Decoding Behavioral Intentions Towards Autonomous Vehicles: a Meta-analysis and Empirical Study
Year: 2024
Type: article
Abstract: This article presents a comprehensive analysis of behavioral intentions towards autonomous vehicles (AVs), addressing a critical gap in understanding AV adoption. Through a systematic review of existing literature, we develop a meta-framework that synthesizes previous findings and identifies key research gaps. Our article reveals distinct patterns of behavioral intention based on personal technology innovativeness. Innovative users are influenced by both utilitarian and hedonic factors, while laggards are primarily motivated by hedonic aspects. Importantly, technological fears, particularly data privacy concerns, significantly impact innovative users' intentions, whereas laggards experience more generalized technological anxiety. The article also explores the relationship between individual intentions and anticipated societal outcomes, such as equal mobility opportunities. Our findings highlight the crucial role of moderating variables in shaping AV adoption patterns and offer valuable insights for researchers and practitioners in the autonomous vehicle industry. This article contributes to the growing body of literature on AV acceptance and provides a foundation for future studies in this rapidly evolving field.
Author: Researcher
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6893054497
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