Data Envelopment Analyses
Sara Baqdadchi; Ghasem Tohidi
Abstract
Multi-attribute decision-making is a powerful and widely used method of solving decision-making problems and choosing the most desirable of the available options. Data envelopment analysis is a nonparametric method for calculating performance size. The basic drawback of conventional decision-making methods ...
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Multi-attribute decision-making is a powerful and widely used method of solving decision-making problems and choosing the most desirable of the available options. Data envelopment analysis is a nonparametric method for calculating performance size. The basic drawback of conventional decision-making methods is that they are not capable of taking into account decision-making priorities and preferences as well as risk-taking or risk aversion. On the other hand, in some cases, it is difficult to determine the exact amount of data and the results are qualitative and quantitative. The weighted average method is classified as one of the decision-making methods that are capable of considering the priorities and subjective evaluations of the decision-maker in the decision-making process. This paper deals with one of the ranking methods in data envelopment analysis called cross-efficiency and tries to consider the decision-makers' risk-taking and risk-aversion in consolidating cross-performance matrix members as well as in the cross-efficiency integration process.