ChatGPT and Tourist Decision-Making: An Accessibility–Diagnosticity Theory Perspective

Abstract

This paper investigates the role of ChatGPT in informing tourist decision-making across different destination contexts, focusing particularly on the accessibility and diagnosticity of its recommendations. Specifically, we inform our analysis with the tenets of the Accessibility–Diagnosticity Theory (ADT), to draw insights into ChatGPT's capabilities to produce contextually relevant and personalised travel content. Our findings reveal a sophisticated and multi-dimensional advisory approach characterised by three themes: ‘Tailored Engagement and Accessibility’, ‘Diagnosticity of Information’ and ‘Contextual Variation in Criteria Prioritisation.’ These themes and their intersections highlight ChatGPT's potential to improve tourist decision-making by offering comprehensive and user-centric guidance. Based on these findings, we develop a model of ChatGPT's advisory dynamics in tourism decision-making, which illustrates how ChatGPT integrates personalised insights, diagnostic relevance and contextual adaptation, offering a blueprint for leveraging artificial intelligence in enhancing the travel experience. We conclude with a discussion of the theoretical and practical contributions of the study.