Income, political affiliation, urbanism and geography in stated preferences for electric vehicles (EVs) and vehicle-to-grid (V2G) technologies in Northern Europe

Bibliographic Data

ID12293237
AuthorsB K Sovacool (0000-0002-4794-9403, University of Sussex, corresponding author), Johannes Kester (0000-0001-5384-0247, Aarhus University), Lance Noel (0000-0001-9396-2361, Aarhus University), Gerardo Zarazua De Rubens (0000-0002-6698-2516, Aarhus University)
Year2019
Volume78
Pages214-229
Publication date2019-06-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Transport Geography (JOURNAL)
Journal identifiersISSN: 0966-6923 • E-ISSN: 1873-1236
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.jtrangeo.2019.06.006
OpenAlexW2954239807
LanguageEN
Citations received18
References cited65

Despite a potentially revolutionary shift towards electric mobility in the passenger vehicle market, the academic and policymaking communities remain wedded to a techno-economic paradigm that may not fully appreciate deeper social and geographic elements of a transition to electric vehicles. In this paper, based primarily on bivariate statistical analysis as well as a hierarchical regression analysis of a survey distributed to >5000 respondents across Denmark, Finland, Iceland, Norway, and Sweden, we analyze how perceptions and attitudes towards electric vehicles and vehicle-to-grid technologies differ by income, political affiliation, and geography. Although our findings confirm EV ownership and mobility patterns in general are related to income—those with higher incomes both own more EVs and drive more generally—they also confirm that interest in EVs is not so strongly related. Lower income groups seem to ask less from their cars, thus potentially opening up a market for cheaper low-range alternates. Political orientation is correlated to car and EV ownership, with those on the “left” more interested yet those on the “right” more able and willing to buy expensive cars. Moreover, we see variation in preferences across urban and rural subcategories, and our findings strongly suggest that EVs need not be promoted only for city or suburban areas. When controlling for variables, a multilevel regression analysis does not change the overall thrust of these associations

Bivariate analysis · Demographic economics · Economic geography · Economics · Electric vehicle · Geography · Multilevel model · Political science · Politics · Electric Vehicles and Infrastructure · Energy and Environment Impacts · Energy, Environment, and Transportation Policies

Tools

Open DOISci-HubOpen Access