The Effects of UTAUT Technology Acceptance Factors on Innovative Behavior through Behavioral Intention and Use Behavior of Generative AI: Focusing on the Moderating Role of Transformational Leadership

Generative AI has recently emerged as a core technology that goes beyond automation by transforming work processes and enhancing productivity. However, empirical research on how Generative AI affects employees’ Innovative Behavior remains limited. This study examines how the technology acceptance factors of the Unified Theory of Acceptance and Use of Technology(UTAUT) influence Innovative Behavior through Behavioral Intention and Use Behavior, and how Transformational Leadership moderates each path. The study highlights the roles of the four core UTAUT variables － Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions － in Generative AI acceptance. Using Partial Least Squares Structural Equation Modeling PLS SEM via SmartPLS, results show that Performance Expectancy and Effort Expectancy significantly and positively affect Behavioral Intention, while Social Influence and Facilitating Conditions are not significant. This implies Generative AI has not yet fully diffused in organizations, so external expectations or institutional support have limited influence on actual behavior. Greater Use Behavior leads to significantly higher Innovative Behavior, and this relationship becomes stronger under Transformational Leadership, which moderates Effort Expectancy to Behavioral Intention, Behavioral Intention to Use Behavior, and Use Behavior to Innovative Behavior. In conclusion, specific UTAUT variables influence Behavioral Intention, Use Behavior, and Innovative Behavior, while Transformational Leadership exerts a meaningful moderating effect across the adoption process. Practically, managing employee expectations and enhancing leadership capabilities can increase technology utilization and maximize innovation outcomes.