نتایج جستجو برای: data envelopment analysis approach dea
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Halme, Joro, Korhonen, Salo and Wallenius [1998] present an approach for using preference information in Data Envelopment Analysis (DEA). In their paper, they develop value efficiency, an extension of the concept of efficiency in DEA. In this paper, we develop some related concepts, and present two refinements: 1. Some bounds on the value efficiency scores that may be obtained without any decis...
The standard data envelopment analysis (DEA) method assumes that the values for inputs and outputs are exact. While DEA assumes exact data, the existing imprecise DEA (IDEA) assumes that the values for some inputs and outputs are only known to lie within bounded intervals, and other data are known only up to an order. In many real applications of DEA, there are cases in which some of the input ...
Data envelopment analysis (DEA) is a mathematical programming technique for identifying efficiency scores of decision making units (DMUs). Since DEA models cannot present efficient frontiers of PPS, in order to do this, we introduce a method for identifying efficient frontier for DMUs with interval data.
Airport efficiency is an area of increasing interest to academics, policy makers and practitioners. This has resulted in a body of literature applying various econometric techniques to compare efficiency between different samples of airports. This paper uses the multi-criteria decision making method Analytic Hierarchy Process (AHP) to incorporate the weightings of input and output variables int...
Airport efficiency is an area of increasing interest to academics, policy makers and practitioners. This has resulted in a body of literature applying various econometric techniques to compare efficiency between different samples of airports. This paper uses the multi-criteria decision making method Analytic Hierarchy Process (AHP) to incorporate the weightings of input and output variables int...
one of the difficulties of data envelopment analysis(dea) is the problem of deciency discriminationamong efficient decision making units(dmus) and hence, yielding large number of dmus as efficientones. the main purpose of this paper is to overcome this inability. one of the methods for rankingefficient dmus is minimizing the coefficient of variation (cv) for inputs-outputs weights. in this pap...
in the use of peer group data to assess individual, typical or best practice performance, the effective detection of outliers is critical for achieving useful results. in these ‘‘deterministic’’ frontier models, statistical theory is now mostly available. this paper deals with the statistical pared sample method and its capability of detecting outliers in data envelopment analysis. in the prese...
one of the major problems in data envelopment analysis (dea) is to determine the projection of inefficient decision making units (dmus) into the efficient frontier. in conventional dea models, inputs and outputs of inefficient dmus alter arbitrarily for reaching to the efficient frontier. nevertheless, sometimes the ability of dmus is defined and restricted. moreover, there are situations in th...
copies of this document for non-commercial purposes by any means, provided that this copyright notice appears on all such copies. This article integrates fuzzy set theory in Data Envelopment Analysis (DEA) framework to compute technical efficiency scores when input and output data are imprecise. The underlying assumption in convectional DEA is that inputs and outputs data are measured with prec...
Context-Dependent Data Envelopment Analysis-Measuring Attractiveness and Progress with Interval Data
Data envelopment analysis (DEA) is a method for recognizing the efficient frontier of decision making units (DMUs).This paper presents a Context-dependent DEA which uses the interval inputs and outputs. Context-dependent approach with interval inputs and outputs can consider a set of DMUs against the special context. Each context shows an efficient frontier including DMUs in particular l...
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