Do Neighborhood Attributes Affect Commuting Times?

Details

• Creators:
  Gordon, Peter ; Lee, Bumsoo ; Moore, James E., II ; Richardson, Harry W.
• Corporate Creators:
  METRANS Transportation Center (Calif.) ; University of Southern California. School of Policy, Planning, and Development ; California. Dept. of Transportation. Division of Research and Innovation
• Corporate Contributors:
  United States. Department of Transportation. Research and Special Programs Administration
• Subject/TRT Terms:
  • Commuting
  • Neighborhoods
  • Metropolitan areas
  • Data analysis
  • Labor force
  • Residential areas
  • Business districts
  • Transportation planning
• Publication/ Report Number:
  FHWA/CA/OR-2006/04;04-13-2006-4
• Resource Type:
  Research Paper
• Geographical Coverage:
  California
• Corporate Publisher:
  METRANS Transportation Center (Calif.)
• Abstract:
  Can generic neighborhood types for California’s major metropolitan areas be defined? To what extent do neighborhood differences affect commuting times? Using census data, including TIGER file variables that describe street patterns and transit and highway accessibility, we found that there are identifiable residential as well as workplace neighborhood types observable throughout the four major California metropolitan areas. We also found that many of these had consistent effects on commuting durations across the four areas. In most cases, neighborhood effects helped to explain a longer commute than could be explained by a generalized accessibility index. Many households trade off desirable neighborhood characteristics (at work and/or at home) for a longer commute. All things considered, jobs-housing “balance” is, apparently, not high on most people’s agenda.
• Format:
  PDF
• Funding:
  65A0047;METRANS Project 04-13
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/57476/dot_57476_DS1.pdf
• File Type:
  [PDF - 1.64 MB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:9e0c3b70e2c361c8471d42e608c8e39bda552c99639bf296aa09ec52d35a9637d0df1f0e3fef8c4409a0e7b0c6aafadaf1f7cf58210c65a85a6378437eaa6cb7