IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i16p4432-d258203.html
   My bibliography  Save this article

Study of the School–Residence Spatial Relationship and the Characteristics of Travel-to-School Distance in Shenyang

Author

Listed:
  • Dawei Mei

    (School of Geographical Sciences, Northeast Normal University, Changchun 130024, Jilin, China)

  • Chunliang Xiu

    (College of Jang Ho Architecture, Northeastern University, Shenyang 110169, Liaoning, China)

  • Xinghua Feng

    (School of Geographical Sciences, Northeast Normal University, Changchun 130024, Jilin, China)

  • Ye Wei

    (School of Geographical Sciences, Northeast Normal University, Changchun 130024, Jilin, China)

Abstract

The school–residence spatial relationship is a key factor in understanding urban spatial structure and travel-to-school behavior of students. Analyzing the change law and the spatial characteristics of travel-to-school distance can provide a basis for improved accessibility of urban educational facilities and enable enrolment of students from the neighborhood. Based on one complete month of mobile phone signaling data for May 2018, the changes in student density with the travel-to-school distance was analyzed using MATLAB and Mann–Kendall Trend Test, and the pattern and the spatial structure of travel-to-school were explored. The results revealed that: (1) With increase in travel-to-school distance, the student density showed a decrease in truncated power law distribution, and it is concentrated within the travel-to-school distance of 5.0 km; (2) According to the sudden change points of the student density growth rate, the threshold distance for travel to kindergartens is 1.30 km, and for primary schools and secondary schools is 1.50 km. The school–residence spatial structure is divided according to the threshold of travel-to-school distance and the scope of attendance; (3) The dominant flow of travel-to-school is generally from urban peripheral and marginal areas to the urban core area, and partly from marginal areas to peripheral areas; (4) The pattern of travel-to-school is polycentric, and the study centers are mainly located in the urban central district north of the Hun River. The urban core area has the strongest attraction of students, while the marginal area has the weakest.

