Extending the Technology Acceptance Model in AI-Driven Tourism Marketing: The Roles of Two-Way Communication, Personalization, and Co-Creation
DOI:
https://doi.org/10.56427/jcbd.v5i2.995
Keywords:
Algorithmic Empathy, Artificial Intelligence, Behavioral Economics, Digital Marketing, Socio-technical TransformationAbstract
This study extends the Technology Acceptance Model (TAM) to explain tourists' acceptance of AI-driven tourism marketing, which functions as an interactive, personalized, and participatory interface supporting destination search, recommendation, itinerary design, and engagement. Drawing on an extended TAM, this study examines the effects of perceived two-way communication, perceived personalization, and perceived co-creation on perceived usefulness, attitude, and tourist behavioral intention. A quantitative survey of 420 tourists who had interacted with AI-supported tourism platforms was analyzed using PLS-SEM. The measurement model demonstrated satisfactory reliability and validity, with outer loadings ranging from 0.724 to 0.891, Cronbach's alpha from 0.837 to 0.902, composite reliability from 0.885 to 0.928, and AVE from 0.606 to 0.721. The structural model revealed that two-way communication, personalization, and co-creation significantly influenced perceived usefulness and attitude, while attitude emerged as the strongest predictor of behavioral intention. The model demonstrated acceptable fit (SRMR = 0.057; NFI = 0.912) and explained 68.4% of the variance in tourist behavioral intention. The findings suggest that tourists accept AI-driven tourism marketing not only because it is useful and easy to use, but also because it enables responsive communication, relevant recommendations, and meaningful participation in travel experience design.
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[1] D. Gursoy, C. Li, and C. Song, 'ChatGPT and the hospitality and tourism industry: an overview of current trends and future research directions,' Journal of Hospitality Marketing & Management, vol. 32, no. 5, pp. 579-592, 2023, doi: 10.1080/19368623.2023.2211993.
[2] I. A. Wong, Q. L. Lian, and D. Sun, 'Autonomous travel decision-making: An early glimpse into ChatGPT and generative AI,' Journal of Hospitality and Tourism Management, vol. 56, pp. 253-263, 2023, doi: 10.1016/j.jhtm.2023.06.022.
[3] I. Carvalho and S. Ivanov, 'ChatGPT for tourism: applications, benefits and risks,' Tourism Review, vol. 79, no. 2, pp. 290-303, 2024, doi: 10.1108/TR-02-2023-0088.
[4] M. Sigala et al., 'Understanding the impact of ChatGPT on tourism and hospitality: Trends, prospects and research agenda,' Journal of Hospitality and Tourism Management, vol. 60, pp. 384-400, 2024, doi: 10.1016/j.jhtm.2024.08.004.
[5] F. D. Davis, 'Perceived usefulness, perceived ease of use, and user acceptance of information technology,' MIS Quarterly, vol. 13, no. 3, pp. 319-340, 1989, doi: 10.2307/249008.
[6] V. Venkatesh and F. D. Davis, 'A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies,' Management Science, vol. 46, no. 2, pp. 186-204, 2000, doi: 10.1287/mnsc.46.2.186.11926.
[7] U. Gretzel, M. Sigala, Z. Xiang, and C. Koo, 'Smart tourism: foundations and developments,' Electronic Markets, vol. 25, no. 3, pp. 179-188, 2015, doi: 10.1007/s12525-015-0196-8.
[8] D. Buhalis and A. Amaranggana, 'Smart tourism destinations enhancing tourism experience through personalisation of services,' in Information and Communication Technologies in Tourism 2015, Cham: Springer, 2015, pp. 377-389, doi: 10.1007/978-3-319-14343-9_28.
[9] M. Tussyadiah, 'A review of research into automation in tourism: Launching the Annals of Tourism Research curated collection on artificial intelligence and robotics in tourism,' Annals of Tourism Research, vol. 81, 102883, 2020, doi: 10.1016/j.annals.2020.102883.
