Measuring generative AI-mediated travel experiences: Development and validation of a multidimensional scale

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Authors: Hakseung Shin, 薛荣学, Heewon Yoon, Junghee Lee
Cited by: 1
References: 87

Abstract

This study conceptualizes and measures generative AI (GAI)-enabled travel experiences by explaining how interaction with GAI changes the travel process. Using a two-phase, mixed-method design involving qualitative interviews and large-scale surveys in South Korea, China, and the United States, the study develops and validates a multidimensional scale. The qualitative results of the study showed that GAI acts as an agent that produces four experiential outcomes: hyper-personalized experiences reflecting autonomous preference expression, effective experiences driven by improved confidence and reduced cognitive effort, expanded experiences enabled by broader access to information and possibilities, and deep experiences that foster rich engagement and co-creation. The quantitative findings show that GAI-enabled travel experiences increase satisfaction, which subsequently increases reuse intentions, loyalty, and word-of-mouth. Theoretically, this study advances understanding of the affective, symbolic, and utilitarian dimensions of GAI-mediated travel experiences. Practically, it provides tourism stakeholders with a measurement tool to design and evaluate GAI-driven services.

Fields of Study & Subjects

AI in Service Interactions Persona Design and Applications Diverse Aspects of Tourism Research

Publication details

Journal / source
Tourism Management Perspectives
Publisher
Elsevier BV
Volume
63
Pages
101492–101492
Publication date
19 June 2026
Language
EN