IDEAS home Printed from https://ideas.repec.org/a/eee/trapol/v160y2025icp125-137.html
   My bibliography  Save this article

Analyzing purchase intentions of used electric vehicles through consumer experiences: A structural equation modeling approach

Author

Listed:
  • Sheykhfard, Abbas
  • Azmoodeh, Mohammad
  • Das, Subasish
  • Kutela, Boniphace

Abstract

The transition rate to electric vehicles (EVs) has accelerated globally as indicated by a notable rise in the number of used EVs in the market. However, most existing studies focused on the attributes related to the new EVs. This study explores the factors influencing consumer purchase intentions of used EVs using structural equation modeling (SEM). Drawing on a survey of 992 used EV owners in the United States, the research examines the impact of sociodemographic characteristics, purchase details, information sources, pre-purchase concerns, current driving and charging experiences, and future purchase intentions. The findings reveal that charging ease has the strongest positive direct effect on future purchase intentions, while information sources and driving experience show negative direct effects. Sociodemographic characteristics and pre-purchase concerns indirectly influence future intentions through other factors. More specifically, income level, education, and Hispanic ethnicity positively contribute to the sociodemographic profile of EV owners. Further, traditional media plays a significant role in disseminating EV information, although online searches show a negative relationship with information source engagement. This comprehensive approach provides a nuanced understanding of the dynamics within the used EV market, ultimately supporting sustainable transportation initiatives. The study highlights the importance of addressing charging infrastructure, battery performance, and affordability concerns to enhance the used EV market's growth.

Suggested Citation

  • Sheykhfard, Abbas & Azmoodeh, Mohammad & Das, Subasish & Kutela, Boniphace, 2025. "Analyzing purchase intentions of used electric vehicles through consumer experiences: A structural equation modeling approach," Transport Policy, Elsevier, vol. 160(C), pages 125-137.
  • Handle: RePEc:eee:trapol:v:160:y:2025:i:c:p:125-137
    DOI: 10.1016/j.tranpol.2024.10.038
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0967070X24003305
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tranpol.2024.10.038?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.

    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:trapol:v:160:y:2025:i:c:p:125-137. 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.

    We have no bibliographic references for this item. You can help adding them by using 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/wps/find/journaldescription.cws_home/30473/description#description .

    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.