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References
1.
Akdim, K. (2021). The influence of eWOM. Analyzing its characteristics and consequences, and future research lines. Spanish Journal of Marketing - ESIC, 25(2), 239-259. https://doi.org/10.1108/SJME-10-2020-0186.
2.
Ali, F., Yasar, B., Ali, L., & Dogan, S. (2023). Antecedents and consequences of travelers’ trust towards personalized travel recommendations offered by ChatGPT. International Journal of Hospitality Management, 114, 103588. https://doi.org/10.1016/j.ijhm.2023.103588.
3.
Booking.com. (2025). Booking.com Releases The Global AI Sentiment Report. https://news.booking.com/bookingcom-releases-the-global-ai-sentiment-report.
4.
Chen, Y., Kanchanapoom, K., & Deeprasert, J. (2026). Understanding the drivers of intention to adopt AI-based conversational recommendation systems for travel planning. Discover Artificial Intelligence. https://doi.org/10.1007/s44163-026-01352-7.
5.
Chi, O. H., Gursoy, D., & Chi, C. G. (2022). Tourists’ Attitudes toward the Use of Artificially Intelligent (AI) Devices in Tourism Service Delivery: Moderating Role of Service Value Seeking. Journal of Travel Research, 61(1), 170-185. https://doi.org/10.1177/0047287520971054.
6.
Connelly, B. L., Certo, S. T., Ireland, R. D., & Reutzel, C. R. (2011). Signaling Theory: A Review and Assessment. Journal of Management, 37(1), 39-67. https://doi.org/10.1177/0149206310388419
7.
Đặng Thị Thu, T., & Trần Hoàng Bảo, L. (2025). Khám phá mối quan hệ giữa mua sắm ngẫu hứng, cảm nhận hạnh phúc, niềm tin và ý định mua lại của người tiêu dùng trong thương mại trên nền tảng xã hội: trường hợp người tiêu dùng gen Z tại Việt Nam. Tạp chí Khoa học Thương mại, 98-116. https://doi.org/10.54404/JTS.2025.198V.06.
8.
Dat, N. Van, & Tho, N. Van. (2025). Shaping the itinerary: Perceived quality of recommendation systems on travel intentions. A case study in Vietnam. Edelweiss Applied Science and Technology, 9(1), 945-959. https://doi.org/10.55214/25768484.v9i1.4291.
9.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008..
10.
Erickson, T., & Kellogg, W. A. (2000). Social translucence: an approach to designing systems that support social processes. ACM Transactions on Computer-Human Interaction, 7(1), 59-83. https://doi.org/10.1145/344949.345004.
11.
Expedia Group. (2025). Travel Priorities Reinvented: Expedia Group’s 2025 Traveler Value Index Signals a Shift in Consumer Priorities. https://ir.expediagroup.com/news-and-events/news/news-details/2025/Travel-Priorities-Reinvented-Expedia-Groups-2025-Traveler-Value-Index-Signals-a-Shift-in-Consumer-Priorities/.
12.
Ghahramani, Z. (2015). Probabilistic machine learning and artificial intelligence. Nature, 521(7553), 452-459. https://doi.org/10.1038/nature14541.
13.
Ghorbanzadeh, D., Sayed, B. T., Alhitmi, H. K., Hasan, R. A., Aldulaimi, M. H., & Prasad, K. (2025). Applying UTAUT and experiential consumption theory to understand the adoption of ChatGPT’s digitalized itinerary. Journal of Hospitality and Tourism Insights, 8(9), 3339-3358. https://doi.org/10.1108/JHTI-02-2025-0300.
14.
Greg Schulze. (2025). 2025 Traveler Value Index highlights. https://partner.expediagroup.com/en-us/resources/blog/2025-traveler-value-index-highlights.
15.
Hùng Cường, P., Xuân Minh, N., & Thị Hương, T. (2025). Tác động của thông tin đánh giá trực tuyến đến quyết định mua hàng tiêu dùng nhanh trên các sàn thương mại điện tử của Gen Z tại Thành phố Hồ Chí Minh. Tạp chí Khoa học Thương mại, 47-64. https://doi.org/10.54404/JTS.2025.205V.04.
16.
Ismagilova, E., Dwivedi, Y. K., & Slade, E. (2020). Perceived helpfulness of eWOM: Emotions, fairness and rationality. Journal of Retailing and Consumer Services, 53, 101748. https://doi.org/10.1016/j.jretconser.2019.02.002.