[10] B. Gao and L. Huang, 'Understanding interactive user behavior in smart media content service: An integration of TAM and smart service belief factors,' Heliyon, vol. 5, no. 12, e02983, 2019, doi: 10.1016/j.heliyon.2019.e02983.
[11] A. Chen et al., 'TravelAgent: An AI assistant for personalized travel planning,' arXiv preprint arXiv:2409.08069, 2024, doi: 10.48550/arXiv.2409.08069.
[12] L. Mich and R. Garigliano, 'ChatGPT for e-Tourism: a technological perspective,' Information Technology & Tourism, vol. 25, no. 1, pp. 1-12, 2023, doi: 10.1007/s40558-023-00248-x.
[13] K. Otaki, T. Kurashima, and T. Toda, 'Travel itinerary recommendation using interaction-based preference elicitation,' Expert Systems with Applications, vol. 259, 125271, 2025, doi: 10.1016/j.eswa.2024.125271.
[14] S. Seyfi, M. J. Kim, A. Nazifi, S. Murdy, and T. Vo-Thanh, 'Understanding tourist barriers and personality influences in embracing generative AI for travel planning and decision-making,' International Journal of Hospitality Management, vol. 126, 104105, 2025, doi: 10.1016/j.ijhm.2025.104105.
[15] C. K. Prahalad and V. Ramaswamy, 'Co-creation experiences: The next practice in value creation,' Journal of Interactive Marketing, vol. 18, no. 3, pp. 5-14, 2004, doi: 10.1002/dir.20015.
[16] M. Neuhofer, D. Buhalis, and A. Ladkin, 'Smart technologies for personalized experiences: a case study in the hospitality domain,' Electronic Markets, vol. 25, pp. 243-254, 2015, doi: 10.1007/s12525-015-0182-1.
[17] T. Araujo, N. Helberger, S. Kruikemeier, and C. H. de Vreese, 'In AI we trust? Perceptions about automated decision-making by artificial intelligence,' AI & Society, vol. 35, pp. 611-623, 2020, doi: 10.1007/s00146-019-00931-w.
[18] C. Fornell and D. F. Larcker, 'Evaluating structural equation models with unobservable variables and measurement error,' Journal of Marketing Research, vol. 18, no. 1, pp. 39-50, 1981, doi: 10.1177/002224378101800104.
[19] J. F. Hair, G. T. M. Hult, C. M. Ringle, and M. Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 3rd ed. Thousand Oaks, CA: Sage, 2022.
[20] P. Guenther, M. Guenther, C. Ringle, G. Zaefarian, and S. Cartwright, 'Improving PLS-SEM use for business marketing research,' Industrial Marketing Management, vol. 111, pp. 127-142, 2023, doi: 10.1016/j.indmarman.2023.03.012.
[21] D. Buhalis and R. Law, 'Progress in information technology and tourism management: 20 years on and 10 years after the Internet,' Tourism Management, vol. 29, no. 4, pp. 609-623, 2008, doi: 10.1016/j.tourman.2008.01.005.
[22] Z. Xiang, V. P. Magnini, and D. R. Fesenmaier, 'Information technology and consumer behavior in travel and tourism: insights from travel planning using the internet,' Journal of Retailing and Consumer Services, vol. 22, pp. 244-249, 2015, doi: 10.1016/j.jretconser.2014.08.005.
[23] C. Koo, F. Ricci, C. Cobanoglu, and F. Okumus, 'Special issue on smart, connected hospitality and tourism,' Information Systems Frontiers, vol. 19, no. 4, pp. 699-703, 2017, doi: 10.1007/s10796-017-9776-9.
[24] H. Harkim, 'Digital business and artificial intelligence,' Golden Ratio of Data in Summary, vol. 5, no. 1, pp. 1-12, 2025, doi: 10.52970/grdis.v5i1.1424.
[25] H. S. N. Hadi, 'The impact of artificial intelligence on healthcare: A systematic review of innovations, challenges, and ethical considerations,' Journal of Computers and Digital Business, vol. 4, no. 1, pp. 1-9, 2025, doi: 10.56427/jcbd.v4i1.601.
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