Abstract
With the widespread application of artificial intelligence (AI) technology in the sports industry, the spectator's experience is increasingly shaped by AI-driven features. To explore the mechanism through which the perceived AI-enabled spectating experience affects viewing behavior, and to validate the mediating role of viewing motivation (SDT Needs Satisfaction) in the relationship between AI and viewing behavior as well as the moderating role of player identification in this mediating pathway, we adopted literature review, survey, and empirical analysis methods. A sample of 272 Chinese tennis enthusiasts was surveyed, and both the measurement model and the structural model were evaluated. The results indicate that the measurement model has good internal consistency, reliability, convergent validity, and discriminant validity. The perceived AI-enabled spectating experience has a significant positive effect on viewing motivation, viewing intention, and recommendation intention. The data show that the indirect effect of the perceived AI-enabled spectating experience on the viewing intention through the viewing motivation is 0.0479, and the indirect effect of the perceived AI-enabled spectating experience on the recommendation intention through the viewing motivation is 0.0548. Both reached a significant level, and the direct effect of the perceived AI-enabled spectating experience has also reached statistical significance. Therefore, viewing motivation plays a partial mediating role between AI and viewing intention and between AI and recommendation intention. Player identification plays a significant positive moderating role (β = 0.2809 on viewing intention, β = 0.1621 on recommendation intention) in the relationship between viewing motivation and viewing behavior; however, it does not moderate the relationship between AI and viewing motivation. In other words, for spectators with higher player identification, viewing motivation drives more strongly both their viewing intention and recommendation intention. We suggest that sports event organizers and media use AI technologies to design differentiated marketing to enhance user engagement and optimize spectators' experience. For spectators with lower player identification, improving service quality can enhance their satisfaction; for those with higher player identification, efforts should focus on strengthening their connection with the players.