New prospects in social choice theory: median and average as tools for measuring, electing and ranking

The goal of this paper is to show that neither mean-based voting systems nor median-based ones can fulfill requirements of an ideal democracy. We then work out an original voting function obtained by hydrizing Borda Majority Count (mean-based) and Majority Judgment (median-based). The so-called “Mean-Median Compromise Method” slices between mean and average values. It proposes, moreover, a new tiebreaking method computing intermedian grades mean

Median and average as tools for measuring, electing and ranking: new prospects

Impossibility theorems expose inconsistencies and paradoxes related to voting systems. Recently, Michel Balinski and Rida Laraki proposed a new voting theory called Majority Judgment which tries to circumvent this limitation. In Majority Judgment, voters are invited to evaluate candidates in terms taken in a well-known common language. The winner is then the one that obtains the highest median. Since the Majority Judgment proposal was made, authors have detected insufficiencies with this new voting system. This article aims at reducing these insufficiencies by proposing a voting system to decide between the median-based voting and the mean-based one. It proposes, moreover, a new tie-breaking method computing intermedian ranks mean

Median and average as tools for measuring, electing and ranking: new prospects

Impossibility theorems expose inconsistencies and paradoxes related to voting systems. Recently, Michel Balinski and Rida Laraki proposed a new voting theory called Majority Judgment which tries to circumvent this limitation. In Majority Judgment, voters are invited to evaluate candidates in terms taken in a well-known common language. The winner is then the one that obtains the highest median. Since the Majority Judgment proposal was made, authors have detected insufficiencies with this new voting system. This article aims at reducing these insufficiencies by proposing a voting system to decide between the median-based voting and the mean-based one. It proposes, moreover, a new tie-breaking method computing intermedian ranks mean

New prospects in social choice theory: median and average as tools for measuring, electing and ranking

The goal of this paper is to show that neither mean-based voting systems nor median-based ones can fulfill requirements of an ideal democracy. We then work out an original voting function obtained by hydrizing Borda Majority Count (mean-based) and Majority Judgment (median-based). The so-called “Mean-Median Compromise Method” slices between mean and average values. It proposes, moreover, a new tiebreaking method computing intermedian grades mean

An aggregation function to solve multicriteria ranking problem involving several decision makers

Multiple Criteria Decision Aiding (MCDA) has been studied in a single decision maker framework for a long time. Nowadays, the need to take into account several conflicting opinions handled by several decisions makers arises. So, researchers are interested with multicriteria problems involving several decision makers. In this context, to solve ranking problem, we develop an aggregation model of several additive value functions. Comparisons with a derivative ELECTRE I method is done on numerical data. Clearly, it appears that the proposed aggregation function is better according to calculation complexity and computation time. Way for further research in this field is proposed

An aggregation function to solve multicriteria ranking problem involving several decision makers

Multiple Criteria Decision Aiding (MCDA) has been studied in a single decision maker framework for a long time. Nowadays, the need to take into account several conflicting opinions handled by several decisions makers arises. So, researchers are interested with multicriteria problems involving several decision makers. In this context, to solve ranking problem, we develop an aggregation model of several additive value functions. Comparisons with a derivative ELECTRE I method is done on numerical data. Clearly, it appears that the proposed aggregation function is better according to calculation complexity and computation time. Way for further research in this field is proposed