IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i10p3909-d1389762.html
   My bibliography  Save this article

Is Development Type a Determinant of College and Graduate Students’ Commute Time to School? The Case of Seoul Metropolitan Area

Author

Listed:
  • Sai-Zu Wang

    (Department of Urban and Regional Development Management, Hanyang University, Seoul 04763, Republic of Korea)

  • Chang-Gyu Choi

    (Department of Urban and Regional Development Management, Hanyang University, Seoul 04763, Republic of Korea)

Abstract

This study examines the impact of large-scale suburban new town development on the commuting time of college and graduate students in the Seoul Metropolitan Area. Household travel diary data from 2016 were analyzed to categorize residential areas and quantify the impacts on commute time to school. Multiple linear regression modeling is used to explore the relationships between development type, individual, and household characteristics and their impact on commute times. The results of the study show that students living in new urban areas have significantly longer commute times than those living in central Seoul, highlighting the differences that result from urban expansion policies targeting middle-class housing. These results suggest that the development of suburban new towns, which was intended to alleviate the housing shortage, has inadvertently lengthened the daily commute time of many students. Thus, a critical reassessment of suburban development strategies is needed to better balance the advantages of residential neighborhoods against the educational and living costs associated with increased travel time.

Suggested Citation

  • Sai-Zu Wang & Chang-Gyu Choi, 2024. "Is Development Type a Determinant of College and Graduate Students’ Commute Time to School? The Case of Seoul Metropolitan Area," Sustainability, MDPI, vol. 16(10), pages 1-16, May.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:10:p:3909-:d:1389762
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/10/3909/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/10/3909/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nash, Sean & Mitra, Raktim, 2019. "University students' transportation patterns, and the role of neighbourhood types and attitudes," Journal of Transport Geography, Elsevier, vol. 76(C), pages 200-211.
    2. 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.
    3. Rotaris, Lucia & Danielis, Romeo, 2014. "The impact of transportation demand management policies on commuting to college facilities: A case study at the University of Trieste, Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 127-140.
    4. Antonio Páez & Steven Farber, 2012. "Participation and desire: leisure activities among Canadian adults with disabilities," Transportation, Springer, vol. 39(6), pages 1055-1078, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bagdatli, Muhammed Emin Cihangir & Ipek, Fatima, 2022. "Transport mode preferences of university students in post-COVID-19 pandemic," Transport Policy, Elsevier, vol. 118(C), pages 20-32.
    2. Hossain, Sanjana & Loa, Patrick & Ong, Felita & Habib, Khandker Nurul, 2022. "The determinants of commute mode usage frequency of post-secondary students in the Greater Toronto and Hamilton Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 164-185.
    3. Aghaabbasi, Mahdi & Shekari, Zohreh Asadi & Shah, Muhammad Zaly & Olakunle, Oloruntobi & Armaghani, Danial Jahed & Moeinaddini, Mehdi, 2020. "Predicting the use frequency of ride-sourcing by off-campus university students through random forest and Bayesian network techniques," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 262-281.
    4. Leslie Cardoza Cedillo & Michelle Montoya & Mónica Jaldón & Ma Guadalupe Paredes, 2023. "GHG Emission Accounting and Reduction Strategies in the Academic Sector: A Case Study in Mexico," Sustainability, MDPI, vol. 15(12), pages 1-18, June.
    5. Stefan P.T. Groot & Henri L.F. de Groot & Paolo Veneri, 2012. "The Educational Bias in Commuting Patterns: Micro-Evidence for the Netherlands," Tinbergen Institute Discussion Papers 12-080/3, Tinbergen Institute.
    6. Beno Mesarec & Branka Trček, 2024. "Suggestions and Solutions for Enhancing Active Commuting to the University of Maribor and Advancing CO 2 Emission Reduction," Sustainability, MDPI, vol. 16(2), pages 1-21, January.
    7. Hui Zheng & Baohong He & Mingwei He & Jinghui Guo, 2022. "Impact of Urban Spatial Transformation on the Mobility of Commuters with Different Transportation Modes in China: Evidence from Kunming 2011–2016," Sustainability, MDPI, vol. 14(13), pages 1-22, June.
    8. J. Ignacio Gimenez-Nadal & José Alberto Molina, 2016. "Commuting Time And Household Responsibilities: Evidence Using Propensity Score Matching," Journal of Regional Science, Wiley Blackwell, vol. 56(2), pages 332-359, March.
    9. Rotaris, Lucia & Danielis, Romeo, 2015. "Commuting to college: The effectiveness and social efficiency of transportation demand management policies," Transport Policy, Elsevier, vol. 44(C), pages 158-168.
    10. 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.
    11. Kim, Sang-O & Palm, Matthew & Han, Soojung & Klein, Nicholas J., 2023. "Facing a time crunch: Time poverty and travel behaviour in Canada," SocArXiv z6tvd, Center for Open Science.
    12. Deeksha Tayal & Aasha Kapur Mehta, 2021. "Working Women, Delhi Metro and Covid-19: A Case Study in Delhi-NCR," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 64(2), pages 389-413, June.
    13. Na Ta & Zhilin Liu & Yanwei Chai, 2019. "Help whom and help what? Intergenerational co-residence and the gender differences in time use among dual-earner households in Beijing, China," Urban Studies, Urban Studies Journal Limited, vol. 56(10), pages 2058-2074, August.
    14. Thomas Skora & Heiko Rüger & Nico Stawarz, 2020. "Commuting and the Motherhood Wage Gap: Evidence from Germany," Sustainability, MDPI, vol. 12(14), pages 1-19, July.
    15. Butler, Alex & Sweet, Matthias, 2020. "No free rides: Winners and losers of the proposed Toronto Transit Commission U-Pass program," Transport Policy, Elsevier, vol. 96(C), pages 15-28.
    16. Isabelle Wachter & Christian Holz-Rau, 2022. "Gender differences in work-related high mobility differentiated by partnership and parenthood status," Transportation, Springer, vol. 49(6), pages 1737-1764, December.
    17. Huber, Martin & Meier, Jonas & Wallimann, Hannes, 2022. "Business analytics meets artificial intelligence: Assessing the demand effects of discounts on Swiss train tickets," Transportation Research Part B: Methodological, Elsevier, vol. 163(C), pages 22-39.
    18. 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.
    19. Olivieri, Cecilia & Fageda, Xavier, 2021. "Urban mobility with a focus on gender: The case of a middle-income Latin American city," Journal of Transport Geography, Elsevier, vol. 91(C).
    20. Jieun Lee & Igor Vojnovic & Sue C Grady, 2018. "The ‘transportation disadvantaged’: Urban form, gender and automobile versus non-automobile travel in the Detroit region," Urban Studies, Urban Studies Journal Limited, vol. 55(11), pages 2470-2498, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:10:p:3909-:d:1389762. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.