data envelopment analysis (dea) is a method for measuring the efficiency of peer decision making units (dmus) with multiple inputs and outputs. the traditional dea treats decision making units under evaluation as black boxes and calculates their efficiencies with first inputs and last outputs. this carries the notion of missing some intermediate measures in the process of changing the inputs to...

We discuss how to measure allocative efficiency without presuming technical efficiency. This is relevant when it is easier to introduce reallocations than improvements of technical efficiency. We compare the approach to the traditional one of assuming technical efficiency before measuring allocative efficiency. In particular, we develop necessary and sufficient conditions on the technology to e...

A nonlinear (nonconvex) programming model provides a new definition of efficiency for use in evaluating activities of not-for-profit entities participating in public programs. A scalar measure of the efficiency of each participating unit is thereby provided, along with methods for objectively determining weights by reference to the observational data for the multiple outputs and multiple inputs...

Efficiency in the mutual fund (MF), is one of the issues that has attracted many investors in countries with advanced financial market for many years. Due to the need for frequent study of MF’s efficiency in short-term periods, investors need a method that not only has high accuracy, but also high speed. Data envelopment analysis (DEA) is proven to be one of the most widely used methods in the ...

Data Envelopment Analysis (DEA) is the most commonly used approach for evaluating healthcare efficiency (Hollingsworth, 2008), but a long-standing concern is that DEA assumes that data are measured without error. This is quite unlikely, and DEA and other efficiency analysis techniques may yield biased efficiency estimates if it is not realized (Gajewski, Lee, Bott, Piamjariyakul and Taunton, 20...

Data envelopment analysis (DEA) is a technique for measuring the efficiency of decision making units. In all models of the DEA, for each unit under assessment, the numerical efficiency is obtained which may be less than or equal to one. Given the possible large number of functional units, we use various ranking methods for evaluating units. One of the rating methods is Balance index and Topsis....

data envelopment analysis (dea) is a technique for measuring the efficiency of decision making units. in all models of the dea, for each unit under assessment, the numerical efficiency is obtained which may be less than or equal to one. given the possible large number of functional units, we use various ranking methods for evaluating units. one of the rating methods is balance index and topsis....

data envelopment analysis (dea) is a technique for measuring the efficiency of decision making units. in all models of the dea, for each unit under assessment, the numerical efficiency is obtained which may be less than or equal to one. given the possible large number of functional units, we use various ranking methods for evaluating units. one of the rating methods is balance index and topsis....

‎In this paper, we present a two-stage model for ranking of decision making units (DMUs) using interval analytic hierarchy process (AHP). Since the efficiency score of unity is assigned to the efficient units, we evaluate the efficiency of each DMU by basic DEA models and calculate the weights of the criteria using proposed model. In the first stage, the proposed model evaluates decision making...

The usefulness the left ventricular ejection fraction as a surrogate endpoint in clinical trials has been confirmed by numerous studies. However, if this approach is to be applied successfully, images must be acquired in a rigorously controlled manner, and it is advisable to use measurement units that have been specifically developed for quantitative analysis of the imaging parameters obtained ...