Understanding Gen Z’s AI adoption for travel planning and recommendation intent

Wicaksono, Adhika Putra and Izharuddin, Muhammad (2026) Understanding Gen Z’s AI adoption for travel planning and recommendation intent. Manajemen dan Bisnis (MABIS), 25 (2). pp. 405-423. ISSN 2477-1783

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Official URL / DOI: https://www.journalmabis.org/mabis/article/view/12...

Abstract

Artificial intelligence (AI) has transformed travel planning by providing personalized recommendations, interactive assistance, and more efficient decision-making processes. Despite the growing adoption of AI technologies in tourism, limited studies have examined how younger travelers embrace these technologies and subsequently recommend them to others. This study investigates the factors influencing Generation Z’s intention to use AI for travel planning and their willingness to recommend AI-based travel planning tools. Extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), this study collected data from 216 Indonesian Generation Z respondents who had prior experience using AI for travel planning and analyzed the data using Partial Least Squares Structural Equation Modeling and Multi-Group Analysis. The findings indicate that facilitating conditions, hedonic motivation, and habit are the primary drivers of Generation Z’s intention to use AI for travel planning, which subsequently encourages their willingness to recommend AI technologies to others. Conversely, performance expectancy, effort expectancy, and social influence do not appear to play a substantial role in shaping adoption intentions. The findings suggest that tourism practitioners and AI developers should prioritize enjoyable, engaging, and seamlessly integrated digital experiences to encourage broader adoption and recommendation of AI-assisted travel planning technologies among younger travelers.

Item Type: Article
Uncontrolled Keywords: Artificial Intelligence, travel planning, Generation Z, UTAUT2, behavioral intention
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Divisions: Faculty of Business and Economic > Department of Management
Depositing User: BAMBANG SEPTIAWAN
Date Deposited: 21 Jul 2026 04:00
Last Modified: 21 Jul 2026 04:00
URI: http://repository.ubaya.ac.id/id/eprint/50999

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