Influence of neighborhood types on trip distances: Spatial error models for Central Ohio

Abstract

ABSTRACTThis study examines the relationships between land-use, transportation infrastructure, household, and individual characteristics and the resulting average and daily trip distances using data from the 1999 Mid-Ohio Area Household Travel Survey. Spatial error models are developed to analyze the determinants of average and daily trip distances at the person level. First, new neighborhood categories are created using K-means cluster analysis and several land-use and built-environment variables. Then, these new neighborhood categories (such as central city residential areas, medium-density suburbs, low-density suburbs, etc.) are used as independent variables to explain the resulting average and total trip distances, while controlling for sociodemographics, access to transit and bicycle facilities, and spatial autocorrelation. The results indicate that the residential location characteristics are a significant factor in explaining trip distances; people who live in areas that are away from urban centers and with a low mix of employment and population travel longer distances. For the Central Ohio Region, residing in lowest-density suburbs may add up to 44% to average trip distances and 33% to daily trip distances.