Suggested Citation

  • Dawei Mei & Chunliang Xiu & Xinghua Feng & Ye Wei, 2019. "Study of the School–Residence Spatial Relationship and the Characteristics of Travel-to-School Distance in Shenyang," Sustainability, MDPI, vol. 11(16), pages 1-15, August.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:16:p:4432-:d:258203
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/16/4432/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/16/4432/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fack, Gabrielle & Grenet, Julien, 2010. "When do better schools raise housing prices? Evidence from Paris public and private schools," Journal of Public Economics, Elsevier, vol. 94(1-2), pages 59-77, February.
    2. Easton, Sue & Ferrari, Ed, 2015. "Children's travel to school—the interaction of individual, neighbourhood and school factors," Transport Policy, Elsevier, vol. 44(C), pages 9-18.
    3. 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.
    4. Zhou, Xingang & Yeh, Anthony G.O. & Yue, Yang, 2018. "Spatial variation of self-containment and jobs-housing balance in Shenzhen using cellphone big data," Journal of Transport Geography, Elsevier, vol. 68(C), pages 102-108.
    5. Larsen, K. & Gilliland, J. & Hess, P. & Tucker, P. & Irwin, J. & He, M., 2009. "The influence of the physical environment and sociodemographic characteristics on children's mode of travel to and from school," American Journal of Public Health, American Public Health Association, vol. 99(3), pages 520-526.
    6. Junjian Yi & Kee Lee Chou & Linda Yung & Junsen Zhang, 2015. "Public Housing, School Segregation, and Children's Education: Evidence from Hong Kong," Frontiers of Economics in China-Selected Publications from Chinese Universities, Higher Education Press, vol. 10(3), pages 414-448, September.
    7. Imberman, Scott A. & Lovenheim, Michael F., 2016. "Does the market value value-added? Evidence from housing prices after a public release of school and teacher value-added," Journal of Urban Economics, Elsevier, vol. 91(C), pages 104-121.
    8. Bouzarth, Elizabeth L. & Forrester, Richard & Hutson, Kevin R. & Reddoch, Lattie, 2018. "Assigning students to schools to minimize both transportation costs and socioeconomic variation between schools," Socio-Economic Planning Sciences, Elsevier, vol. 64(C), pages 1-8.
    9. Müller, Sven & Tscharaktschiew, Stefan & Haase, Knut, 2008. "Travel-to-school mode choice modelling and patterns of school choice in urban areas," Journal of Transport Geography, Elsevier, vol. 16(5), pages 342-357.
    10. Malczewski, Jacek & Jackson, Marlene, 2000. "Multicriteria spatial allocation of educational resources: an overview," Socio-Economic Planning Sciences, Elsevier, vol. 34(3), pages 219-235, September.
    11. Agarwal, Sumit & Rengarajan, Satyanarain & Sing, Tien Foo & Yang, Yang, 2016. "School allocation rules and housing prices: A quasi-experiment with school relocation events in Singapore," Regional Science and Urban Economics, Elsevier, vol. 58(C), pages 42-56.
    12. Marique, Anne-Francoise & Dujardin, Sébastien & Teller, Jacques & Reiter, Sigrid, 2013. "School commuting: the relationship between energy consumption and urban form," Journal of Transport Geography, Elsevier, vol. 26(C), pages 1-11.
    13. Cheng, Lin & Chen, Chen & Xiu, Chunliang, 2017. "Excess kindergarten travel in Changchun, Northeast China: A measure of residence-kindergarten spatial mismatch," Journal of Transport Geography, Elsevier, vol. 60(C), pages 208-216.
    14. Broberg, Anna & Sarjala, Satu, 2015. "School travel mode choice and the characteristics of the urban built environment: The case of Helsinki, Finland," Transport Policy, Elsevier, vol. 37(C), pages 1-10.
    15. John Ries & Tsur Somerville, 2010. "School Quality and Residential Property Values: Evidence from Vancouver Rezoning," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 928-944, November.
    16. Qiyan Wu & Xiaoling Zhang & Paul Waley, 2016. "Jiaoyufication: When gentrification goes to school in the Chinese inner city," Urban Studies, Urban Studies Journal Limited, vol. 53(16), pages 3510-3526, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Qiya Huang & Xijuan Cui & Libang Ma, 2023. "The Equity of Basic Educational Facilities from the Perspective of Space," Sustainability, MDPI, vol. 15(15), pages 1-16, August.
    2. Hu, Yujie & Sherlock, Phillip & Huang, Jing & Knopf, Herman T. & Hall, Jaclyn M., 2024. "Unveiling spatial mismatch in childcare supply and demand: An excess commuting analysis of home-to-childcare distance in subsidized families," Journal of Transport Geography, Elsevier, vol. 116(C).
    3. Cong Liao & Teqi Dai, 2022. "Is “Attending Nearby School” Near? An Analysis of Travel-to-School Distances of Primary Students in Beijing Using Smart Card Data," Sustainability, MDPI, vol. 14(7), pages 1-12, April.
    4. Pizzol, Bruna & Giannotti, Mariana & Tomasiello, Diego Bogado, 2021. "Qualifying accessibility to education to investigate spatial equity," Journal of Transport Geography, Elsevier, vol. 96(C).
    5. Huasheng Liu & Haoran Deng & Yu Li & Yuqi Zhao & Xiaowen Li, 2022. "School Surrounding Region Traffic Commuting Analysis Based on Simulation," IJERPH, MDPI, vol. 19(11), pages 1-25, May.
    6. Guoqiang Shen & Zhangye Wang & Long Zhou & Yu Liu & Xiaoyi Yan, 2020. "Home-Based Locational Accessibility to Essential Urban Services: The Case of Wake County, North Carolina, USA," Sustainability, MDPI, vol. 12(21), pages 1-21, November.

