IDEAS home Printed from https://ideas.repec.org/p/irp/essays/2-2017.html
   My bibliography  Save this paper

A Multi-Criteria Analysis (MCA) for the territorial reorganization of the school network in a Tuscan inland area

Author

Listed:
  • Sabrina Iommi

    (Istituto Regionale per la Programmazione Economica della Toscana)

  • Donatella Marinari

    (Istituto Regionale per la Programmazione Economica della Toscana)

Abstract

A number of reasons arising from the need to reduce public spending are increasingly calling for a rationalization of the territorial distribution of public services. As far as the reorganization of the school network is concerned, this process is usually handled in an empirical way, through the opposition between public decision makers, who suggest to make dimensional thresholds (normally “adjusted” in the case of lower density areas) more binding, and local communities, which vigorously defend the status quo, generally resulting from past decisions taken on the basis of context-related characteristics that are very different from a financial, as well as a demographic and technological viewpoint. The present paper draws on data relating to the localization of education supply and demand in an inland area of Tuscany, so as to test the use of multi-criteria techniques and provide a more rational and transparent foundation to the debate on the spatial reorganization of public services. The present contribution is instrumental in furthering the studies in the IRPET research area addressing inland territories.

Suggested Citation

  • Sabrina Iommi & Donatella Marinari, "undated". "A Multi-Criteria Analysis (MCA) for the territorial reorganization of the school network in a Tuscan inland area," Studi e approfondimenti 2, Istituto Regionale per la Programmazione Economica della Toscana.
    • Handle: RePEc:irp:essays:2-2017
    as

    Download full text from publisher

    File URL: http://www.irpet.it/wp-content/uploads/2017/01/sa-amc_localizz_serv_aree_interne-iommi-27-12-2016.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Enrico Conti & Silvia Duranti & Carla Rampichini & Nicola Sciclone, 2015. "Quanto conta l?effetto scuola nel ciclo primario? L?efficacia delle istituzioni scolastiche in Toscana," ECONOMIA PUBBLICA, FrancoAngeli Editore, vol. 2015(3), pages 59-84.
    2. 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.
    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. De Grauwe, Paul & Ji, Yuemei, 2016. "Flexibility versus Stability: A difficult trade-off in the eurozone," CEPS Papers 11530, Centre for European Policy Studies.

    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. 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.
    2. Wang, Derek D., 2019. "Performance-based resource allocation for higher education institutions in China," Socio-Economic Planning Sciences, Elsevier, vol. 65(C), pages 66-75.
    3. João Lourenço Marques & Muhammad Tufail & Jan Wolf & Mara Madaleno, 2021. "Population Growth and the Local Provision of Services: The Role of Primary Schools in Portugal," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 40(2), pages 309-335, April.
    4. 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).
    5. Gerber, Pierre J. & Carsjens, Gerrit J. & Pak-uthai, Thanee & Robinson, Timothy P., 2008. "Decision support for spatially targeted livestock policies: Diverse examples from Uganda and Thailand," Agricultural Systems, Elsevier, vol. 96(1-3), pages 37-51, March.
    6. Włodzimierz Ogryczak, 2009. "Inequality measures and equitable locations," Annals of Operations Research, Springer, vol. 167(1), pages 61-86, March.
    7. 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.
    8. 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.
    9. Bruno, Giuseppe & Cavola, Manuel & Diglio, Antonio & Piccolo, Carmela, 2020. "Improving spatial accessibility to regional health systems through facility capacity management," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    10. Yuanyuan Zhu & John Aloysius Zinda & Qin Liu & Yukuan Wang & Bin Fu & Ming Li, 2023. "Accessibility of Primary Schools in Rural Areas and the Impact of Topography: A Case Study in Nanjiang County, China," Land, MDPI, vol. 12(6), pages 1-18, May.
    11. 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).
    12. 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.
    13. Zhenchao Zhang & Weixin Luan & Chuang Tian & Min Su & Zeyang Li, 2021. "Spatial Distribution Equilibrium and Relationship between Construction Land Expansion and Basic Education Schools in Shanghai Based on POI Data," Land, MDPI, vol. 10(10), pages 1-17, October.
    14. 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.

    More about this item

    Keywords

    education; models for the localization of public services; Multi-Criteria Analysis;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:irp:essays:2-2017. 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: Stefania Salvucci (email available below). General contact details of provider: https://edirc.repec.org/data/irpetit.html .

    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.