IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v72y2020ics0038012119304343.html
   My bibliography  Save this article

Optimizing the spatial assignment of schools to reduce both inequality of educational opportunity and potential opposition rate through introducing random mechanism into proximity-based system

Author

Listed:
  • Liao, Cong
  • Scheuer, Bronte
  • Dai, Teqi
  • Tian, Yuan

Abstract

A serious spatial inequality of educational opportunity was revealed worldwide, for wealthy families can access good schools by buying real estate with good school' enrollment quota. Although the existing studies had revealed that random-based school assignment can significantly improve equality of opportunity allocation, random mechanism was adopted only in few places. Two major resistances of introducing random mechanism exist: the possibility of increased commuting distance to schools and the effected relative beneficiaries. In order to make the random-based allocation more feasible, this study proposes a spatial optimization model to take these two factors into account into proximity-based school assignment system. The proposed multi-objective allocation model, with the constraint conditions of assigning students to 3 closest schools and school capacities, was developed in this study to minimize the spatial disparity of educational opportunity and the potential opposition rate of introducing random mechanism into proximity-based assignment system. The model will be solved by a heuristic algorithm and applied to a case study area of Shijingshan District, Beijing. The results showed that the proposed model could improve spatial equality of educational opportunity significantly, but along with a minor increase on commuting distance to schools. In addition, potential opponents of introducing random mechanism decrease as the weight of parameters related to opposition rate increases in the model, reducing nearly 10% in the best case. Therefore, the solutions provided by proposed model may encounter less resistance in a democratic voting system. However, the results also indicated that there would be some relative beneficiaries who may oppose introducing random mechanism into proximity-based school system even in the best case. This implies that, to achieve equal educational opportunity in the context of proximity-based school system, optimized allocation is needed along with a more even distribution of educational resources.

Suggested Citation

  • Liao, Cong & Scheuer, Bronte & Dai, Teqi & Tian, Yuan, 2020. "Optimizing the spatial assignment of schools to reduce both inequality of educational opportunity and potential opposition rate through introducing random mechanism into proximity-based system," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
  • Handle: RePEc:eee:soceps:v:72:y:2020:i:c:s0038012119304343
    DOI: 10.1016/j.seps.2020.100893
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0038012119304343
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.seps.2020.100893?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gordon F. Mulligan, 1991. "Equality Measures And Facility Location," Papers in Regional Science, Wiley Blackwell, vol. 70(4), pages 345-365, October.
    2. Harris, Douglas N. & Sass, Tim R., 2011. "Teacher training, teacher quality and student achievement," Journal of Public Economics, Elsevier, vol. 95(7-8), pages 798-812, August.
    3. Parag A. Pathak, 2011. "The Mechanism Design Approach to Student Assignment," Annual Review of Economics, Annual Reviews, vol. 3(1), pages 513-536, September.
    4. Goeverden, C.D. van & Boer, E. de, 2013. "School travel behaviour in the Netherlands and Flanders," Transport Policy, Elsevier, vol. 26(C), pages 73-84.
    5. João Teixeira & António Antunes & Dominique Peeters, 2007. "An Optimization-Based Study on the Redeployment of a Secondary School Network," Environment and Planning B, , vol. 34(2), pages 296-315, April.
    6. Kesten, Onur & Unver, Utku, 2015. "A theory of school choice lotteries," Theoretical Economics, Econometric Society, vol. 10(2), May.
    7. Tim Butler & Chris Hamnett, 2007. "The Geography of Education: Introduction," Urban Studies, Urban Studies Journal Limited, vol. 44(7), pages 1161-1174, June.
    8. Teixeira, Joao C. & Antunes, Antonio P., 2008. "A hierarchical location model for public facility planning," European Journal of Operational Research, Elsevier, vol. 185(1), pages 92-104, February.
    9. Marsh, Michael T. & Schilling, David A., 1994. "Equity measurement in facility location analysis: A review and framework," European Journal of Operational Research, Elsevier, vol. 74(1), pages 1-17, April.
    10. Lemberg, David S. & Church, Richard L., 2000. "The school boundary stability problem over time," Socio-Economic Planning Sciences, Elsevier, vol. 34(3), pages 159-176, September.
    11. William Clark & Regan Maas, 2012. "Schools, Neighborhoods and Selection: Outcomes Across Metropolitan Los Angeles," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 31(3), pages 339-360, June.
    12. Eric Delmelle & Jean-Claude Thill & Dominique Peeters & Isabelle Thomas, 2014. "A multi-period capacitated school location problem with modular equipment and closest assignment considerations," Journal of Geographical Systems, Springer, vol. 16(3), pages 263-286, July.
    13. Clarke, S. & Surkis, J., 1968. "An operations research approach to racial desegregation of school systems," Socio-Economic Planning Sciences, Elsevier, vol. 1(3), pages 259-272, July.
    14. Haase, Knut & Müller, Sven, 2013. "Management of school locations allowing for free school choice," Omega, Elsevier, vol. 41(5), pages 847-855.
    15. Richard Arneson, 2018. "Four Conceptions of Equal Opportunity," Economic Journal, Royal Economic Society, vol. 128(612), pages 152-173.
    16. 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.
    17. 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.
    18. Richard Arneson, 2018. "Four Conceptions of Equal Opportunity," Economic Journal, Royal Economic Society, vol. 128(612), pages 152-173, July.
    19. Eric Budish & Yeon-Koo Che & Fuhito Kojima & Paul Milgrom, 2013. "Designing Random Allocation Mechanisms: Theory and Applications," American Economic Review, American Economic Association, vol. 103(2), pages 585-623, April.
    20. F Caro & T Shirabe & M Guignard & A Weintraub, 2004. "School redistricting: embedding GIS tools with integer programming," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(8), pages 836-849, August.
    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. Liberatore, Federico & Camacho-Collados, Miguel & Quijano-Sánchez, Lara, 2023. "Towards social fairness in smart policing: Leveraging territorial, racial, and workload fairness in the police districting problem," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    2. Mayerle, Sérgio F. & Rodrigues, Hidelbrando F. & Neiva de Figueiredo, João & De Genaro Chiroli, Daiane M., 2022. "Optimal student/school/class/teacher/classroom matching to support efficient public school system resource allocation," Socio-Economic Planning Sciences, Elsevier, vol. 83(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.

