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Research Article

Understanding Tourist Booking Intention in the Generative AI Era: Integrating AI-Generated Information, Trust, and the TAM-SOR Framework

Authors

  • Bao Tan Vo Master of Science, South East Technological University, Ireland

Abstract

This study examines tourist booking intention in the generative artificial intelligence (GenAI) era by integrating the Technology Acceptance Model (TAM) and the Stimulus-Organism-Response (S-O-R) framework. Using a quantitative research design, data were collected from 438 tourists who had used GenAI for tourism-related information search and planning. The proposed model investigates the relationships among AI-generated information, perceived usefulness, trust in AI-generated content, and tourist booking intention. The findings indicate that respondents reported high perceptions of AI-generated information (M = 4.21, SD = 0.721), perceived usefulness (M = 4.38, SD = 0.654), trust (M = 4.12, SD = 0.781), and booking intention (M = 4.18, SD = 0.748). PLS-SEM results indicate that AI-generated information significantly influences perceived usefulness and trust, while trust has a stronger direct effect on booking intention than perceived usefulness. Mediation results further indicate that perceived usefulness and trust transmit the influence of AI-generated information on booking intention. The model explains 62.1% of the variance in booking intention.

Article information

Journal

Journal of Business and Management Studies

Volume (Issue)

8 (10)

Pages

01-13

Published

2026-10-02

How to Cite

Bao Tan Vo. (2026). Understanding Tourist Booking Intention in the Generative AI Era: Integrating AI-Generated Information, Trust, and the TAM-SOR Framework. Journal of Business and Management Studies, 8(10), 01-13. https://doi.org/10.32996/jbms.2026.8.10.1

References

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Keywords:

Generative AI, Tourist Booking Intention, Trust in AI-Generated Content, Technology Acceptance Model.