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Ranking of different ranking models using a voting model and its application in determining efficient candidates

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There are different ways to allow the voters to express their preferences on a set of candidates. In ranked voting systems, each voter selects a subset of the candidates and ranks them in order of preference. Cook and Kress using a data envelopment analysis/assurance region (DEA/AR) model, proposed to assess each candidate with the most favourable scoring vector for him/her. However, the use of this procedure often causes several candidates to be efficient, i.e., they achieve the maximum score. For this reason, several methods to discriminate among efficient candidates have been proposed. In this research, after reviewing the existing ranking models, we propose a new methodology to rank the ranking models for the performance indices of only DEA efficient candidates based on a voting model. Also, an approach for combining the results obtained from the ranking models is presented.

Keywords: data envelopment analysis, DEA, voting models, ranking models, voter preferences, efficient candidates

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