What Drives Tourists to Use Conversational AI? Evidence from an Extended UTAUT2 Model

  • Bendjedid Rachad Sanoussi Euromed Business School (EBS), Euromed University of Fes (UEMF), Fes, Morocco
  • Omar Benjelloun Andaloussi Euromed Business School (EBS), Euromed University of Fes (UEMF), Fes, Morocco
  • Mohamed Amine Marhraoui Euromed Business School (EBS), Euromed University of Fes (UEMF), Fes, Morocco
DOI: https://doi.org/10.19139/soic-2310-5070-3365
Keywords: AI adoption, tourism, UTAUT2, trust, behavioural intention, usage behaviour, conversational agents, ChatGPT-like assistants

Abstract

This study examines the factors shaping tourists’ adoption and use of artificial intelligence (AI) tools in tourism by drawing on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Focusing on tourists visiting Fes, Morocco, AI is operationalised as a conversational assistant similar to ChatGPT that helps travellers search for information, plan itineraries, and make decisions during their trip. The research investigates how performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit influence behavioural intention and usage behaviour, and whether trust in AI technology moderates the intention–behaviour link. Data were collected through an online survey of N=183 tourists in Fes, Morocco. Respondents completed a screening question on prior use of a ChatGPT-like assistant for travel tasks. Only “Yes” respondents proceeded. Usage behavior reflects general self-reported use of AI for travel purposes, not verified frequency of use during the Fes stay. The collected data was then analyzed using a consistent “partial least squares” (PLS) SEM technique. The findings show that performance expectancy, hedonic motivation, price value, and habit significantly predict behavioural intention. Facilitating conditions and habit significantly predict usage behaviour. Effort expectancy and social influence are non-significant predictors of intention. Trust in AI technology does not significantly moderate the relationship between intention and usage behaviour. The study contributes to tourism technology literature by refining the application of UTAUT2 in an AI-intensive context and highlighting the role of habit and perceived value in tourists’ continued reliance on AI assistants. Practical implications are discussed for tourism managers and destination stakeholders seeking to design and communicate trustworthy AI-based services.

Author Biographies

Omar Benjelloun Andaloussi, Euromed Business School (EBS), Euromed University of Fes (UEMF), Fes, Morocco
Prof Omar Benjelloun Andaloussi, Ph.D is an Assistant Professor of Digital Marketing at Euromed University of Fez, Morocco. Prior to this appointment, he served as a teacher and educational manager at HEM Business School in Fez. A native of Fez, Dr. Benjelloun Andaloussi earned his Ph.D. in Management Sciences, specializing in digital marketing, from Sidi Mohamed Ben Abdallah University in Fez. His research focuses on customer experience and artificial intelligence, and he has a strong publication record in these areas, including articles in Scopus and Web of Science indexed journals, contributions to collective works, and presentations at international conferences. He is regularly solicited by Scopus and Web of Science indexed journals to serve as a peer reviewer, reflecting his expertise in the field. Dr. Benjelloun Andaloussi leads two specialized master's programs: "Marketing and Business Development" and "Digital Marketing and Data Analytics." Currently, he is directing a research project funded by the Moroccan Ministry of Higher Education titled, "The Promotion of 'Made in Morocco' as Part of the New Import-Substitution Industrial Strategy."
Mohamed Amine Marhraoui , Euromed Business School (EBS), Euromed University of Fes (UEMF), Fes, Morocco
Prof Mohamed Amine Marhraoui is a Professor Researcher at Euromed Business School, Euromed University of Fes. His research interests encompass the impact of Information Technology on firm’s organizational agility and the mediating role of agility in enhancing enterprise’s performance. Moreover, Pr Marhraoui studies the impacts of digital competences especially for project managers. Pr Marhraoui has graduated from ENSEIRB (Telecommunications, National School of electronics, computer and telecommunications of Bordeaux, France, 2007) and obtained an MSc in Commercial Engineering and Project Management from INSEEC Business School (Paris, France, 2011). Pr Marhraoui has obtained his Phd from ENSIAS (National Higher School for Computer Science and System Analysis) Rabat Mohammed V University, Morocco within TIME Laboratory (Information Technology and Management). Pr Marhraoui has published articles in highly recognized peer-reviewed and has participated in high ranked international conferences. Pr Marhraoui strives to transfer academic knowledge to socioeconomic actors through case studies and regular media outreach. He is a certified Scrum Master and project management professional (PMP) from the PMI (Project Management Institute). Moreover, Pr Marhraoui has worked for fifteen years as a consultant in Information Technology management, organization and project management in different sectors (energy, industry and banking).
Published
2026-03-19
How to Cite
Sanoussi, B. R., Benjelloun Andaloussi, O., & Marhraoui , M. A. (2026). What Drives Tourists to Use Conversational AI? Evidence from an Extended UTAUT2 Model. Statistics, Optimization & Information Computing. https://doi.org/10.19139/soic-2310-5070-3365
Issue
Online First
Section
Research Articles
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