Integrating perceived safety and socio-demographic factors in UTAUT model to explore Australians' intention to use fully automated vehicles

Abstract

Growing global research utilizes user acceptance models to investigate the public acceptance of automated vehicles (AVs). A growing body of literature suggests it is essential to recognize cultural differences that may influence people's decisions and the intention to use (AVs). While the influence of perceived safety on AVs adoption has been examined globally, it has often been overlooked in Australia. To address this knowledge gap, this study extended the Unified Theory of Acceptance and Use of Technology (UTAUT) model by incorporating perceived safety and socio-demographic factors in assessing behavioral intention for fully AVs in Australia. This study is the first in Australia to include perceived safety in the UTAUT model and look at how different factors like age, gender, experience, income, education, and travel habits affect people's intention to use technology. The model was evaluated with Structural Equation Modelling using a dataset of 804 respondents from Australia.

Perceived Safety (PS) holds comparable importance to Social Influence (SI) and Facilitating Conditions (FC). Our analysis revealed that younger age groups exhibit a more substantial positive correlation between Performance Expectancy (PE) and Behavioral Intention (BI) compared to older age groups. Notably, there are significant distinctions in the impact of PS on BI between older and younger age groups, as well as between those with and without prior experience with AVs. Moreover, gender has a moderating effect akin to age in the PE-BI relationship. Our findings also reveal that age moderates the relationship between PE and BI, with younger individuals exhibiting less susceptibility to social influence compared to older counterparts. Gender also emerges as a moderator, affecting the relationship between FC and BI. Additionally, income moderates the relationships between both EE (Effort Expectancy) and FC with BI. However, qualifications do not significantly moderate the relationships between latent variables and BI.

The multigroup analysis highlights a significant divergence in the influence of PE on BI between groups with no experience and experienced people. Additionally, the study shows that the higher-income group displays a lower coefficient of FC towards BI, potentially due to their pre-existing knowledge base. The findings from this study assist decision-makers by providing insights into public attitudes towards AVs by revealing the key factors influencing public acceptance.