IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/122924.html
   My bibliography  Save this paper

The Clustering Method Applied in a Fair Division Process

Author

Listed:
  • Mputu Losala Lomo, Denis-Robert

Abstract

In this paper, we intend to present our two processes for the equitable sharing of resources which use several variables, take into account the type of variables and the origin of the resource, involving in particular the notions of data transformation and of clustering used in Statistics. These processes are: PRRS (for Procédé de la Répartition des Ressources Sans réduction des inégalités, in English Process of the Distribution of Resources without reduction of inequalities) and PRRC (for Procédé de la Répartition des Ressourcesà partir des résultats de la Classification, in English Process of the Distribution of Resources from Clustering results). They come to solve the problem of injustice in a sharing of resources (in particular, a sum of money), the injustice due to 1) the use of a single variable (criterion) instead of several, 2) the direct use of homogeneous variables where the same unit of measurement is expressed differently for each variable, 3) the direct use of heterogeneous variables and 4) the lack of reduction of inequalities between individuals, in certain cases.

Suggested Citation

  • Mputu Losala Lomo, Denis-Robert, 2023. "The Clustering Method Applied in a Fair Division Process," MPRA Paper 122924, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:122924
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/122924/1/MPRA_paper_122924.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Ascending Hierarchical Classification; Equitable sharing; Resource; Process; Reduction of inequalities.;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory

    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:pra:mprapa:122924. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.