17.
Li, S., Han, R., Fu, T., Chen, M., & Zhang, Y. (2025). Tourists’ behavioural intentions to use ChatGPT for tour route planning: an extended TAM model including rational and emotional factors. Current Issues in Tourism, 28(13), 2119-2135. https://doi.org/10.1080/13683500.2024.2355563.
18.
Omran, W., Casais, B., & Ramos, R. F. (2025). Attributes of Virtual and Augmented Reality Tourism Mobile Applications Predicting Tourist Behavioral Engagement. International Journal of Human-Computer Interaction, 41(21), 13335-13348. https://doi.org/10.1080/10447318.2025.2470293.
19.
Orden-Mejía, M., Carvache-Franco, M., Huertas, A., Carvache-Franco, O., & Carvache-Franco, W. (2025a). Analysing how AI-powered chatbots influence destination decisions. PLOS ONE, 20(3), e0319463. https://doi.org/10.1371/journal.pone.0319463.
20.
Orden-Mejía, M., Carvache-Franco, M., Huertas, A., Carvache-Franco, O., & Carvache-Franco, W. (2025b). The Role of AI-Based Destination Chatbots in Satisfaction, Continued Usage Intention, and Visit Intention: A Study from Quito, Ecuador. International Journal of Human-Computer Interaction, 41(15), 9384-9399. https://doi.org/10.1080/10447318.2024.2425882.
21.
Sâsâeac, Ștefania M., Bertea, P. E., Jelea, A. R., Manolică, A., & Roman, C. T. (2025). eWOM vs. aWOM: AI Powered Word of Mouth and its Impact on Consumer Decision Making in Tourism. Scientific Annals of Economics and Business, 72(3), 489-517. https://doi.org/10.47743/saeb-2025-0026.
22.
Spence, M. (1973). Job Market Signaling. The Quarterly Journal of Economics, 87(3), 355. https://doi.org/10.2307/1882010.
23.
Suasapha, A. H. (2025). Will Generation Z Use ChatGPT for Tourism Recommendations? Tourism and Hospitality Management, 31(3), 483-491. https://doi.org/10.20867/thm.31.3.11.
24.
Tedjakusuma, A. P., Liu, L.-W., Eunike, I. J., & Silalahi, A. D. K. (2025). Rethinking Information Quality: How Trust in ChatGPT Shapes Destination Visit Intentions. Tourism and Hospitality, 6(4), 178. https://doi.org/10.3390/tourhosp6040178.
25.
Topsakal, Y. (2025). How Familiarity, Ease of Use, Usefulness, and Trust Influence the Acceptance of Generative Artificial Intelligence (AI)-Assisted Travel Planning. International Journal of Human-Computer Interaction, 41(15), 9478-9491. https://doi.org/10.1080/10447318.2024.2426044.
26.
Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926.
27.
Vu Thi Thuy Hang, & Nguyen Thi Van. (2024). Factors influencing social media addiction among Vietnamese adolescents. VNU University of Economics and Business, 4(6), 104. https://doi.org/10.57110/vnu-jeb.v4i6.354.
28.
Wang, Y., & Rodgers, S. (2010). Electronic word of mouth and consumer generated content: From concept to application. In Handbook of Research on Digital Media and Advertising: User Generated Content Consumption (pp. 212-231). https://doi.org/10.4018/978-1-60566-792-8.ch011.
29.
Williams, N. L., Ferdinand, N., & Bustard, J. (2020). From WOM to aWOM - the evolution of unpaid influence: a perspective article. Tourism Review, 75(1), 314-318. https://doi.org/10.1108/TR-05-2019-0171.
30.
Xu, H., Law, R., Lovett, J., Luo, J. M., & Liu, L. (2024). Tourist acceptance of ChatGPT in travel services: the mediating role of parasocial interaction. Journal of Travel & Tourism Marketing, 41(7), 955-972. https://doi.org/10.1080/10548408.2024.2364336.
31.
Yan, S., Yu, X., Zhang, Z., & Gan, L. (2024). Understanding the acceptance of online tourism programs: Perspectives of generic learning outcomes and theory of planned behavior. Heliyon, 10(15), e35500. https://doi.org/10.1016/j.heliyon.2024.e35500.
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