Factors Affecting the Tourist Intention to use Artificial Intelligence in United States

Abstract

This study investigates the determinants of individuals' intention to use artificial intelligence (AI) for tourism in the United States. This study adopts a cross-sectional design, employing a convenience sampling technique. Data collection was conducted via an online survey, targeting 239 participants who have recent travel experience. Constructs including interactivity, facilitating conditions, informational support, performance expectancy, and intention to use AI for tourism were assessed using established measurement items adapted from prior literature. The analysis employed partial least squares structural equation modeling (PLS-SEM) to examine the relationships between these constructs. The results reveal that interactivity, facilitating conditions, informational support, and performance expectancy significantly influence individuals' intention to use AI for tourism. The findings offer practical implications for the tourism industry, suggesting strategies to enhance AI adoption among travelers. Additionally, this study contributes to the theoretical understanding of technology adoption in the tourism context. Future research could explore additional factors and employ longitudinal designs to further elucidate the dynamics of AI adoption in tourism. Overall, this study advances our knowledge of the factors shaping individuals' intention to use AI for tourism and lays the groundwork for continued research in this rapidly evolving field.