Incorporating land use and pricing policies for reducing car dependence: Analytical framework and empirical evidence

Abstract

This article develops an analytical framework to connect the theories of market and planning failures with the reasoning of incorporating land use and pricing policies for reducing driving and car dependence. A multilevel multinomial logit model (MML) is applied to estimate the effects of neighbourhood land use characteristics and price variables on travel mode choice of non-work trips and their interaction effects in the city of Austin, Texas. Results reveal that pricing policies are more efficient for reducing auto travel while land use policies appear better for adjusting non-auto travel. The practical significance of land use policies for reducing car dependence are more reflected in the modified effects of land use on pricing elasticities of driving probability. Pricing policies are more effective for reducing driving in neighbourhoods with a higher sidewalk density and a better accessibility to mixed-use activity centres. These findings validate the theoretical analysis and demonstrate the importance of coordinating land use and pricing policies together in the transportation planning practice.