Travel Recommendations of Tomorrow: Generative Artificial Intelligence and Travel Planning
Dušan Mladenovića✉, Elvira Ismagilovab, Emmanuel Mogajic d, Yogesh K. Dwivedie f g h i
- aDepartment of Business Management, Faculty of Economics and Administration Masaryk University Brno Czech Republic
- bSchool of Management Swansea University (Bay Campus) Swansea UK
- cJaipuria Institute of Management Jaipur India
- dKeele Business School, Denise Coates Foundation Building Keele University Staffordshire UK
- eDepartment of Information Systems &
- fOperations Management King Fahd University of Petroleum &
- gMinerals Dhahran Saudi Arabia
- hInterdisciplinary Research Center for Finance and Digital Economy, King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia
- iRiyad Bank Chair Professor of Digital Business, King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia
- ✉Corresponding author
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Abstract
ABSTRACT This study aims to cultivate an initial understanding of travelers' engagement with generative artificial intelligence (GAI) during the travel planning phase. It focuses on its influence on decision‐making and intentions for continuous usage in planning tourism activities. Utilizing the stimulus–organism–response framework and domain literature, data were gathered through semi‐structured interviews (UK) and scenario‐based questionnaires (USA). The study reveals complex aspects of travelers' behavior, uncovering that while GAI recommendations mitigate the risk of information overload, their influence does not necessarily streamline decision‐making. Trust and information retrieval skills surfaced as moderate determinants of the relationship between recommendations and information overload. This work is a pioneer in empirically exploring and quantifying continuance intentions of generative artificial intelligence (GAI) usage, contributing novel insights to electronic Word of Mouth and decision‐making literature.
TL;DRThe study reveals complex aspects of travelers' behavior, uncovering that while GAI recommendations mitigate the risk of information overload, their influence does not necessarily streamline decision‐making. (Semantic Scholar)