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This study aimed to investigate tourists’ intentions regarding the adoption of AI-enhanced tour guide apps. Variables such as effort expectancy, performance expectancy, social influence, facilitating conditions, and hedonic motivation from the Unified Theory of Acceptance and Use of Technology (UTAUT2) model were utilised to assess the acceptance of AI-enhanced tour guide apps. The data was collected online from adults aged ‘18 and above’ in the United States, using a market panel company. A dataset of 525 participants was utilised for the research. SPSS was utilised for conducting frequency and factor analysis, while SmartPLS-4 was employed for carrying out structural equation testing. To ensure the validity and reliability of the research, exploratory factor analysis, correlation analysis, and discriminant validity analyses were initially performed. The study findings highlight that the acceptance of AI-enhanced tour guide apps among tourists, as framed within the UTAUT2 model, is significantly influenced by performance expectancy, facilitating conditions, and hedonic motivation. Gender and age did not moderate the relationship between effort expectancy, performance expectancy, social influence, facilitating conditions, hedonic motivation, and usage intentions to use AI-enhanced tour guide apps. |
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