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Consumer intentions for alternative fuelled and autonomous vehicles: A segmentation analysis across six countries

Potoglou, Dimitris, Whittle, Colin, Tsouros, Ioannis and Whitmarsh, Lorraine 2020. Consumer intentions for alternative fuelled and autonomous vehicles: A segmentation analysis across six countries. Transportation Research Part D: Transport and Environment 79 , 102243. 10.1016/j.trd.2020.102243
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Abstract

Rapid advances in the development of autonomous and alternative-fuel vehicles (AFVs) are likely to transform the future of mobility and could bring benefits such as improved road safety and lower emissions. Achieving these potential benefits requires widespread consumer support for these disruptive technologies. To date, research to explore consumer perceptions of transport innovations has tended to consider them in isolation (e.g., driverless cars, electric vehicles). The current paper examines the predictors of consumer interest in and willing to pay for both AFVs and autonomous vehicles through a choice experiment conducted in six diverse markets: Germany, India, Japan, Sweden, UK and US. Using Latent Class Discrete Choice Models, we observe significant heterogeneity both within and across the country samples. For example, while Japanese consumers are generally willing to pay for autonomous vehicles, in most European countries, consumers need to be compensated for automation. Within countries, though, we found some segments – typically, those with a university degree, and self-identifying as having a pro-environmental identity and as being innovators– are more in favour of automation. Significantly, we also found that support for autonomous vehicles is associated with support for AFVs, perhaps, due to common demographic or socio-psychological predictors of both types of innovative technology. These findings are valuable for policymakers and the automotive industry in identifying potential early adopters, as well as consumer segments or cultures less convinced to adopt these innovative transport technologies.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Geography and Planning (GEOPL)
Psychology
Publisher: Elsevier
ISSN: 1361-9209
Date of First Compliant Deposit: 22 January 2020
Date of Acceptance: 17 January 2020
Last Modified: 24 Nov 2020 15:15
URI: http://orca.cf.ac.uk/id/eprint/128938

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