Investigating the Neighborhood Effect on Hybrid Car Adaptation
Authors: X. Zhu and C. Liu
Report
Synopsis: Utilizing the 2009 Florida NHTS add-on data, we conducted a cluster analysis to display the spatial clusters of the households who purchased the HEVs during the period of 2005-2008. We found that more clusters of HEVs emerged overtime. Geographic patterns also demonstrated the increasing number of clusters featured by households with hybrid vehicles and the surrounding hybrid vehicle adopters. Further, the relationship between the hybrid vehicle adoption and neighborhood effects (NE) and social-demographic factors are analyzed using Binary Logit models with and without weight. Neighborhood effects are confirmed to be significant in both urban and rural models, especially the factors of 1-mile and 5-mile neighborhood coverage. This indicates that potential buyers are more likely to purchase the HEVs when there are more HEVs exposures surrounding, and this measurement of exposure is proved to be reasonable for neighborhood effect. Among the social and demographic attributes, household income is the most significant variable and plays a dominant role in affecting the propensity to buy hybrid vehicles. Other factors, such as vehicle ownership, household structure and education attainment level also significantly affect households’ choice of hybrid cars. Vehicle usage is a controversial factor in this study because of the interactive correlation between the type of vehicle owned and corresponding usage.
Authors: X. Zhu and C. Liu
Report
Synopsis: Utilizing the 2009 Florida NHTS add-on data, we conducted a cluster analysis to display the spatial clusters of the households who purchased the HEVs during the period of 2005-2008. We found that more clusters of HEVs emerged overtime. Geographic patterns also demonstrated the increasing number of clusters featured by households with hybrid vehicles and the surrounding hybrid vehicle adopters. Further, the relationship between the hybrid vehicle adoption and neighborhood effects (NE) and social-demographic factors are analyzed using Binary Logit models with and without weight. Neighborhood effects are confirmed to be significant in both urban and rural models, especially the factors of 1-mile and 5-mile neighborhood coverage. This indicates that potential buyers are more likely to purchase the HEVs when there are more HEVs exposures surrounding, and this measurement of exposure is proved to be reasonable for neighborhood effect. Among the social and demographic attributes, household income is the most significant variable and plays a dominant role in affecting the propensity to buy hybrid vehicles. Other factors, such as vehicle ownership, household structure and education attainment level also significantly affect households’ choice of hybrid cars. Vehicle usage is a controversial factor in this study because of the interactive correlation between the type of vehicle owned and corresponding usage.