Although the integration of Artificial Intelligence (AI) in tourism has grown exponentially, the existing literature is heavily skewed towards a consumer-centric perspective, leaving the determinants of adoption at the firm level underexplored. To address this gap, this study investigates the factors influencing behavioral intention to adopt AI among travel agents in Batam, Indonesia, using the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. A cross-sectoral quantitative survey was conducted with N = 239 respondents across licensed travel agents, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Empirical findings indicate that Effort Expectancy, Performance Expectancy, and Enabling Conditions all have a positive and statistically significant impact on adoption intention. Notably, Enabling Conditions emerged as the most dominant predictor, as AI integration relies on existing underlying infrastructure rather than capital-intensive technology investments. Overall, the model explains 55.0% of the variance in adoption intention (R² = 0.550). Theoretically, this study validates UTAUT in the context of organizational tourism, while practically offering actionable insights for AI developers and travel agency managers to leverage fundamental digital assets for competitive advantage.
Agapitou, C., Sabazioti, A., Bouchoris, P., Folina, M., Folinas, D., & Tsaramiadis, G. (2025). How Can Chatbots Help Companies to Improve the Customer Experience Offered to Their End Users / Customers in the Tourism Industry?? Tourism and Hospitality, 1–22. https://doi.org/https:// doi.org/10.3390/tourhosp6040207
Biloš, A., & Budimir, B. (2024). Understanding the Adoption Dynamics of ChatGPT among Generation Z: Insights from a Modified UTAUT2 Model. Journal of Theoretical and Applied Electronic Commerce Research , 19(2), 863–879. https://doi.org/10.3390/jtaer19020045
Changalima, I. A., & Chuwa, M. P. (2025). Partial least squares structural equation modeling (PLS-SEM) in business research: A simple guide for novice researchers. INTERNATIONAL JOURNAL OF RESEARCH IN BUSINESS AND SOCIAL SCIENCE 14(9), 14(9), 497–506.
Chen, Y.-K., Chiu, F.-R., & Huang, T.-L. (2025). Travelers ’ intentions to adopt travel AI chatbot services?: an integrated multi- theory and multi-method analysis. Journal of Hospitality and Tourism Technology. https://doi.org/10.1108/JHTT-01-2025-0050
Do?an, S., & Niyet, ?. Z. (2024). Artificial Intelligence (AI) in Tourism. In C. Tanrisever, H. Pamukçu, & A. Sharma (Eds.), Future Tourism Trends Volume 2: Technology Advancement, Trends and Innovations for the Future in Tourism (p. 0). Emerald Publishing Limited. https://doi.org/10.1108/978-1-83753-970-320241001
Dwivedi, Y. K., Pandey, N., Currie, W., & Micu, A. (2023). Leveraging ChatGPT and other generative arti fi cial intelligence ( AI ) -based applications in the hospitality and tourism industry?: practices , challenges and research agenda. International Journal of Contemporary Hospitality Management, 36(1), 1–12. https://doi.org/10.1108/IJCHM-05-2023-0686
Fahlevi, R., Purwianti, L., Riyadi, A., & Arafah, W. (2025). Drivers of Artificial Intelligence ( AI ) Adoption in Tourism Companies?: An Empirical Study of Technology Acceptance Model ( TAM ) Theory. KNE Publishing, 115–124. https://doi.org/10.18502/kss.v10i29.20257
Fararni, K. A. L., Nafis, F., Aghoutane, B., Yahyaouy, A., & Riffi, J. (2021). Hybrid Recommender System for Tourism Based on Big Data and AI?: A Conceptual Framework. Big Data Mining and Analytics, 4(1), 47–55. https://doi.org/10.26599/BDMA.2020.9020015
Filrando, A., Fahlevi, R., & Sinambela, F. A. (2026). Exploring the Factors Influencing User Attitudes and AI Chatbot Use in the Tourism Sector: Evidence from Indonesia. Journal of Enterprise and Development (JED), 8(1), 70–83. https://doi.org/https://doi.org/10.20414/jed.v8i1.14881
Gaji?, T., Vukoli?, D., Bugar?i?, J., ?okovi?, F., Spasojevi?, A., Kneževi?, S., ?or?evi? Boljanovi?, J., Gliši?, S., Matovi?, S., & Dávid, L. D. (2024). The Adoption of Artificial Intelligence in Serbian Hospitality: A Potential Path to Sustainable Practice. Sustainability (Switzerland) , 16(8). https://doi.org/10.3390/su16083172
Hair, J. F., Black, W. C., Babin, B. J., &, & Anderson, R. E. (2019). Multivariate data analysis(8th ed.).
