The spatial pattern of demand in the early market for electric vehicles: Evidence from the United Kingdom Craig Morton Jillian Anable Godwin Yeboah Caitlin Cottrill 2134/35133 https://repository.lboro.ac.uk/articles/journal_contribution/The_spatial_pattern_of_demand_in_the_early_market_for_electric_vehicles_Evidence_from_the_United_Kingdom/9458009 This paper reports a spatial analysis of Electric Vehicle registrations across the local authorities of the United Kingdom during the early phase of market development. Spatial autocorrelation tests are applied in order to identify any spatial organisation in registrations rates and spatial regression models are specified to consider the effect of socioeconomic, household, and transport system characteristics over registrations. Specific attention is paid to the association between Electric Vehicle registrations and the presence of charging infrastructure to consider if registrations are affected by infrastructure in the immediate and intermediate vicinity. The results of the analysis suggest Electric Vehicle demand exhibits a moderate degree of spatial clustering, which indicates the emergence of lead and laggard markets, and that the spatial variation in Electric Vehicle uptake can be partially explained through other characteristics of the local authorities. Characteristics relating to education level, employment status, income level, population density, dwelling type, household size, car availability, and the presence of Hybrid Electric Vehicles are significant factors in explaining the rate of Electric Vehicle registrations. Moreover, the level of charge point infrastructure installed within a local authority is positively associated with EV demand. From a policy perspective, the results reported in this paper indicate that local conditions are likely to be important in the rate of Electric Vehicle adoption, which may be of use when considering the development of geographically targeted interventions to accelerate Electric Vehicle demand. 2018-10-02 12:55:30 Electric vehicle demand Spatial diffusion Socio-technical transitions Spatial regression Spatial spillovers Built Environment and Design not elsewhere classified