Demographic Insights Into Autonomous Taxi Adoption: A Multi-Group Analysis Extending UTAUT2 With Trust, Perceived Risk, and Personal Innovativeness
Year: 2025
Type: article
Study design: Observational Study
Abstract: The adoption of autonomous taxis (ATs) is expected to revolutionize urban mobility, yet user skepticism and demographic disparities present significant barriers to widespread acceptance. To address crucial gaps in AT adoption research, this study explores direct determinants of AT adoption using an enhanced UTAUT2, the moderating role of personal innovativeness, and demographic variations in these relationships. Based on a survey of 417 respondents in Wuhan, China, relationships between the proposed theoretical constructs and AT adoption intention are examined using structural equation modeling (SEM), complemented by multi-group analysis (MGA) to investigate demographic variations. The findings indicate that performance expectancy, effort expectancy, facilitating conditions, perceived cost, trust, and perceived risk significantly influence AT adoption, while social influence, hedonic motivation, and personal innovativeness do not. Trust plays a particularly strong role among experienced users, while perceived risk remains a universal concern. MGA reveals that lower-income and lower-education groups are more sensitive to effort expectancy, whereas higher-income users are primarily influenced by performance expectancy. Personal innovativeness moderates the effects of performance expectancy and trust, with stronger impacts observed in higher-income groups. This research advances the autonomous transportation technology acceptance theory in the AT domain and provides actionable insights for policymakers, technology developers, and transportation planners to promote AT adoption through targeted strategies.
Source: IEEE Access
Authors: Chuan Zheng, Danling Sun, Munirah Khamarudin, Azanin Ahmad, Han Wei, Jie Xu
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,075
OpenAlex ID: W4412403874