Law, R., Lin, K. J., Ye, H., Ka, D., & Fong, C. (2024). Artificial intelligence research in hospitality: a state-of-the-art review and future directions. International Journal of Contemporary Hospitality Management, 36(6), 2049–2068. https://doi.org/10.1108/IJCHM-02-2023-0189
Machucho, R., & David Ortiz. (2025). The Impacts of Artificial Intelligence on Business Innovation: A Comprehensive Review of Applications, Organizational Challenges, and Ethical Considerations. Systems, 1–35. https://doi.org/https://doi.org/10.3390/ systems13040264
Pillai, R., & Sivathanu, B. (2020). Adoption of AI-based chatbots for hospitality and tourism. International Journal of Contemporary Hospitality Management, 32(10), 3199–3226. https://doi.org/10.1108/IJCHM-04-2020-0259
Sebastián, M. G. de B., José Ramón Sarmiento Guede, & Antonovica, A. (2022). Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants. Frontiers in Psychology. https://doi.org/doi: 10.3389/fpsyg.2022.993935
Sentoso, A., Sibarani, T. P., Muchsinati, E. S., Pasar, O., & Teknologi, O. (2024). Business Performance of MSMEs?: an Analysis of the Effect of Entrepreneurial Orientation , Market Orientation , and Technology Orientation. 15(85), 318–333.
Shi, J., Lee, M., Girish, V. G., Xiao, G., & Lee, C. K. (2024). Embracing the ChatGPT revolution: unlocking new horizons for tourism. Journal of Hospitality and Tourism Technology, 15(3), 433–448. https://doi.org/10.1108/JHTT-07-2023-0203
Sukthankar, S., Fernandes, R., Gaonkar, S., & Shetye, A. (2026). Unveiling the Determinants of Tourists ’ Behavioural Intention to Adopt AI-Powered Chatbots for the Hospitality and Tourism Industry?: Revising the UTAUT2 Model. Tourism and Hospitality, 1–29. https://doi.org/https://doi.org/10.3390/tourhosp7030065
Tussyadiah, I. (2020). Annals of Tourism Research A review of research into automation in tourism?: Launching the Annals of Tourism Research Curated Collection on Arti fi cial Intelligence and Robotics in Tourism. Annals of Tourism Research, 81. https://doi.org/10.1016/j.annals.2020.102883
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. Management Information Systems Research Center, University of Minnesota, 27(3), 425–478. https://www.jstor.org/stable/30036540
Vicente-Martínez, P., Soria-Olivas, E., Esteve-Mompó, I., Sánchez-Montañés, M., Escrivà, M. Á. G., & Edu William-Secin. (2026). Design and Evaluation of an AI-Based Conversational Agent for Travel Agencies?: Enhancing Training , Assistance , and Operational Efficiency. AI. https://doi.org/https://doi.org/10.3390/ai7040123
Xian, X. (2021). Psychological Factors in Consumer Acceptance of Artificial Intelligence in Leisure Economy?: A Structural Equation Model. Psychological Factors in Consumer Acceptance of Artificial Intelligence in Leisure Economy: A Structural Equation Model, 697–706. https://doi.org/10.3966/160792642021052203018
Zhang, B., Zhu, Y., Deng, J., Zheng, W., Liu, Y., Wang, C., & Zeng, R. (2023). “I Am Here to Assist Your Tourism”: Predicting Continuance Intention to Use AI-based Chatbots for Tourism. Does Gender Really Matter? International Journal of Human-Computer Interaction, 39(9), 1887–1903. https://doi.org/10.1080/10447318.2022.2124345
Fahlevi, R., Sinambela, F. A., Riyadi, A., & Augris, E. (2026). Determinants of Artificial Intelligence Adoption in Tourism Corporations: An Empirical Study of Travel Agents Using the UTAUT Model. International Journal of Academic Research in Business and Social Sciences, 16(8), 674–686.
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