<![CDATA[The growing role of AI in tourism has transformed how tourists plan and make spending decisions. However, limited research investigates how AI-powered platforms influence tourist spending patterns, particularly in Taiwan’s tourism industry. This study aims to fill that gap by examining the relationship between quality recommendations, user engagement, and trust, with perceived value as a mediator and destination familiarity and economic background as moderators. A quantitative research design was used, with data collected from 400 tourists in Taiwan who utilized AI-driven platforms for travel planning. Respondents were selected using purposive sampling. Structural equation modeling (SEM) was employed to analyze direct, indirect, and moderating relationships. The results reveal that quality recommendations, user engagement, and trust significantly affect tourist spending patterns. Perceived value mediates these relationships, while destination familiarity and economic background moderate their influence, particularly for first-time visitors and high-income tourists. This study contributes to the literature by integrating mediating and moderating variables, offering a comprehensive understanding of AI’s impact on tourism. Practically, it suggests that tourism stakeholders should focus on building trust and enhancing AI-driven recommendations to increase spending. Future studies should explore cultural influences and the long-term effects of AI on tourist behavior across different contexts.]]>
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