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Disaggregate Journey-to-Work Data: Implications for Excess Commuting and Jobs–Housing Balance

Author

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  • Morton E O'Kelly

    (Department of Geography, Ohio State University, 1036 Derby Hall, 154 North Oval Mall, Columbus, OH 43210-1361, USA)

  • Wook Lee

    (Department of Geography, Texas Center for Geographic Information Science, Texas State University—San Marcos, 601 University Drive, San Marcos, TX 78666-4616, USA)

Abstract

Much of the analysis to date on the topic of excess commuting and jobs–housing balance deals with total commuting flow, undifferentiated with respect to worker and job characteristics. In this paper we explicitly address the disaggregation issue in terms of job and worker heterogeneity and show how to incorporate such details into the analysis of excess commuting. The objectives of this paper are (1) to develop a trip-distribution model disaggregating journey-to-work data according to type of occupation in order to estimate actual commutes; (2) to develop a disaggregated version of a linear program to measure theoretical minimum and maximum commutes; and, (3) to verify variations in excess commuting and jobs–housing balance according to type of occupation. Results of actual trip-length distributions for each occupation vary from 3.72 to 5 miles for Boise, Idaho, and from 4.27 to 7.78 miles for Wichita, Kansas. Minimum commutes vary from 0.95 to 3.58 miles and from 1.5 to 3.79 miles for Boise and Wichita, respectively. These results imply nonuniform levels of excess commuting and jobs/workers ratios. The proposed models are expected to have a wide range of uses in measurement and assessment of empirical patterns of commuting. The scope of the disaggregation can be extended to other targets, such as different types of industry, household structure, income level, ethnic background, education level, transportation mode, and gender. Further dimensions of disaggregation can address spatial interactions of different socioeconomic groups in urban areas, and, more generally, contribute to exploring urban sprawl according to job characteristics and industries.

Suggested Citation

  • Morton E O'Kelly & Wook Lee, 2005. "Disaggregate Journey-to-Work Data: Implications for Excess Commuting and Jobs–Housing Balance," Environment and Planning A, , vol. 37(12), pages 2233-2252, December.
    • Handle: RePEc:sae:envira:v:37:y:2005:i:12:p:2233-2252
    DOI: 10.1068/a37312
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    References listed on IDEAS

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    1. Stuart Sweeney, 1999. "Model-based incomplete data analysis with an application to occupational mobility and migration accounts," Mathematical Population Studies, Taylor & Francis Journals, vol. 7(3), pages 279-305.
    2. Genevieve Giuliano & Kenneth A. Small, 1993. "Is the Journey to Work Explained by Urban Structure?," Urban Studies, Urban Studies Journal Limited, vol. 30(9), pages 1485-1500, November.
    3. David Merriman & Toru Ohkawara & Tsutomu Suzuki, 1995. "Excess Commuting in the Tokyo Metropolitan Area: Measurement and Policy Simulations," Urban Studies, Urban Studies Journal Limited, vol. 32(1), pages 69-85, February.
    4. Mark Horner & Alan Murray, 2003. "A Multi-objective Approach to Improving Regional Jobs-Housing Balance," Regional Studies, Taylor & Francis Journals, vol. 37(2), pages 135-146.
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    Citations

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    Cited by:

    1. Sung, Hyungun, 2023. "Multi-scale moderation impacts of jobs and housing balancing on sustainable commuting behavior in Seoul," Journal of Transport Geography, Elsevier, vol. 110(C).
    2. Michael A. Niedzielski, 2006. "A Spatially Disaggregated Approach to Commuting Efficiency," Urban Studies, Urban Studies Journal Limited, vol. 43(13), pages 2485-2502, December.
    3. Mark W Horner & Jessica N Mefford, 2007. "Investigating Urban Spatial Mismatch Using Job–Housing Indicators to Model Home–Work Separation," Environment and Planning A, , vol. 39(6), pages 1420-1440, June.
    4. Jiawen Yang, 2008. "Policy Implications of Excess Commuting: Examining the Impacts of Changes in US Metropolitan Spatial Structure," Urban Studies, Urban Studies Journal Limited, vol. 45(2), pages 391-405, February.
    5. Goliszek Sławomir & Połom Marcin & Duma Patryk, 2020. "Potential and cumulative accessibility of workplaces by public transport in Szczecin," Bulletin of Geography. Socio-economic Series, Sciendo, vol. 50(50), pages 133-146, December.
    6. Li, Yongling & Geertman, Stan & Hooimeijer, Pieter & Lin, Yanliu & Yang, Haoran & Yang, Linchuan, 2022. "Interaction effects of socioeconomic factors on long-distance commuting after disentangling residential self-selection: An empirical study in Xiamen, China," Journal of Transport Geography, Elsevier, vol. 105(C).
    7. Mark W. Horner & Bernadette M. Marion, 2009. "A Spatial Dissimilarity-based Index of the Jobs—Housing Balance: Conceptual Framework and Empirical Tests," Urban Studies, Urban Studies Journal Limited, vol. 46(3), pages 499-517, March.
    8. Mark W. Horner, 2008. "`Optimal' Accessibility Landscapes? Development of a New Methodology for Simulating and Assessing Jobs—Housing Relationships in Urban Regions," Urban Studies, Urban Studies Journal Limited, vol. 45(8), pages 1583-1602, July.
    9. Kim, Kyusik & Horner, Mark W., 2021. "Examining the impacts of the Great Recession on the commuting dynamics and jobs-housing balance of public and private sector workers," Journal of Transport Geography, Elsevier, vol. 90(C).
    10. Liying Yue & Morton E. O’Kelly, 2023. "Rents and wages derived from spatial interaction analysis in Shanghai," Journal of Geographical Systems, Springer, vol. 25(1), pages 59-75, January.
    11. Morton E O'Kelly & Michael A Niedzielski, 2009. "Are Long Commute Distances Inefficient and Disorderly?," Environment and Planning A, , vol. 41(11), pages 2741-2759, November.
    12. Dominik Papinski & Darren M Scott, 2013. "Route Choice Efficiency: An Investigation of Home-To-Work Trips Using GPS Data," Environment and Planning A, , vol. 45(2), pages 263-275, February.
    13. Yue, Liying & O'Kelly, Morton E., 2023. "Variations in excess commuting by educational and occupational worker subgroups: A case study of Shanghai," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    14. Goliszek Sławomir, 2022. "The potential accessibility to workplaces and working-age population by means of public and private car transport in Szczecin," Miscellanea Geographica. Regional Studies on Development, Sciendo, vol. 26(1), pages 31-41, January.
    15. Matt Kures & Steven C. Deller, 2023. "Growth in Commuting Patterns and Their Impacts on Rural Workforce and Economic Development," Economic Development Quarterly, , vol. 37(1), pages 54-63, February.
    16. Jie Huang & David Levinson & Jiaoe Wang & Haitao Jin, 2019. "Job-worker spatial dynamics in Beijing: Insights from Smart Card Data," Working Papers 2019-01, University of Minnesota: Nexus Research Group.
    17. Woo Jang & Fei Yuan & Jose Javier Lopez, 2021. "Investigating Sustainable Commuting Patterns by Socio-Economic Factors," Sustainability, MDPI, vol. 13(4), pages 1-14, February.

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