IDEAS home Printed from https://ideas.repec.org/h/spr/prbchp/978-3-032-24745-2_20.html

The Effects of Artificial Intelligence and Cognitive Dissonance on Tourist Decisions Across Vietnam

In: Vietnamese Business and Sustainable Development in a Globalized and Digitalized Era

Author

Listed:
  • Ngan Nguyen Hoang Thanh

    (National Kaohsiung University of Science and Technology, Department of Tourism Management, School of Business Intelligence)

  • Le Nguyen Ngoc Thanh

    (Tomas Bata University in Zlín, Department of Management, Faculty of Management and Economics)

  • Vo Hong Son

    (Tomas Bata University in Zlín, Department of Management, Faculty of Management and Economics)

Abstract

ABSTRACT Artificial Intelligence (AI’s) progression in tourism enhances travel experiences through optimized decision-making. The integration of AI raises privacy and trust concerns due to data requirements. This study examines AI’s impact on tourist decisions through Cognitive Dissonance Theory, which explains discomfort from conflicting cognitions between personalisation desires and privacy concerns. Using structural equation modelling, the study tested relationships between AI benefits, privacy concerns, trust, cognitive dissonance, and AI recommendation adoption. Data from AI travel tool users showed robust model fit (CFI = 0.975, RMSEA = 0.035). Privacy concerns increased cognitive dissonance, reducing AI recommendation adoption. Perceived benefits influenced adoption through positive attitudes, while trust supported usage intentions. These findings suggest providers can improve AI tourism services by enhancing trust measures and data transparency.

Suggested Citation

  • Ngan Nguyen Hoang Thanh & Le Nguyen Ngoc Thanh & Vo Hong Son, 2026. "The Effects of Artificial Intelligence and Cognitive Dissonance on Tourist Decisions Across Vietnam," Springer Proceedings in Business and Economics, in: Zafar U. Ahmed & Nhat Tan Pham (ed.), Vietnamese Business and Sustainable Development in a Globalized and Digitalized Era, pages 376-398, Springer.
    • Handle: RePEc:spr:prbchp:978-3-032-24745-2_20
    DOI: 10.1007/978-3-032-24745-2_20
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:prbchp:978-3-032-24745-2_20. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.