Where are the electric vehicles? A spatial model for vehicle-choice count data

T. Donna Chen, Yiyi Wang and Kara M. Kockelman

Journal of Transport Geography, 2015, vol. 43, issue C, 181-188

Abstract: Electric vehicles (EVs) are predicted to increase in market share as auto manufacturers introduce more fuel efficient vehicles to meet stricter fuel economy mandates and fossil fuel costs remain unpredictable. Reflecting spatial autocorrelation while controlling for a variety of demographic and locational (e.g., built environment) attributes, the zone-level spatial count model in this paper offers valuable information for power providers and charging station location decisions. By anticipating over 745,000 personal-vehicle registrations across a sample of 1000 census block groups in the Philadelphia region, a trivariate Poisson-lognormal conditional autoregressive (CAR) model anticipates Prius hybrid EV, other EV, and conventional vehicle ownership levels.Initial results signal higher EV ownership rates in more central zones with higher household incomes, along with significant residual spatial autocorrelation, suggesting that spatially-correlated latent variables and/or peer (neighbor) effects on purchase decisions are present. Such data sets will become more comprehensive and informative as EV market shares rise. This work’s multivariate Poisson-lognormal CAR modeling approach offers a rigorous, behaviorally-defensible framework for spatial patterns in choice behavior.

Keywords: Electric vehicles; Spatial count modeling; Vehicle choice; Vehicle ownership; Consumer behavior; Conditional auto-regressive (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (21)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jotrge:v:43:y:2015:i:c:p:181-188

DOI: 10.1016/j.jtrangeo.2015.02.005

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