Commuting Mode Choice in a High-Density City: Do Land-Use Density and Diversity Matter in Hong Kong?

Int J Environ Res Public Health. 2018 May 4;15(5):920. doi: 10.3390/ijerph15050920.

Abstract

Hong Kong is a densely populated and transit-oriented Chinese city, which provides an ideal urban environment with which to study the various successful facets of land use policy as a model for potential replication to curb increasing car use in other Chinese cities. We examine the commuting mode choice of 203,900 households living in 4768 street blocks in Hong Kong from 2011 census. A street block is the smallest planning unit, made up of one or more housing estates with a homogenous built environment and socioeconomic status. The built environment is measured using the five Ds framework, an international dimensioning framework for classifying and measuring attributes of the built environment for physical activity and travel behaviors. Generalized, multi-level mixed models were applied to detect the associations between travel choice and built environment characteristics, while adjusting for socioeconomic status. Design and destination accessibility had greater effects on the choices to walk and take public transport than on the choice to drive. Density and diversity had only marginal effects on mode choice. Unexpectedly, distance to the urban center had the opposite effect on automobile use to that found in Western studies. Hong Kong residents living close to the urban center were more likely to drive for commuting trips. The contrasting findings between our study and Western studies suggest that the associations between a high-density built environment and travel choice vary with urban context.

Keywords: built environment; commuting trips; high density; land use policy; travel choice; urban design.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cities
  • Cross-Sectional Studies
  • Environment Design*
  • Exercise
  • Female
  • Hong Kong
  • Humans
  • Male
  • Residence Characteristics / statistics & numerical data*
  • Social Class
  • Transportation / statistics & numerical data*
  • Walking