    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. Mayerle, Sérgio F. & Rodrigues, Hidelbrando F. & Neiva de Figueiredo, João & De Genaro Chiroli, Daiane M., 2022. "Optimal student/school/class/teacher/classroom matching to support efficient public school system resource allocation," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    2. Wei, Ran & Feng, Xin & Rey, Sergio & Knaap, Elijah, 2022. "Reducing racial segregation of public school districts," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    3. Eric Delmelle & Jean-Claude Thill & Dominique Peeters & Isabelle Thomas, 2014. "A multi-period capacitated school location problem with modular equipment and closest assignment considerations," Journal of Geographical Systems, Springer, vol. 16(3), pages 263-286, July.
    4. Murray, Alan T., 2016. "Assessing the impacts of traditional school year calendar start dates," Socio-Economic Planning Sciences, Elsevier, vol. 54(C), pages 28-36.
    5. 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.
    6. Jorge Amaya & Dominique Peeters & Paula Uribe & Juan P. Valenzuela, 2016. "Optimization Modeling for Resource Allocation in the Chilean Public Education System," International Regional Science Review, , vol. 39(2), pages 155-176, April.
    7. Scott Duke Kominers & Alexander Teytelboym & Vincent P Crawford, 2017. "An invitation to market design," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 33(4), pages 541-571.
    8. Karsu, Özlem & Morton, Alec, 2015. "Inequity averse optimization in operational research," European Journal of Operational Research, Elsevier, vol. 245(2), pages 343-359.
    9. Hoda Heidari & Michele Loi & Krishna P. Gummadi & Andreas Krause, 2018. "A Moral Framework for Understanding of Fair ML through Economic Models of Equality of Opportunity," Papers 1809.03400, arXiv.org, revised Nov 2018.
    10. 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.
    11. Elias Bouacida & Renaud Foucart, 2022. "Rituals of Reason," Working Papers 344119591, Lancaster University Management School, Economics Department.
    12. Andrew McLennan & Shino Takayama & Yuki Tamura, 2024. "An Efficient, Computationally Tractable School Choice Mechanism," Discussion Papers Series 668, School of Economics, University of Queensland, Australia.
    13. Song, Yang & Zhou, Guangsu, 2019. "Inequality of opportunity and household education expenditures: Evidence from panel data in China," China Economic Review, Elsevier, vol. 55(C), pages 85-98.
    14. Chong Hyun Park & Gemma Berenguer, 2020. "Supply Constrained Location‐Distribution in Not‐for‐Profit Settings," Production and Operations Management, Production and Operations Management Society, vol. 29(11), pages 2461-2483, November.
    15. Onur Kesten & Morimitsu Kurino & Alexander S. Nesterov, 2017. "Efficient lottery design," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 48(1), pages 31-57, January.
    16. Nikhil Agarwal & Eric Budish, 2021. "Market Design," NBER Working Papers 29367, National Bureau of Economic Research, Inc.
    17. F Caro & T Shirabe & M Guignard & A Weintraub, 2004. "School redistricting: embedding GIS tools with integer programming," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(8), pages 836-849, August.
    18. Wonki Jo Cho & Battal Doğan, 2017. "Stability and the immediate acceptance rule when school priorities are weak," International Journal of Game Theory, Springer;Game Theory Society, vol. 46(4), pages 991-1014, November.
    19. Cruz Lopez-de-los-Mozos, M. & Mesa, Juan A., 2001. "The maximum absolute deviation measure in location problems on networks," European Journal of Operational Research, Elsevier, vol. 135(1), pages 184-194, November.
    20. Bhatnagar, Abhishek & Bolia, Nomesh B., 2019. "Improved governance of Indian school system through school consolidation," Journal of Policy Modeling, Elsevier, vol. 41(6), pages 1160-1178.

    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:eee:soceps:v:72:y:2020:i:c:s0038012119304343. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/seps .

    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.