AI-personalized sports experiences: the moderating role of fan identification
Don Lee, Woong Kwon, Iseup Maeng, Minseok Cho, Michael CottinghamPurpose
This study aims to investigate how fans respond to artificial intelligence (AI)-personalized sports experiences and how these responses are influenced by their level of identification with a sports entity.
Design/methodology/approach
Integrating the technology acceptance model, source credibility theory and uses and gratifications framework, personalization is conceptualized as a driver of perceived authenticity, which, in turn, enhances overall satisfaction with AI-generated sports content (e.g. personalized highlights, recommendation feeds, chatbots and AI-driven statistics). Using a cross-sectional survey of adult sport consumers with recent AI content experience, we test a moderated mediation model in which fan identification moderates both the personalization–authenticity and authenticity–satisfaction relationships.
Findings
Results suggest that personalization enhances perceived authenticity and satisfaction, with these effects amplified for highly identified fans. Conversely, low-identified fans may perceive AI content as overly algorithmic or intrusive, attenuating or reversing these effects.
Originality/value
This study extends theory on AI-mediated sports marketing by highlighting authenticity as a key psychological mechanism linking personalization to satisfaction and demonstrating fan identification as a critical boundary condition. Findings offer actionable guidance for tailoring AI personalization to optimize fan engagement and sponsorship outcomes.