Navigating generative AI use in tourism and hospitality: how trust and ethics shape human-machine information interaction of practitioners

Purpose This study aims to investigate how trust and ethics of generative AI (GenAI) could influence information seeking of practitioners, which is important for human–machine collaboration. Method Drawing from the social response theory, this study analyzes data from in-depth interviews with tourism account operators and hotel staff who use GenAI services to assist their work. Thematic analysis was used to systematically examine and interpret the interview data, enabling the identification of recurring patterns, themes and underlying meanings within participants’ responses. Findings The mind perception can facilitate employees’ technical trust, which in turn further facilitates their exploration willingness. And the sociotechnical concern can dampen employees’ technical trust, which should have facilitated their exploration willingness. The mind perception can facilitate employees’ ethical recognition of AI rights, whereas sociotechnical concerns tend to inhibit such recognition. Moreover, employees’ ethical recognition of AI rights can facilitate their exploration willingness. Originalities/values Beyond theory, the findings offer a practical roadmap for business leaders and AI developers to foster responsible AI adoption, balancing innovation with human-centric values. By bridging the gap between machine efficiency and human intuition, this study equips organizations to navigate the GenAI era, where trust, ethics and collaboration define success.

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Publication Details

Journal
Tourism Review
Published
2026-02-26
DOI
https://doi.org/10.1108/tr-07-2025-0740
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Navigating generative AI use in tourism and hospitality: how trust and ethics shape human-machine information interaction of practitioners

Beining Zhang, Bocong Yuan, Yujiu Liao, Hairong Zhao
Tourism Review
AI in Service Interactions
article

Navigating generative AI use in tourism and hospitality: how trust and ethics shape human-machine information interaction of practitioners

Beining Zhang, Bocong Yuan, Yujiu Liao, Hairong Zhao
article en

Abstract

Purpose This study aims to investigate how trust and ethics of generative AI (GenAI) could influence information seeking of practitioners, which is important for human–machine collaboration. Method Drawing from the social response theory, this study analyzes data from in-depth interviews with tourism account operators and hotel staff who use GenAI services to assist their work. Thematic analysis was used to systematically examine and interpret the interview data, enabling the identification of recurring patterns, themes and underlying meanings within participants’ responses. Findings The mind perception can facilitate employees’ technical trust, which in turn further facilitates their exploration willingness. And the sociotechnical concern can dampen employees’ technical trust, which should have facilitated their exploration willingness. The mind perception can facilitate employees’ ethical recognition of AI rights, whereas sociotechnical concerns tend to inhibit such recognition. Moreover, employees’ ethical recognition of AI rights can facilitate their exploration willingness. Originalities/values Beyond theory, the findings offer a practical roadmap for business leaders and AI developers to foster responsible AI adoption, balancing innovation with human-centric values. By bridging the gap between machine efficiency and human intuition, this study equips organizations to navigate the GenAI era, where trust, ethics and collaboration define success.

Tourism Review
Sun Yat-sen University (CN), University of Macau (MO)
Decent work and economic growth
Openalex Percentile: Top 45%
AI in Service Interactions
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