Uniqueness versus superficial accuracy: The perceived accuracy of GPTs for travel decision-making

Abstract

The study aims to uncover the factors influencing tourists’ acceptance of GPTs for travel decision-making and how they perceive the accuracy of GPTs, using an interaction-centric approach and assemblage theory. The study is situated in the pre-trip phase of travel decision-making. It employs experimental and qualitative methodologies, utilizing IPA to examine the nuanced dynamics of these interactions and their implications for travel decision-making. The study incorporated scenario-based research to create a realistic and reflective environment for observing tourist–GPT interactions. Following the interactions with GPT, in-depth semi-structured interviews were conducted to focus on participants’ experiences. The results showed that participants accept using GPTs to obtain travel information since GPTs’ recommendations are relevant, efficient, and intelligent beyond superficial accuracy. Still, participants do not make their travel decisions solely based on GPTs. They use GPTs for travel decision-making if they generate a human-like interaction environment. The study contributes to existing theoretical discussions by applying assemblage theory and the interaction-centric approach to a novel technological context, thereby highlighting the implications of human–technology assemblages in shaping contemporary travel behavior. Therefore, the findings illuminate the unique aspects of GPTs, their perceived accuracy, and their acceptance in informing tourists’ travel decision-making, subsequently generating further interest and research.