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Factors influencing early battery electric vehicle adoption in Ireland

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  • Mukherjee, Sanghamitra Chattopadhyay
  • Ryan, Lisa

Abstract

This paper examines factors that influence battery electric vehicle (BEV) uptake amongst early adopters. An incomplete understanding of the motivations behind consumer uptake hampers policy design to encourage adoption. We provide new evidence for Ireland on the key determinants of uptake in the early phase of technology diffusion by combining Irish census and BEV uptake data at a granular spatial scale for the first time. Results from our count data models show that while people with a university degree and long-distance commuters commuting for at least an hour a day are positive determinants of adoption, rented accommodation and young people between 19 and 34 years are negative predictors of uptake. Moreover, two GIS-derived spatial variables are significant albeit with unexpected signs – while the average distance to the nearest charge point is a positive predictor of uptake, access to dealers within 10 km of the neighbourhood is a negative predictor of uptake. The spatial econometric analysis indicates that adopters mainly cluster around the largest urban centres in Ireland. This may be influenced by population as well as spillover effects due to adoption in neighbouring localities, changes in socio-demographics and neighbourhood characteristics such as public charging infrastructure or dealers in the area, and other unobserved cross-border effects that we cannot estimate due to lack of data. The Irish results could potentially be applied to comparable emerging EV markets. They may help policy-makers devise strategies that stimulate regional adoption where uptake has been poor or be used to predict potential future uptake based on past trends.

Suggested Citation

  • Mukherjee, Sanghamitra Chattopadhyay & Ryan, Lisa, 2020. "Factors influencing early battery electric vehicle adoption in Ireland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
    • Handle: RePEc:eee:rensus:v:118:y:2020:i:c:s1364032119307129
    DOI: 10.1016/j.rser.2019.109504
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