Media Influence, Trust, and the Public Adoption of Automated Vehicles

Abstract

Automated vehicles (AVs) have received attention from academia and industry due to their numerous advantages, including safety, efficient mobility, and convenience. One of the biggest challenges to the mass implementation of AVs is public acceptance. This study aimed to explore the factors affecting the public’s intention to adopt AVs. Based on social cognitive theory, a theoretical model was developed with the constructs of social media (e.g., WeChat, Weibo, and TikTok) influence, traditional media (e.g., television, radio, and newspapers) influence, subjective norms, self-efficacy, perceived safety and privacy risks, trust, and behavioral intentions. The data were collected from Changsha, China, through web- and paper-based surveys. A total of 964 responses was collected to test the hypothesized model through the partial least squares path modeling approach. The results revealed that the public’s trust and intention to adopt AVs are more likely to increase through positive information on social and traditional media, strengthening subjective norms and self-efficacy, and reducing perceived safety risks. The study’s findings can be useful for establishing intervention strategies and managerial applications to enhance the public’s trust and intentions to adopt AVs.