ChatGPT use in hospitality and tourism: a multi-analytic approach

This study explored the antecedents of tourists’ intentions to use ChatGPT for seeking information, and investigated the effect of these, using a fuzzy-set approach. The study performed a complex configurational assessment of the technology acceptance model (TAM), the theory of planned behavior (TPB), and behavioral reasoning theory (BRT) to predict tourists’ strong and weak intentions to use AI chatbots for hospitality and tourism information. To attain this research goal, a total of 604 questionnaires were collected using Korean customers who used ChatGPT in Korea. Results of the analyses indicated that multiple factors rooted in the TAM, TPB, and BRT, showed significant interactions resulting in both desirable and undesirable outcomes. Furthermore, the essential role of convenience was found to be one of the BRT factors that increased intentions to use ChatGPT. The present research differs from earlier studies in that it investigated the complex nature of tourists’ behavioral intentions, and therefore the findings advance current knowledge and offer novel insights for practitioners.