoardo, 2007. "Attribute cut-offs in freight service selection," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(5), pages 506-515, September.
    19. Xian, Yujiao & Wang, Qian & Fan, Wenrong & Da, Yabin & Fan, Jing-Li, 2022. "The impact of different incentive policies on new energy vehicle demand in China's gigantic cities," Energy Policy, Elsevier, vol. 168(C).
    20. Jia, Wenjian & Jiang, Zhiqiu & Wang, Qian & Xu, Bin & Xiao, Mei, 2023. "Preferences for zero-emission vehicle attributes: Comparing early adopters with mainstream consumers in California," Transport Policy, Elsevier, vol. 135(C), pages 21-32.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bansal, Prateek & Kumar, Rajeev Ranjan & Raj, Alok & Dubey, Subodh & Graham, Daniel J., 2021. "Willingness to pay and attitudinal preferences of Indian consumers for electric vehicles," Energy Economics, Elsevier, vol. 100(C).
    2. Oehlmann, Malte & Glenk, Klaus & Lloyd-Smith, Patrick & Meyerhoff, Jürgen, 2021. "Quantifying landscape externalities of renewable energy development: Implications of attribute cut-offs in choice experiments," Resource and Energy Economics, Elsevier, vol. 65(C).
    3. Jia, Wenjian & Jiang, Zhiqiu & Wang, Qian & Xu, Bin & Xiao, Mei, 2023. "Preferences for zero-emission vehicle attributes: Comparing early adopters with mainstream consumers in California," Transport Policy, Elsevier, vol. 135(C), pages 21-32.
    4. Evangelinos, Christos & Tscharaktschiew, Stefan & Marcucci, Edoardo & Gatta, Valerio, 2018. "Pricing workplace parking via cash-out: Effects on modal choice and implications for transport policy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 369-380.
    5. Moser, Riccarda & Raffaelli, Roberta, 2014. "Does attribute cut-off elicitation affect choice consistency? Contrasting hypothetical and real-money choice experiments," Journal of choice modelling, Elsevier, vol. 11(C), pages 16-29.
    6. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    7. Jia, Wenjian & Chen, T. Donna, 2023. "Investigating heterogeneous preferences for plug-in electric vehicles: Policy implications from different choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    8. Fatemeh Nazari & Abolfazl Mohammadian & Thomas Stephens, 2023. "Exploring the Role of Perceived Range Anxiety in Adoption Behavior of Plug-in Electric Vehicles," Papers 2308.10313, arXiv.org.
    9. Zhang, Rong & Zhu, Lichao, 2019. "Threshold incorporating freight choice modeling for hinterland leg transportation chain of export containers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 858-872.
    10. 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).
    11. Iogansen, Xiatian & Wang, Kailai & Bunch, David & Matson, Grant & Circella, Giovanni, 2023. "Deciphering the factors associated with adoption of alternative fuel vehicles in California: An investigation of latent attitudes, socio-demographics, and neighborhood effects," Transportation Research Part A: Policy and Practice, Elsevier, vol. 168(C).
    12. Bhat, Furqan A. & Verma, Ashish, 2024. "Electric two-wheeler adoption in India – A discrete choice analysis of motivators and barriers affecting the potential electric two-wheeler buyers," Transport Policy, Elsevier, vol. 152(C), pages 118-131.
    13. Román, Concepción & Arencibia, Ana Isabel & Feo-Valero, María, 2017. "A latent class model with attribute cut-offs to analyze modal choice for freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 212-227.
    14. Oryani, Bahareh & Koo, Yoonmo & Shafiee, Afsaneh & Rezania, Shahabaldin & Jung, Jiyeon & Choi, Hyunhong & Khan, Muhammad Kamran, 2022. "Heterogeneous preferences for EVs: Evidence from Iran," Renewable Energy, Elsevier, vol. 181(C), pages 675-691.
    15. Jaržemskis Andrius & Jaržemskienė Ilona, 2022. "European Green Deal Implications on Country Level Energy Consumption," Folia Oeconomica Stetinensia, Sciendo, vol. 22(2), pages 97-122, December.
    16. Chakraborty, Rahul & Chakravarty, Sujoy, 2023. "Factors affecting acceptance of electric two-wheelers in India: A discrete choice survey," Transport Policy, Elsevier, vol. 132(C), pages 27-41.
    17. Marcucci, Edoardo & Gatta, Valerio & Scaccia, Luisa, 2015. "Urban freight, parking and pricing policies: An evaluation from a transport providers’ perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 74(C), pages 239-249.
    18. Krishnan, V. Vijai & Sreekumar, M., 2023. "An integrated behavioral approach to analyze the adoption of electric vehicles in the context of a developing country," Transport Policy, Elsevier, vol. 142(C), pages 162-172.
    19. Shi, Lei & Wu, Rongxin & Lin, Boqiang, 2023. "Where will go for electric vehicles in China after the government subsidy incentives are abolished? A controversial consumer perspective," Energy, Elsevier, vol. 262(PA).
    20. Khakdaman, Masoud & Rezaei, Jafar & Tavasszy, Lóránt A., 2020. "Shippers’ willingness to delegate modal control in freight transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:192:y:2024:i:c:s0301421524002805. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.