The Impact of AI-Based Personalized Recommendation Services on Sports Fans’ Digital Consumption Behavior: Focusing on the Mediating Effects of Immersion and Satisfaction

This study empirically analyzed the impact of AI-based personalized content recommendation services on the digital consumption behavior of sports fans. Specifically, it examined how the sub-factors of the recommendation service-usefulness, relevance, and reliability-affect content satisfaction and immersion, and how these variables influence digital consumption behavior. The study targeted individuals aged 10 to 40 and older residing in Seoul and the metropolitan area who had experience using AI-based personalized content services. A total of 385 questionnaires were collected, and 373 valid responses were used for the final analysis after excluding 12 insincere ones. Data were analyzed using SPSS 28.0, including frequency analysis for general characteristics, exploratory factor analysis for construct validity, Cronbach’s α for reliability, descriptive statistics for means, standard deviations, skewness, and kurtosis, Pearson correlation analysis, and regression analysis to test the research hypotheses. The results showed that AI-based personalized recommendation services had a positive effect on both content satisfaction and immersion. Furthermore, both satisfaction and immersion significantly influenced digital consumption behavior. The recommendation service also had both direct and indirect effects on digital consumption behavior through satisfaction and immersion. These findings suggest that AI-driven personalization is a critical strategy in enhancing user engagement and behavioral responses in digital sports content platforms.