IDEAS home Printed from https://ideas.repec.org/h/spr/prbchp/978-3-032-23925-9_24.html

Understanding AI Adoption in Tourism: Extending UTAUT2 with Trust

In: Information and Communication Technologies in Tourism 2026

Author

Listed:
  • Bendjedid Rachad Sanoussi

    (Euromed University of Fes (UEMF), Euromed Business School (EBS))

  • Omar Benjelloun Andaloussi

    (Euromed University of Fes (UEMF), Euromed Business School (EBS))

  • Mohamed Amine Marhraoui

    (Euromed University of Fes (UEMF), Euromed Business School (EBS))

Abstract

This study investigates tourists’ adoption and use of artificial intelligence tools in tourism based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). The analysis focuses on tourists visiting Fès, Morocco, where AI is defined as a conversational assistant used for information search, trip planning, and decision support. Using survey data analysed through PLS-SEM, the study examines the effects of UTAUT2 constructs on behavioural intention and usage behaviour, as well as the role of trust in AI technology. The results show that performance expectancy, hedonic motivation, price value, and habit significantly influence intention to use AI, while facilitating conditions and habit directly affect usage behaviour. Effort expectancy and social influence are not significant. Trust in AI technology does not moderate the intention–usage relationship. The findings extend UTAUT2 to conversational AI in tourism and provide practical insights for AI-based service design.

Suggested Citation

  • Bendjedid Rachad Sanoussi & Omar Benjelloun Andaloussi & Mohamed Amine Marhraoui, 2026. "Understanding AI Adoption in Tourism: Extending UTAUT2 with Trust," Springer Proceedings in Business and Economics, in: Peter O'Connor & Mattia Rainoldi & Julia Neidhardt (ed.), Information and Communication Technologies in Tourism 2026, chapter 24, pages 351-363, Springer.
    • Handle: RePEc:spr:prbchp:978-3-032-23925-9_24
    DOI: 10.1007/978-3-032-23925-9_24
    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

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    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:978-3-032-23925-9_24. 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.