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Daniel Kogan

Clustering Analysis of Attitudes towards Automated Vehicles ©2022

While market segmentation is widely used to study travel behaviour (Beirão & Cabral, 2008; Kieu et al., 2015), it has not been widely applied to study the public opinion of automated vehicles (AVs). Previous research has primarily used inferential statistics and has found that younger males living in urban areas who have higher income are likely to be more interested in AV use and more willing to pay (WTP) for such technology (Bansal et al., 2016; Hohenberger et al., 2016; Hudson et al., 2018; Schoettle & Sivak, 2014). This study differs from those in that it applies Two-Step Clustering Analysis, a market segmentation approach which highlights more complex linkages between consumer segments and adoption than is portrayed in conditional bivariate estimates. We identified five sample market segments: Retirees, Rural Workers, Students, Working Class, and Torontonians. These segments significantly differ one from another when cross-tabulated with intention of use and WTP for AV variables. Results suggest that market segmentation may be a viable technique for studying and targeting sub-groups of individuals to shape automated vehicle use, while also providing policymakers with means and insights for intervention. Since we found no differences in attitudes regarding AV modes, we conclude that AV adoption will highly depend on public opinion regarding AVs, and that interventions should focus on raising awareness and exposure to AV modes with the most societal benefits.