Evaluative Roles, Fear, and Usage Experience in Shaping the Social Acceptance of Robotaxis

Robotaxis—AI-driven autonomous vehicles operating within platform-based ride-hailing services—have moved from pilot testing to early-stage commercial deployment in China. Despite increasing technological maturity, their diffusion has been accompanied by persistent public fear, posing a critical challenge to wider deployment. Adopting a socio-technical lens, this study advances a dual-role evaluation perspective and positions fear as a central emotional mechanism shaping social acceptance of robotaxis. It distinguishes between user-centric fear, related to personal use of the technology, and society-centric fear, concerning broader societal consequences. Using a mixed-methods approach, 30 interviews were conducted to identify the threats leading to each form of fear. A survey of 602 respondents (302 experienced and 300 inexperienced users) was then employed to examine the proposed research model. The results show that threats regarding safety, time efficiency, privacy, and liability elicit user-centric fear, whereas threats related to employment, equity, and infrastructure increase society-centric fear. Both forms of fear suppress social acceptance. Mediation analysis indicates that several threats influence social acceptance primarily through fear, underscoring the pivotal role of emotional processing in robotaxi deployment. Moderation analysis reveals that robotaxi-riding experience reshapes fear–acceptance relationships: user-centric fear is more influential among inexperienced individuals, whereas society-centric fear becomes more salient among experienced users. These findings highlight the importance of emotion-sensitive and stage-aware management strategies for the socially responsible deployment of AI-enabled mobilities.