In this paper, we formulate and estimate a nested model structure that includes a multiple discrete-continuous extreme value (MDCEV) component to analyze the choice of vehicle type/vintage and usage in the upper level anda multinomial logit (MNL) component to analyze the choice of vehicle make/model in the lower nest. Data for the analysis are drawn from the 2000 San Francisco Bay Area Travel Survey. The model results indicate the important effects of household demographics, household location characteristics, built environment attributes, household head characteristics, and vehicle attributes on household vehicle holdings and use. The model developed in the paper is applied to predict the impact of land-use and fuel cost changes on vehicle holdings and usage of the households. Such predictions can inform the design of proactive land-use, economic, and transportation policies to influence household vehicle holdings and usage in a way that reducesthe negative impacts of automobile dependency such as traffic congestion,fuel consumption and air pollution. (A) Reprinted with permission from Elsevier.
Abstract