User acceptance of autonomous vehicles: a mixed-methods study

Purpose: This research aims to provide a comprehensive understanding of the factors influencing individuals' adoption of autonomous vehicles (AVs) and shed light on further development of technology acceptance theories in the backdrop of radical technological and societal changes. Design/methodology/approach: The study adopts a mixed-methods approach, combining a meta-analysis of 107 empirical studies and 20 in-depth interviews. The meta-analysis examines the predictive power of technology acceptance models, while the interviews offer qualitative insights to elaborate on and deepen the quantitative findings. The integration of these two methods allows for the development of meta-inferences and a more holistic view of AV adoption. Findings: The meta-analysis revealed that while traditional technology acceptance factors such as perceived usefulness and trust remain significant, the effects of perceived ease of use and perceived behavioral control are weak. New factors such as perceived loss of autonomy, loss of personal control,and informational social influence emerged as critical influences on AV adoption. The qualitative findings further elaborate on these factors, highlighting the need for updated conceptualizations. Originality: This research offers a novel contribution by integrating meta-analytic and qualitative findings to reassess the applicability of existing technology acceptance theories for AVs. It introduces new constructs, such as perceived loss of autonomy and informational social influence and emphasizes the need to update and refine traditional constructs like perceived usefulness and trust to reflect the unique features of AV technologies.

Publication Details

Journal
Newcastle University ePrints (Newcastle Univesity)
Published
2025-04-28
DOI
https://doi.org/10.57711/yeh6-c954
Primary Topic
Seismic Waves and Analysis
Type
article
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article

User acceptance of autonomous vehicles: a mixed-methods study

Newcastle University ePrints (Newcastle Univesity)
Seismic Waves and Analysis
article

User acceptance of autonomous vehicles: a mixed-methods study

article en

Abstract

Purpose: This research aims to provide a comprehensive understanding of the factors influencing individuals' adoption of autonomous vehicles (AVs) and shed light on further development of technology acceptance theories in the backdrop of radical technological and societal changes. Design/methodology/approach: The study adopts a mixed-methods approach, combining a meta-analysis of 107 empirical studies and 20 in-depth interviews. The meta-analysis examines the predictive power of technology acceptance models, while the interviews offer qualitative insights to elaborate on and deepen the quantitative findings. The integration of these two methods allows for the development of meta-inferences and a more holistic view of AV adoption. Findings: The meta-analysis revealed that while traditional technology acceptance factors such as perceived usefulness and trust remain significant, the effects of perceived ease of use and perceived behavioral control are weak. New factors such as perceived loss of autonomy, loss of personal control,and informational social influence emerged as critical influences on AV adoption. The qualitative findings further elaborate on these factors, highlighting the need for updated conceptualizations. Originality: This research offers a novel contribution by integrating meta-analytic and qualitative findings to reassess the applicability of existing technology acceptance theories for AVs. It introduces new constructs, such as perceived loss of autonomy and informational social influence and emphasizes the need to update and refine traditional constructs like perceived usefulness and trust to reflect the unique features of AV technologies.

Newcastle University ePrints (Newcastle Univesity)
Openalex Percentile: Top 52%
Seismic Waves and Analysis
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User acceptance of autonomous vehicles: a mixed-methods study · Newcastle University ePrints (Newcastle Univesity) (2025) | TGRS Research Map | TGRS