Analysis of technology acceptance of AI umpiring in baseball using the UTAUT model

Abstract

This study explores the acceptance of AI-based umpiring systems among baseball players, focusing on the factors influencing their intention to adopt the technology. Using the Unified Theory of Acceptance and Use of Technology (UTAUT), the research examines the effects of performance expectancy, effort expectancy, and social influence on trust and behavioral intention. A total of 191 baseball players from university and professional teams in South Korea participated in the survey, and structural equation modeling was employed for analysis. The results indicate that all three UTAUT factors had significant positive effects on both trust and behavioral intention, with trust serving as a significant mediator, particularly in the paths from performance expectancy and effort expectancy. Importantly, this study provides unique insights based on the precedent-setting case of South Korea, which became the first country to fully implement an AI umpiring system in professional baseball (KBO). By empirically analyzing players’ initial perceptions in this pioneering context, the study offers valuable perspectives for global discussions on AI adoption in sports officiating. As baseball returns to the official Olympic program at LA28, the research provides timely implications regarding the human factors essential for successful AI integration in elite sports.