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Determinants of Commuting Time and Distance for Seoul Residents: The Impact of Family Status on the Commuting of Women

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  • Bun Song Lee

    (Bun Song Lee is in the Division of Economics, University of Seoul, 90 Jeonnong-dong, Dongdaemoon-ku, Seoul, Korea 130-743. Fax: 822 2210 5232. bunslee@hotmail.com)

  • John F. McDonald

    (Departments of Finance and Economics, University of Illinois at Chicago, College of Business Administration (MC 075), 601 S. Morgan Street, Chicago, IL 60607-7122, USA.mcdonald@uic.edu)

Abstract

This paper performs multiple regression analysis to identify a large number of determinants of commuting time and distance for Seoul residents using the 2 per cent public-use sample data tape of the 1995 Korean Population Census. Among the numerous findings, it is noted that commuting times and distances are longer for male workers, full-time salaried workers, workers with more education, home-owners and male workers in the prime earning years (over age 35). It is found that the household responsibility of childcare is an important factor for the shorter commuting of Korean married women.

Suggested Citation

  • Bun Song Lee & John F. McDonald, 2003. "Determinants of Commuting Time and Distance for Seoul Residents: The Impact of Family Status on the Commuting of Women," Urban Studies, Urban Studies Journal Limited, vol. 40(7), pages 1283-1302, June.
  • Handle: RePEc:sae:urbstu:v:40:y:2003:i:7:p:1283-1302
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    Cited by:

    1. Scheiner, Joachim, 2014. "Gendered key events in the life course: effects on changes in travel mode choice over time," Journal of Transport Geography, Elsevier, vol. 37(C), pages 47-60.
    2. Wang, Donggen & Chai, Yanwei, 2009. "The jobs–housing relationship and commuting in Beijing, China: the legacy of Danwei," Journal of Transport Geography, Elsevier, vol. 17(1), pages 30-38.
    3. Wynen, Jan, 2013. "Explaining travel distance during same-day visits," Tourism Management, Elsevier, vol. 36(C), pages 133-140.
    4. Feng, Jianxi & Dijst, Martin & Wissink, Bart & Prillwitz, Jan, 2013. "The impacts of household structure on the travel behaviour of seniors and young parents in China," Journal of Transport Geography, Elsevier, vol. 30(C), pages 117-126.
    5. Sharma, Ajay & Chandrasekhar, S., 2014. "Growth of the Urban Shadow, Spatial Distribution of Economic Activities, and Commuting by Workers in Rural and Urban India," World Development, Elsevier, vol. 61(C), pages 154-166.
    6. He, Mingwei & Zhao, Shengchuan & He, Min, 2016. "Tolerance threshold of commuting time: Evidence from Kunming, China," Journal of Transport Geography, Elsevier, vol. 57(C), pages 1-7.
    7. Manurl Frondel & Colin Vance, 2009. "On Marginal and Interaction Effects: The Case of Heckit and Two-Part Models," Ruhr Economic Papers 0138, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    8. Kawabata, Mizuki & Abe, Yukiko, 2018. "Intra-metropolitan spatial patterns of female labor force participation and commute times in Tokyo," Regional Science and Urban Economics, Elsevier, vol. 68(C), pages 291-303.
    9. Li, Mengya & Kwan, Mei-Po & Wang, Fahui & Wang, Jun, 2018. "Using points-of-interest data to estimate commuting patterns in central Shanghai, China," Journal of Transport Geography, Elsevier, vol. 72(C), pages 201-210.
    10. Hong, Sung Hyo & Lee, Bun Song & McDonald, John F., 2018. "Commuting time decisions for two-worker households in Korea," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 122-129.
    11. Gimenez-Nadal, J. Ignacio & Molina, José Alberto & Velilla, Jorge, 2020. "Trends in Commuting Time of European Workers: A Cross-Country Analysis," IZA Discussion Papers 12916, Institute of Labor Economics (IZA).
    12. Yang, Shuo & Fan, Yingling & Deng, Wei & Cheng, Long, 2019. "Do built environment effects on travel behavior differ between household members? A case study of Nanjing, China," Transport Policy, Elsevier, vol. 81(C), pages 360-370.
    13. Motte, Benjamin & Aguilera, Anne & Bonin, Olivier & Nassi, Carlos D., 2016. "Commuting patterns in the metropolitan region of Rio de Janeiro. What differences between formal and informal jobs?," Journal of Transport Geography, Elsevier, vol. 51(C), pages 59-69.
    14. Yingling Fan, 2017. "Household structure and gender differences in travel time: spouse/partner presence, parenthood, and breadwinner status," Transportation, Springer, vol. 44(2), pages 271-291, March.
    15. Shen, Yue & Kwan, Mei-Po & Chai, Yanwei, 2013. "Investigating commuting flexibility with GPS data and 3D geovisualization: a case study of Beijing, China," Journal of Transport Geography, Elsevier, vol. 32(C), pages 1-11.
    16. Mizuki Kawabata & Yukiko Abe, 2016. "Spatial dimensions of intra-metropolitan disparities in commuting time and female labor force participation," Keio-IES Discussion Paper Series 2016-024, Institute for Economics Studies, Keio University.
    17. Stefanie Kley & Sonja Drobnič, 2019. "Does moving for family nest-building inhibit mothers' labour force (re-)entry?," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 40(7), pages 155-184.
    18. Qin, Ping & Wang, Lanlan, 2019. "Job opportunities, institutions, and the jobs-housing spatial relationship: Case study of Beijing," Transport Policy, Elsevier, vol. 81(C), pages 331-339.
    19. Mercado, Ruben & Páez, Antonio, 2009. "Determinants of distance traveled with a focus on the elderly: a multilevel analysis in the Hamilton CMA, Canada," Journal of Transport Geography, Elsevier, vol. 17(1), pages 65-76.
    20. Shin, Eun Jin, 2019. "Self-employment and travel behavior: A case study of workers in central Puget Sound," Transport Policy, Elsevier, vol. 73(C), pages 101-112.
    21. repec:zbw:rwirep:0138 is not listed on IDEAS
    22. Subodh Dubey & Prateek Bansal & Ricardo A. Daziano & Erick Guerra, 2019. "A Generalized Continuous-Multinomial Response Model with a t-distributed Error Kernel," Papers 1904.08332, arXiv.org, revised Jan 2020.

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