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A Methodology for the Disaggregate, Multidimensional Measurement of Residential Neighbourhood Type

Author

Listed:
  • Michael N. Bagley

    (South Texas Community College, PO Box 9701, McAllen, Texas 78502 9701, USA, mnbagley@stcc.cc.tx.us)

  • Patricia L. Mokhtarian

    (Institute of Transport Studies, University of Cakfornia, Davis, California 95616, USA, plmokhtarian@ucdavis.edu)

  • Ryuichi Kitamura

    (Department of Transport Engineering, Kyoto University, Sakyo-ku, Kyoto 606, Japan, rkitamura@term.kuciv.kyoto-u.ac.jp)

Abstract

Binary designation of a residential neighbourhood as either traditional or suburban is a distortion of reality, since a location may have some characteristics of both types and since residents in different parts of the neighbourhood may perceive its character differently. This paper presents and applies a methodology for assessing neighbourhood type that results in a measure that is continuous rather than binary, disaggregate rather than aggregate, and potentially multidimensional. Specifically, 18 variables identified by the literature as distinguishing traditional and suburban locations are measured for 852 residents of 5 San Francisco area neighbourhoods. These data are factor-analysed to develop scales on which each individual has a person-specific score. Although we expected a single 'traditionalness' dimension to result, instead we found two factors: traditional and suburban. Study neighbourhoods could and did score highly on both dimensions, and considerable individual variation within neighbourhood was observed. By more accurately capturing the complexity in classifying a neighbourhood and the heterogeneity of individual perception within a neighbourhood, use of this methodology to measure neighbourhood type is expected to improve models involving residential location as an endogenous or exogenous variable.

Suggested Citation

  • Michael N. Bagley & Patricia L. Mokhtarian & Ryuichi Kitamura, 2002. "A Methodology for the Disaggregate, Multidimensional Measurement of Residential Neighbourhood Type," Urban Studies, Urban Studies Journal Limited, vol. 39(4), pages 689-704, April.
    • Handle: RePEc:sae:urbstu:v:39:y:2002:i:4:p:689-704
    DOI: 10.1080/00420980220119525
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    References listed on IDEAS

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    Cited by:

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    4. Kees Maat & Paul de Vries, 2006. "The Influence of the Residential Environment on Green-Space Travel: Testing the Compensation Hypothesis," Environment and Planning A, , vol. 38(11), pages 2111-2127, November.
    5. Aiga Stokenberga, 2019. "How family networks drive residential location choices: Evidence from a stated preference field experiment in Bogotá, Colombia," Urban Studies, Urban Studies Journal Limited, vol. 56(2), pages 368-384, February.
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    7. Dick Ettema, 2010. "The impact of telecommuting on residential relocation and residential preferences: A latent class modelling approach," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 3(1), pages 7-24.
    8. Patterson, Zachary & Saddier, Simon & Rezaei, Ali & Manaugh, Kevin, 2014. "Use of the Urban Core Index to analyze residential mobility: the case of seniors in Canadian metropolitan regions," Journal of Transport Geography, Elsevier, vol. 41(C), pages 116-125.
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    11. Christopher Harding & Zachary Patterson & Luis F Miranda-Moreno & Seyed Amir Zahabi, 2014. "A Spatial and Temporal Comparative Analysis of the Effects of Land-Use Clusters on Activity Spaces in Three Quebec Cities," Environment and Planning B, , vol. 41(6), pages 1044-1062, December.
    12. Popovich, Natalie & Spurlock, C. Anna & Needell, Zachary & Jin, Ling & Wenzel, Tom & Sheppard, Colin & Asudegi, Mona, 2021. "A methodology to develop a geospatial transportation typology," Journal of Transport Geography, Elsevier, vol. 93(C).
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