GENERATIVE ARTIFICIAL INTELLIGENCE IN SPORTS MARKETING: EXAMINING ITS INFLUENCE ON FAN ENGAGEMENT, BRAND TRUST, AND CONSUMER DECISION-MAKING

Panagiota Tsekeri

Abstract


The rapid evolution of Generative Artificial Intelligence (GenAI) is transforming the global sports industry by redefining how sport organizations communicate with supporters, personalize digital experiences, and influence consumer behavior. Unlike traditional artificial intelligence applications that primarily automate operational tasks, generative AI enables the creation of personalized content, interactive communication, and immersive fan experiences through technologies such as conversational chatbots, automated content generation, recommendation systems, and virtual assistants. These innovations provide sports organizations with unprecedented opportunities to strengthen fan engagement, improve brand trust, and enhance consumer decision-making across digital platforms. Despite the increasing adoption of generative AI by professional football clubs, sports brands, and digital sport media, empirical research examining the mechanisms through which AI-driven personalization influences supporters' behavioral responses remains limited. Existing studies have largely focused on technology adoption or digital marketing effectiveness, while relatively little attention has been given to the combined effects of perceived usefulness, perceived enjoyment, brand trust, and fan engagement within a unified theoretical framework. Consequently, there remains a significant gap in understanding how generative AI contributes to long-term consumer relationships and purchasing behavior in sports marketing. Drawing upon the Technology Acceptance Model (TAM), Relationship Marketing Theory, and the Stimulus–Organism–Response (S–O–R) framework, this study proposes a conceptual research model explaining how AI personalization shapes supporters' cognitive and emotional evaluations, subsequently influencing purchase intention and consumer decision-making. A quantitative research design is proposed using a structured questionnaire administered to football supporters, with data analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM). The proposed model incorporates AI personalization as the primary stimulus, perceived usefulness and perceived enjoyment as psychological responses, and brand trust, fan engagement, purchase intention, and consumer decision-making as behavioral outcomes. The study is expected to contribute to both theory and practice by integrating contemporary artificial intelligence literature with sports marketing research and by providing a comprehensive framework for understanding consumer behavior in AI-enabled sporting environments. The findings are anticipated to assist sports organizations, clubs, sponsors, and digital marketers in designing personalized AI-driven marketing strategies capable of strengthening fan relationships, enhancing trust, and improving long-term commercial performance.

Keywords


generative artificial intelligence; sports marketing; fan engagement; brand trust; purchase intention; consumer decision-making; technology acceptance model; digital sports; personalization

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References


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DOI: http://dx.doi.org/10.46827/ejpe.v13i5.6906

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