IDEAS home Printed from https://ideas.repec.org/a/taf/rcitxx/v28y2025i4p604-621.html
   My bibliography  Save this article

Tourists’ pro-environmental behaviour in an autonomous vehicle’s adoption: aligning the integration of value-belief-norm theory and the theory of planned behaviour

Author

Listed:
  • Salman Khan
  • Qingyu Zhang
  • Ikram Ullah Khan
  • Safeer Ullah Khan
  • Shafaqat Mehmood

Abstract

Automated vehicles powered by artificial intelligence (AI) represent some of the most disruptive technologies with broad social implications, including increasing safety for travelers and drivers, protecting the environment, and upholding equity. This study aims to develop a unified conceptual framework combining the value-belief-norm (VBN) theory with the theory of planned behaviour (TPB) to understand how tourists accept autonomous vehicles. The PLS-SEM results of 586 tourists’ data show that altruistic and biospheric values positively affect the awareness of consequences, whereas egoistic values negatively affect it. Moreover, the findings of this study validate the suggested relationships between value-based constructs, including awareness of consequences, ascription of responsibility, and pro-environmental personal norms. The relationship between behavioural intention and pro-environmental personal norms was confirmed by attitudes toward behaviour, subjective norms, and perceived behavioural control. This study offers theoretical and practical implications that enhance the likelihood of travelers’ acceptance of autonomous vehicles.

Suggested Citation

  • Salman Khan & Qingyu Zhang & Ikram Ullah Khan & Safeer Ullah Khan & Shafaqat Mehmood, 2025. "Tourists’ pro-environmental behaviour in an autonomous vehicle’s adoption: aligning the integration of value-belief-norm theory and the theory of planned behaviour," Current Issues in Tourism, Taylor & Francis Journals, vol. 28(4), pages 604-621, February.
  • Handle: RePEc:taf:rcitxx:v:28:y:2025:i:4:p:604-621
    DOI: 10.1080/13683500.2024.2325491
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/13683500.2024.2325491
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/13683500.2024.2325491?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.

    More about this item

    Statistics

    Access and download statistics

    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:taf:rcitxx:v:28:y:2025:i:4:p:604-621. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/rcit .

    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.