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.
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.
| Original language | English |
|---|---|
| Number of pages | 21 |
| Journal | Industrial Management & Data Systems |
| Early online date | 31 Mar 2025 |
| DOIs | |
| Publication status | E-pub ahead of print - 31 Mar 2025 |
Bibliographical note
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