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First published online January 1, 2013

Investigating the Neighborhood Effect on Hybrid Vehicle Adoption

Abstract

Transportation accounts for about 33% of total U.S. greenhouse gas emissions. To reduce petroleum consumption, vehicle air pollution, and noise emissions, the hybrid electric vehicle (HEV) was introduced to the U.S. market in 1999 and offered new efficiency-improving technologies. However, the current market share and adoption rate of HEVs are still low. HEV sales are not spatially and temporally uniform. The HEV spatial diffusion process is investigated, and the influence of the neighborhood effect (NE) on HEV adoption is analyzed. A cluster analysis is conducted with Florida add-on data from the 2009 National Household Travel Survey to display the spatial clusters of the households that purchased HEVs from 2005 to 2008. More HEV clusters emerge over time. Geographic patterns demonstrate increasing numbers of clusters featuring households with hybrid vehicles and surrounding HEV adopters. Furthermore, the relationships between hybrid vehicle adoption, NEs, and sociodemographic factors are analyzed with weighted and unweighted binary logit models. NEs are confirmed to be significant in both urban and rural models, especially the factors of 1- and 5-mi neighborhood coverage. This finding indicates that potential buyers are more likely to purchase HEVs when HEV exposure is high in the surrounding areas, and this measurement of exposure is proved reasonable for NEs. Of the sociodemographic attributes, household income is the most significant variable and plays a dominant role in affecting the propensity to buy hybrid vehicles. Factors such as vehicle ownership, household structure, and education attainment level also significantly affect a household's choice to buy a hybrid car.

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Article first published online: January 1, 2013
Issue published: January 2013

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© 2013 National Academy of Sciences.
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Authors

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Xiaoyu Zhu
Room 1226C, National Center for Smart Growth Research and Education, University of Maryland, Preinkert Field House, College Park, MD 20742.
Chao Liu
Room 1226D, National Center for Smart Growth Research and Education, University of Maryland, Preinkert Field House, College Park, MD 20742.

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