Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/114092
Title: Generative artificial intelligence in tourism management : an integrative review and roadmap for future research
Authors: Li, H 
Xi, J 
Hsu, CHC 
Yu, BXB
Zheng, XK 
Issue Date: Oct-2025
Source: Tourism management, Oct. 2025, v. 110, 105179
Abstract: Rapid technical advances have spurred the potential of generative artificial intelligence (GenAI) in various business settings. However, the tourism industry is in the early stages of understanding and applying GenAI, and comprehensive knowledge is needed. This paper presents a systematic review of the empirical literature, published between 2022 and 2024, related to GenAI in the business and tourism fields. Findings draw a detailed picture of the state of GenAI research. In total, 170 published articles are reviewed based on topics, theories, and methods. Three main topic clusters are identified: 1) antecedents of using GenAI; 2) impacts and applications of GenAI; and 3) technicalities of GenAI. Theoretically, most studies have borrowed foundations from other fields without substantial development. Methodologically, existing research—particularly in tourism—has tended to feature quantitative techniques. This research also compares business and tourism literature based on an antecedents, process and outcomes framework, outlining potential research gaps and opportunities. In addition to synthesizing the current research landscape, this paper presents a multidimensional framework (i.e., theories, contexts, characteristics, and methods – TCCM) that suggests multiple future research questions to inform GenAI studies in tourism.
Keywords: Business
Future research
Generative artificial intelligence
Hospitality
Integrative review
Tourism
Publisher: Pergamon Press
Journal: Tourism management 
ISSN: 0261-5177
EISSN: 1879-3193
DOI: 10.1016/j.tourman.2025.105179
Appears in Collections:Journal/Magazine Article

Open Access Information
Status embargoed access
Embargo End Date 2028-10-31
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.