    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. Rajapaksa, Darshana & Gono, Marcel & Wilson, Clevo & Managi, Shunsuke & Lee, Boon & Hoang, Viet-Ngu, 2020. "The demand for education: The impacts of good schools on property values in Brisbane, Australia," Land Use Policy, Elsevier, vol. 97(C).
    2. Li, Man & Wang, Yupeng & Zhou, Dian, 2023. "Effects of the built environment and sociodemographic characteristics on Children's school travel," Transport Policy, Elsevier, vol. 134(C), pages 191-202.
    3. Wati, Kala & Tranter, Paul J., 2015. "Spatial and socio-demographic determinants of South East Queensland students’ school cycling," Journal of Transport Geography, Elsevier, vol. 47(C), pages 23-36.
    4. Xiaofeng Ji & Haotian Guan & Mengyuan Lu & Fang Chen & Wenwen Qin, 2022. "International Research Progress in School Travel and Behavior: A Literature Review and Bibliometric Analysis," Sustainability, MDPI, vol. 14(14), pages 1-25, July.
    5. Müller, Sven & Mejia-Dorantes, Lucia & Kersten, Elisa, 2020. "Analysis of active school transportation in hilly urban environments: A case study of Dresden," Journal of Transport Geography, Elsevier, vol. 88(C).
    6. Melser, Daniel & Moallemi, Morteza & Kim, Jun Sung, 2021. "Preferences for single-sex schools: Evidence from the housing market," Journal of Economic Behavior & Organization, Elsevier, vol. 189(C), pages 710-726.
    7. Xuejuan Su & Huayi Yu, 2022. "Valuing elementary schools: evidence from public school acquisitions in Beijing," Scandinavian Journal of Economics, Wiley Blackwell, vol. 124(4), pages 1117-1141, October.
    8. Crocker H. Liu & Patrick S. Smith, 2023. "School quality as a catalyst for bidding wars and new housing development," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 51(4), pages 785-818, July.
    9. Su, Xuejuan & Yu, Huayi, 2019. "How Much are Good Schools Worth? Evidence from School Acquisitions in Beijing," Working Papers 2019-12, University of Alberta, Department of Economics.
    10. Kang Mo Koo & Jerry Liang, 2021. "The Effect of Bilingual Education on Housing Price-a Case Study of Bilingual School Conversion," The Journal of Real Estate Finance and Economics, Springer, vol. 62(4), pages 629-664, May.
    11. Alireza Ermagun & Amir Samimi, 2018. "Mode choice and travel distance joint models in school trips," Transportation, Springer, vol. 45(6), pages 1755-1781, November.
    12. Chen, Peng & Jiao, Junfeng & Xu, Mengyuan & Gao, Xu & Bischak, Chris, 2018. "Promoting active student travel: A longitudinal study," Journal of Transport Geography, Elsevier, vol. 70(C), pages 265-274.
    13. Zhang, Rui & Yao, Enjian & Liu, Zhili, 2017. "School travel mode choice in Beijing, China," Journal of Transport Geography, Elsevier, vol. 62(C), pages 98-110.
    14. Yuta Kuroda, 2022. "What does the disclosure of school quality information bring? The effect through the housing market," Journal of Regional Science, Wiley Blackwell, vol. 62(1), pages 125-149, January.
    15. Zwerts, Enid & Allaert, Georges & Janssens, Davy & Wets, Geert & Witlox, Frank, 2010. "How children view their travel behaviour: a case study from Flanders (Belgium)," Journal of Transport Geography, Elsevier, vol. 18(6), pages 702-710.
    16. Shang Xie & Muhammad Ateeq ur Reman & Kang Mao, 2022. "Effects of Education Equalization Measures on Housing Prices: Evidence from a Natural Experiment in Suzhou, China," Review of Economic Assessment, Anser Press, vol. 1(1), pages 22-33, December.
    17. Kelly, J. Andrew & Fu, Miao, 2014. "Sustainable school commuting – understanding choices and identifying opportunities," Journal of Transport Geography, Elsevier, vol. 34(C), pages 221-230.
    18. Yan Xu & Weixuan Song & Chunhui Liu, 2018. "Social-Spatial Accessibility to Urban Educational Resources under the School District System: A Case Study of Public Primary Schools in Nanjing, China," Sustainability, MDPI, vol. 10(7), pages 1-16, July.
    19. Muñoz-Morales, Juan & Singh, Ruchi, 2023. "Do school shootings erode property values?," Regional Science and Urban Economics, Elsevier, vol. 98(C).
    20. Ed Ferrari & Mark A Green, 2013. "Travel to School and Housing Markets: A Case Study of Sheffield, England," Environment and Planning A, , vol. 45(11), pages 2771-2788, November.

    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:11:y:2019:i:16:p:4432-:d:258203. 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.