Skip to main content

Advertisement

SpringerLink
Log in

What neighborhood are you in? Empirical findings of relationships between household travel and neighborhood characteristics

  • Published:
Transportation Aims and scope Submit manuscript

Abstract

In recent years, there have been studies of the influence of neighborhood or built environment characteristics on residential location choice and household travel behavior. Interestingly, there is no uniform definition of neighborhood in the literature and the definition is often vague. This paper presents an alternative way of defining neighborhood and neighborhood type, which involves innovative usage of public data sources. Furthermore, the paper investigates the interaction between neighborhood environment and household travel in the US. A neighborhood here is spatially identical to a census tract. A neighborhood type identifies a group of neighborhoods with similar neighborhood socio-economic, demographic, and land use characteristics. This is accomplished by performing log-likelihood clustering on the Census Transportation Planning Package (CTPP) 2000 data. Five household travel measures, i.e., number of trips per household, mode share, average travel distance and time per trip, and vehicle miles of travel (VMT), are then compared across the resulting 10 neighborhood types, using the 2001 National Household Travel Survey (NHTS) household and trip files. It is found that household life cycle status and residential location are not independent. Transit availability at place of residence tends to increase the transit mode share regardless of household automobile ownership and income level, and job-housing trade-offs are evident when mobility is not of concern. The study also reveals racial preference in residential location and contrasting travel characteristics among ethnic groups.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. CTPP is a set of special tabulations of household/individual and commute trip attributes derived from the long form of decennial census at various geographic levels. It has three parts of surveyed information for place of residence (Part I), place of work (Part II), and journey to work (Part III).

  2. Census-tract and census-block-group geocoded National Household Travel Survey (NHTS) data were provided by the Federal Highway Administration (FHWA) for our study.

  3. The common variables in the CTPP and the NHTS have been recoded to have exactly the same levels or categories. Those variables are race/ethnicity, income, age, and occupation. As summarized in Table 1, race/ethnicity was recoded to eight categories; household income to 15 levels; age to six levels and occupation five categories in both data sets.

  4. The nine add-ons are: Baltimore, MD, Des Moines, IA, Edmonson, Carter, Pulaski, and Scott Counties, KY, Lancaster, PA, Oahu, HIi, State of Hawaii except Oahu, State of New York, State of Texas, and State of Wisconsin.

References

  • Bagley, M.N., Mokhtarian, P.L.: The impact of residential neighborhood type on travel behavior: a structural equations modeling approach. Ann. Reg. Sci. 36, 279–297 (2002)

    Article  Google Scholar 

  • Bhat, R.C.: A multi-level cross-classified model for discrete response variables. Transp. Res. Part B 34, 567–582 (2000)

    Article  Google Scholar 

  • Blumenberg, E., Ong, P.: Cars, buses, and jobs: welfare participants and employment access in Los Angeles. Transp. Res. Rec., J. Transp. Res. Board 1756, 22–31 (2001)

    Article  Google Scholar 

  • Boarnet, M.G., Crane, R.: Travel by Design: The Influence of Urban Form on Travel. Oxford University Press, Oxford (2001)

    Google Scholar 

  • Burgess, J.F. Jr., Christiansen, C.L., Michalak, S.E., Morris, C.N.: Medical profiling: improving standards and risk adjustments using hierarchical models. J. Health Econ. 19(3), 291–309 (2000)

    Article  Google Scholar 

  • Cao, X., Handy, S.L., Mokhtarian, P.L.: The influences of the built environment and residential self-selection on pedestrian behavior: evidence from Austin, TX. Transportation 33, 1–20 (2006)

    Article  Google Scholar 

  • Cao, X., Mokhtarian, P.L., Handy, S.L.: Cross-sectional and quasi-panel explorations of the connection between the built environment and auto ownership. Environ. Plan. A 39, 830–847 (2007)

    Article  Google Scholar 

  • Cervero, R., Radisch, C.: Pedestrian versus automobile oriented neighborhoods. Transp. Policy 3, 127–141 (1996)

    Article  Google Scholar 

  • Chiu, T., Fang, D., Chen, J., Wang, Y., Jeris, C.: A robust and scalable clustering algorithm for mixed type attributes in large database environment. In: Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, vol. 263 (2001)

  • Chu, X., Polzin, S.E., Rey, J.R., Hill, E.T.: Mode Choice by People of Color for Non-Work Travel: Findings from the Nationwide Personal Transportation Surveys in Travel Patterns of People of Color. Prepared for the Federal Highway Administration by Battelle Memorial Institute, Columbus, Ohio, June (2000)

  • Clifton, K., Handy, S.: Limits on access in low-income neighborhoods and the travel patterns of low-income households. Research report 167502-1. Southwest Region University Transportation Center, Texas Transportation Institute, College Station, Texas (2001)

  • Crane, R., Crepeau, R.: Does neighborhood design influence travel? A behavioral analysis of travel diary and GIS data. Transp. Res. Part D 3(4), 225–238 (1998)

    Article  Google Scholar 

  • Dietz, R.D.: The estimation of neighborhood effects in the social sciences: an interdisciplinary approach. Soc. Sci. Res. 31, 539–575 (2002)

    Article  Google Scholar 

  • Galster, G.: On the nature of neighborhood. Urban Stud. 38(12), 2111–2124 (2001)

    Article  Google Scholar 

  • Giuliano, G.: Residential Location Differences in People of Color, in Travel Patterns of People of Color. Prepared for the Federal Highway Administration by Battelle Memorial Institute, Columbus, Ohio (2000)

