IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v15y2025i2p21582440251335517.html
   My bibliography  Save this article

Environmental Perception and Willingness to Pay for Electric Vehicles: An Analysis Using the Lens Model

Author

Listed:
  • Yinan Dong

Abstract

As China transitions away from electric vehicles (EVs) purchase subsidies, understanding the factors influencing consumer adoption becomes increasingly important. While much research has focused on subsidies and technical attributes, few studies have examined the role of environmental perception in shaping consumer willingness to pay (WTP) for EVs. This study addresses this gap by investigating how different environmental stimuli influence WTP for key EVs attributes. A randomized controlled experiment involving 112 participants in Nanyang City was conducted using a choice experiment to assess WTP for attributes such as driving range, charging time, and emissions reduction. Participants were divided into groups exposed to different stimuli: distal (policy information), proximal (environmental quality images), both combined, and a control group with no stimuli. Results indicate that proximal stimuli significantly increased WTP, especially for driving range and charging time, while distal stimuli alone had a modest effect, enhancing WTP mainly for driving range. Combined stimuli yielded the highest overall increase in WTP across all EVs attributes, suggesting a strong synergistic effect of emotional and informational perception. These findings suggest that emotionally engaging, visual environmental perception heighten perceived value, while abstract policy information alone is less effective. This study provides practical insights for policymakers and EVs businesses, recommending strategies that blend tangible product improvements with emotionally resonant messaging to sustain market growth post-subsidy. Future research could explore the long-term impact of environmental perception and their applicability in broader geographic settings.

Suggested Citation

  • Yinan Dong, 2025. "Environmental Perception and Willingness to Pay for Electric Vehicles: An Analysis Using the Lens Model," SAGE Open, , vol. 15(2), pages 21582440251, May.
  • Handle: RePEc:sae:sagope:v:15:y:2025:i:2:p:21582440251335517
    DOI: 10.1177/21582440251335517
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/21582440251335517
    Download Restriction: no

    File URL: https://libkey.io/10.1177/21582440251335517?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
    ---><---

    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:sae:sagope:v:15:y:2025:i:2:p:21582440251335517. 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: SAGE Publications (email available below). General contact details of provider: .

    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.