What drives people to use self-driving cars? An integrated model

This study examines the factors associated with users' behavioral intentions to adopt self-driving cars by integrating the Technology Acceptance Model (TAM), Task-Technology Fit (TTF), and self-efficacy. Data from 293 self-driving car users were analyzed using structural equation modeling (SEM). The results show that TTF is positively associated with both perceived usefulness (PU) and perceived ease of use (PEOU), underscoring the importance of system-task alignment. However, PEOU is not significantly related to PU, diverging from traditional TAM assumptions, while PU's association with behavioral intention is fully mediated by user attitudes. Self-efficacy and opinion leadership are positively related to TTF, highlighting the role of individual capability and social influence. System features such as interactivity and flexibility are positively related to user perceptions, whereas inadequate system guidelines show a negative association with TTF. These findings provide theoretical and practical insights for improving user acceptance of autonomous vehicles by emphasizing self-efficacy development, opinion leadership, and user-centered system design.