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A universal voting system based on the Potential Method

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  • Čaklović, Lavoslav
  • Kurdija, Adrian Satja

Abstract

Pairwise comparison of various objects (alternatives) is common in many procedures related to decision making. Potential Method (PM) uses a (weighted) preference graph as the basic structure generated by such comparisons to obtain a value function (potential) on the set of alternatives. The potential is calculated as a solution of a system of equations involving the Laplacian matrix of the preference graph. In multiple-criteria decision analysis or group decision making, each criterion or decision maker is represented by its preference graph. A multigraph obtained by joining these graphs aggregates the individual preferences and generates the group potential. Moreover, the influence (weight) of each criterion or decision maker on the group potential may be adjusted. In this article the aggregation of preference graphs is applied to voting systems. Many different forms of voting ballots can generate preference graphs, which gives us a universal (ballot-independent) voting system. As an illustration of the PM in the voting context we have chosen the Eurovision Song Contest and the analysis of the cookie-type ballots where the voters allocate a certain number of points (cookies) to the candidates.

Suggested Citation

  • Čaklović, Lavoslav & Kurdija, Adrian Satja, 2017. "A universal voting system based on the Potential Method," European Journal of Operational Research, Elsevier, vol. 259(2), pages 677-688.
    • Handle: RePEc:eee:ejores:v:259:y:2017:i:2:p:677-688
    DOI: 10.1016/j.ejor.2016.10.032
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    References listed on IDEAS

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    Cited by:

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    2. Csató, László, 2019. "A characterization of the Logarithmic Least Squares Method," European Journal of Operational Research, Elsevier, vol. 276(1), pages 212-216.
    3. Hou, Fujun & Triantaphyllou, Evangelos, 2019. "An iterative approach for achieving consensus when ranking a finite set of alternatives by a group of experts," European Journal of Operational Research, Elsevier, vol. 275(2), pages 570-579.
    4. László Csató, 2019. "Axiomatizations of inconsistency indices for triads," Annals of Operations Research, Springer, vol. 280(1), pages 99-110, September.
    5. L'aszl'o Csat'o & Csaba T'oth, 2018. "University rankings from the revealed preferences of the applicants," Papers 1810.04087, arXiv.org, revised Feb 2020.
    6. Csató, László & Tóth, Csaba, 2020. "University rankings from the revealed preferences of the applicants," European Journal of Operational Research, Elsevier, vol. 286(1), pages 309-320.

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