  • Golab, C.: The geography of the neighborhood. In: Bayer, R. (ed.) Neighborhoods in Urban America, pp. 70–85. Kennikat, Port Washington (1982)

    Google Scholar 

  • Goodman, A.C., Thibodeau, T.G.: Housing market segmentation. J. Hous. Econ. 7(2), 121–143 (1998)

    Article  Google Scholar 

  • Greenland, S.: Principles of multilevel modeling. Int. J. Epidemiol. 29, 158–167 (2000)

    Article  Google Scholar 

  • Guo, J.Y., Bhat, C.R.: Operationalizing the concept of neighborhood: application to residential location choice analysis. J. Transp. Geogr. 15, 31–45 (2007)

    Article  Google Scholar 

  • Hallman, H.W.: Neighborhoods: Their Place in Urban Life. Sage Publications, Beverly Hills (1984)

    Google Scholar 

  • Keller, S.: The Urban Neighborhood. Random House, New York (1968)

    Google Scholar 

  • Khattak, A.J., Rodriguez, D.: Travel behavior in neo-traditional neighborhood developments: a case study in USA. Transp. Res. Part A 39, 481–500 (2005)

    Google Scholar 

  • Khattak, A.J., Amerlynck, V.J., Quercia, R.G.: Are travel times and distances to work greater for residents of poor urban neighborhoods? Transportation research record. J. Trans. Res. Board 1718, 73–82 (2000)

    Article  Google Scholar 

  • Kitamura, R., Mokhtarian, P.L., Laidet, L.: A micro-analysis of land use and travel in five neighborhoods in the San Francisco bay area. Transportation 24, 125–158 (1997)

    Article  Google Scholar 

  • Krizek, K.J.: Residential relocation and changes in urban travel: does neighborhood-scale urban form matter? J. Am. Plan. Assoc. 69, 125–158 (2003)

    Article  Google Scholar 

  • Morris, D., Hess, K.: Neighborhood Power. Beacon Press, Boston (1975)

    Google Scholar 

  • Nunes Amaral, L.A., Buldyrev, S.V., Havlin, S., Maass, P., Salinger, M.A., Stanley, H.E., Stanley, M.H.R.: Scaling behavior in economics: the problem of quantifying company growth. Phys. A: Statist. Theor. Phys. 244(1–4), 1–24 (1997)

    Article  Google Scholar 

  • Openshaw, S.: Concepts and Techniques in Modern Geography: Number 38 – The Modifiable Areal Unit Problem. Geo Books, Norwick (1984)

  • Polzin, S., Chu, X., Rey, J.R.: Demographics of People of Color: Findings from the Nationwide Personal Transportation Survey, in Travel Patterns of People of Color. Prepared for the Federal Highway Administration by Battelle Memorial Institute, Columbus, Ohio (2000)

  • Pucher, J., Renne, J.L.: Rural mobility and mode choice: evidence from the 2001 National Household Travel Survey. Transportation 32, 165–186 (2005)

    Article  Google Scholar 

  • Rodriguez, D.A., Khattak, A.J., Evenson, K.R.: Can new urbanism encourage physical activity? Comparing a new urbanist neighborhood with conventional suburbs. J. Am. Plan. Assoc. 72(1), 43–54 (2006)

    Article  Google Scholar 

  • Sampson, R.J., Morenoff, J.D., Gannon-Rowley, T.: Assessing ‘neighborhood effects’: social processes and new directions in research. Annu. Rev. Sociol. 28, 443–478 (2002)

    Article  Google Scholar 

  • Schoenberg, S.: Criteria for the evaluation of neighborhood viability in working class and low income areas in core cities. Social Probl. 27, 69–85 (1979)

    Article  Google Scholar 

  • Schwanen, T., Mokhtarian, P.L.: What if you live in the wrong neighborhood? The impact of residential neighborhood type dissonance on distance traveled. Transp. Res. Part D 10, 127–151 (2005)

    Article  Google Scholar 

  • Sermons, M.W., Seredich, N.: Assessing traveler responsiveness to land and location based accessibility and mobility solutions. Transp. Res. Part D 6, 417–428 (2001)

    Article  Google Scholar 

  • Singer, J.D.: Using SAS PROC MIXED to fit multilevel models, hierarchical models, and individual growth models. J. Educ. Behav. Statist. 24(4), 323–355 (1998)

    Google Scholar 

Download references

Acknowledgements

This study was funded by the Federal Highway Administration (FHWA). We thank Susan Liss, Nanda Srinivasan, Nancy Mcguckin, and Ed Christopher from FHWA for their support of the study and comments on the analysis. We also thank the anonymous reviewers and the editor for their valuable comments and suggestions.

Author information

Authors and Affiliations

  1. Department of Civil and Materials Engineering, Institute of Environmental Science and Policy, University of Illinois at Chicago, 842 W. Taylor St. (MC246), Chicago, IL, 60607, USA

    Jie Lin

  2. Cambridge Systematics, Inc., 555 12th Street, Suite 1600, Oakland, CA, 94607, USA

    Liang Long

Authors
  1. Jie Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Liang Long
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jie Lin.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lin, J., Long, L. What neighborhood are you in? Empirical findings of relationships between household travel and neighborhood characteristics. Transportation 35, 739–758 (2008). https://doi.org/10.1007/s11116-008-9167-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11116-008-9167-7

Keywords

Search

Navigation