The market for plug-in electric vehicles (PEVs) that primarily include battery electric vehicles (BEVs) and plug-in hybrid vehicles (PHEVs) has been rapidly growing in California for the past few years. Given the targets for PEV penetration in the state, it is important to have a better understanding of the pattern of technology diffusion and the factors that are driving the process. Using spatial analysis and Poisson count models, the researchers identify the importance of a neighborhood effect (at home locations) and workplace effect (at commute destinations) in supporting the diffusion of PEV technology in California. In the case of new BEV sales, they found that exposure to one additional BEVor PHEV within a 1-mile radius of a block group centroid is associated with a 0.2%increase in BEV sales in the block group. Interestingly, for new PHEV sales,the neighborhood effect of BEV sales is negative, suggesting that enhanced exposure to this type of technology (which is differentiated in distinctive ways from PHEVs) may impact new PHEV sales through a substitution effect. Specifically, higher BEVconcentration in an area can have an overall negative effect on new PHEV sales. While the neighborhood effect at residential locations is important, the workplace effect also have a notably important effect on new PEV sales. Both effects work in combination with socioeconomic, demographic, policy, and built environment factors in encouraging PEV adoption. These results suggest that policymakers should consider targeted programs and investments that can boost the impact of neighborhood and peer effects on PEV sales

Key words: Plug-in electric vehicles, Peer effects, Spatial analysis, Count model