Modeling the Acceptance of Artificial Intelligence in Sports Services

Abstract

This research aims to model the factors influencing the acceptance of artificial intelligence in sports services. This study is descriptive-correlational in nature and uses Structural Equation Modeling (SEM) for data analysis. The statistical population consists of users from sports clubs in northern Tehran, and sampling was conducted using a convenience sampling method (n = 380). Data were analyzed using a researcher-developed questionnaire and software tools SPSS and SmartPLS. The results indicated that sports services (β = 0.203), evaluation and monitoring systems (β = 0.102), time and resource management (β = 0.363), and participation in sports (β = 0.230) have a significant positive impact on the intention to use artificial intelligence services in sports (p < 0.05). The overall model fit index (GOF = 0.63) demonstrates a strong model fit. This study showed that artificial intelligence, by improving service quality, optimizing resource management, and analyzing sports data, can contribute to increasing user satisfaction and technology acceptance in the sports field.