Abstract Electrification of the transportation sector has grown substantially over recent years, though much remains unclear regarding the continued trajectory of electric vehicle (EV) adoption and its influencing factors. The impacts of charging infrastructure and the geographic heterogeneity of adopter characteristics are two facets not fully understood. This work investigates EV adoption at a granular geographic level using spatial econometric methods. The dataset – ZIP (postal) code-level EV population in four US states since 2011 – is more comprehensive than previous studies at a granular geographic level have used. The work finds that battery EV and plug-in hybrid EV forecasts must be developed separately. Spatial clustering is significant and cannot be ignored; geographic variations in sociodemographic and land use measures are found to influence adoption and their intensity varies by state. Finally, existing data permits a better understanding of these relationships with respect to the earliness of adoption rather than the rate of adoption in ZIP codes.
Highlights Utilizes spatial econometric models to examine EV adoption in US ZIP codes. Creates logistic model forecasts of EV adoption. Spatial clustering of earliness of EV adoption and rate of adoption in ZIP codes. Examines influence of public charging infrastructure on EV adoption. Considers relationship between EV adoption and sociodemographics and land use.
Examining electric vehicle adoption at the postal code level in US states
2024-01-06
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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