a characteristic of data envelopment analysis (dea) is to allow individual decision making units (dmus) to select the factor weights which are the most advantageous for them in calculating their efficiency scores. this flexibility in selecting the weights, on the other hand, deters the comparison among dmus on a common base. for dealing with this difficulty and assessing all the dmus on the sam...

this study uses the data envelopment analysis (dea) to assess the progress/regression of decision-making units (dmus) having a two-stage structure‎. ‎the progress/regression of these dmu can be assessed in the first stage‎, ‎the second stage‎, ‎and the whole system‎. ‎in the first stage‎, ‎the progress/regression of bank branches in collecting resources and in the second stage their progress/re...

data envelopment analysis (dea) was developed to help compare the relative performance of decision-making units. it is a non-parametric method for performing frontier analysis. it uses linear programming to estimate the efficiency of multiple decision-making units and it is commonly used in production, management and economics [3]. dea generates an efficiency score between 0 and 1 for each unit...

recently the concept of facility efficiency, which defined by data envelopment analysis (dea), introduced as a location modeling objective, that provides facilities location’s effect on their performance in serving demands. by combining the dea models with the location problem, two types of “efficiencies” are optimized: spatial efficiency which measured by finding the least cost location and al...

data envelopment analysis (dea) as a non-parametric method for efficiency measurement allows decision making units (dmus) to select the most advantageous weight factors in order to maximize their efficiency scores.  in most practical applications of dea presented in the literature, the presented models assume that all inputs are fully desirable. however, in many real situations undesirable inpu...

background: during the last decades, the number of dentistry units increased significantly across the country. the aim of this study was to assess the efficiency of dental units of iran provinces regarding dental health inputs and outputs using data envelopment analysis approach. methods: in this applied descriptive-analytical study, the study population included all of iran 31 provinces. the o...

In a relatively short period of time Data Envelopment Analysis (DEA) has grown into a powerful quantitative, analytical tool for measuring and evaluating performance. DEA has been successfully applied to a host of different types of entities engaged in a wide variety of activities in many contexts worldwide. This chapter discusses the fundamental DEA models and some of their extensions.

Abstract—Multi-component data envelopment analysis (MCDEA) is a popular technique for measuring aggregate performance of the decision making units (DMUs) along with their components. However, the conventional MC-DEA is limited to crisp input and output data which may not always be available in exact form. In real life problems, data may be imprecise or fuzzy. Therefore, in this paper, we propos...

The outcome of a production process might not only deviate from a theoretical maximum due to inefficiency, but also because of non-controllable influences. This raises the issue of reliability of Data Envelopment Analysis in noisy environments. I propose to assume an i.i.d. data generating process with bounded noise component, so that the following approach is feasible: Use DEA to estimate a ps...