Preference Voting and Ranking Using Dea Game Cross Efficiency Model
نویسندگان
چکیده
Abstract Data envelopment analysis (DEA), a useful assessment tool, has been used to solve the problem of preference voting and aggregation which require the determination of the weights associated with different ranking places. Instead of applying the same externally imposed weighting scheme to all candidates, DEA models allow each candidate to choose his/her own weights in order to maximize his/her own overall ratings subject to certain conditions. It is evident that competition exists among the candidates in a preferential election, while there is no literature considering the factor of competition. This paper proposes an approach to rank candidates based on DEA game cross efficiency model, in which each candidate is viewed as a player who seeks to maximize its own efficiency, under the condition that the cross efficiencies of each of other DMU’s does not deteriorate. The game cross efficiency score is obtained when the DMU’s own maximized efficiencies are averaged. The obtained game cross efficiency scores constitute a Nash Equilibrium point. Therefore, the results and orders based upon game cross efficiency analysis are more reliable and will benefit the decision-maker.
منابع مشابه
Voting and different ranking orders in DEA
Data Envelopment Analysis (DEA) technique now widely use for efficiency evaluation of a set of Decision Making Units (DMUs). As regards of the necessity for ranking efficient units different DEA models presented each of which has advantages and rank efficient units from special aspects. Note that all the existing ranking models have disadvantages, as well and there is not a model in which all t...
متن کاملRanking Efficient Decision Making Units Using Cooperative Game Theory Based on SBM Input-Oriented Model and Nucleolus Value
In evaluating the efficiency of decision making units (DMUs) by Data Envelopment Analysis (DEA) models, may be more than one DMU has an efficiency score equal to one. Since ranking of efficient DMUs is essential for decision makers, therefore, methods and models for this purpose are presented. One of ranking methods of efficient DMUs is cooperative game theory. In this study, Lee and Lozano mod...
متن کاملMaximum appreciative cross-efficiency in DEA: A new ranking method
Ranking decision making units (DMUs) is one of the most important applications of data envelopment analysis (DEA). In this paper, we exploit the power of individual appreciativeness in developing a methodology that combines crossevaluation, preference voting and ordered weighted averaging (OWA). We show that each stage of the proposed methodology enhances discrimination among DMUs while offerin...
متن کاملA Dea- Compromise Programming Model for Comprehensive Ranking
This paper addresses comprehensive ranking systems determining an ordering of entities by aggregating quantitative data for multiple attributes. We propose a DEA-CP (Data Envelopment Analysis Compromise Programming) model for the comprehensive ranking, including preference voting (ranked voting) to rank candidates in terms of aggregate vote by rank for each candidate. Although the DEA-CP model ...
متن کامل