ArticleBMC psychology2025
What drives people to use self-driving cars? An integrated model.
Article in BMC psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
3 authors.
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Abstract
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.