How control allocation in AI-enabled travel planning shapes reuse intention: the roles of user experience, emotion regulation and psychological empowerment
Purpose This study examines how control allocation between users and artificial intelligence (AI) systems shapes reuse intention in AI-enabled travel planning and whether this effect operates through user experience (UX), cognitive reappraisal, expressive suppression, psychological empowerment and satisfaction. Design/methodology/approach Two scenario-based studies were conducted. A laboratory pilot (n = 92) validated system-dominant, shared-control and user-dominant planning conditions. A main online study (n = 463) tested the proposed serial process using confirmatory factor analysis, structural equation modeling and 5,000-resample bootstrapping. Findings Control allocation significantly affected UX. More favorable UX increased cognitive reappraisal and reduced expressive suppression, and these two regulatory routes had opposite effects on psychological empowerment. Empowerment enhanced satisfaction, which subsequently predicted reuse intention. A supplementary analysis further indicated that AI usage experience conditioned the relationships between UX and emotion regulation. Practical implications AI travel planners should treat control allocation as an interaction-design decision. Modular editing, progressive explanations, reversible changes and adaptive control can preserve user agency while retaining the efficiency benefits of AI assistance. Originality/value This study extends continuance research by identifying the upstream psychological process through which satisfaction is formed under different control-allocation structures. It further distinguishes UX as an evaluative appraisal from emotion regulation as a subsequent coping process in AI-enabled travel planning.
Authors
- Xiaojie Zhu (ORCID: https://orcid.org/0009-0009-5075-2474)
- Xiaoyan Hao (ORCID: https://orcid.org/0009-0004-1188-7054)
- Ying Wang (ORCID: https://orcid.org/0009-0008-5295-1162)
- Xiaofeng Wang
Institutions
- Huanghuai University (CN)
- Shandong University of Art and Design (CN)
- Yeungnam University (KR)
Publication Details
- Journal
- Journal of Hospitality and Tourism Insights
- Published
- 2026-10-27
- DOI
- https://doi.org/10.1108/jhti-02-2026-0221
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00