Data Envelopment Analysis (DEA) is a widely used technique for measuring the relative efficiencies of homogenous Decision Making Units (DMUs) with multiple inputs and multiple outputs. These factors may be evaluated in fuzzy or stochastic environment. Hence, the classic structures of DEA model may be changed where in two fold fuzzy stochastic environment. For instances, linearity, feasibility a...

this paper presents a combination of data envelopment analysis (dea) and principal component analysis (pca) to reduce the dimensionality of data set. dea is known as effective tool for assessment and benchmarking. the weak point of dea, it is that the number of efficient dmus relies on the number of variables (inputs and outputs). for solving this, first, we do principal component analysis (pca...

A characteristic of data envelopment analysis (DEA) is to allow individual decision making units (DMUs) to select the most advantageous weights in calculating their efficiency scores. This flexibility, 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 same scale, this paper proposes using a multiple objective...

Dear DEA [2] Description: This series of five clinical vignettes focuses on common concerns of clinicians and illustrates the relationship between the Drug Enforcement Administration (DEA) and health professionals, noting that the DEA can help explain federal regulations on legally prescribing controlled substances to patients. Authors: Heit HA, Covington E, Good PM. Source: Pain Medicine field...

Data Envelopment Analysis (DEA) has been widely studied in the literature since its inception with Charnes, Cooper and Rhodes work in 1978. The methodology behind the classical DEA method is to determine how much improvements in the outputs (inputs) dimensions is necessary in order to render them efficient. One of the underlying assumptions of this methodology is that the units consume and prod...

data envelopment analysis (dea) is a non-parametric technique for evaluation of relative efficiency of decision making units described by multiple inputs and outputs. it is based on solving linear programming problems. since 1978 when basic dea model was introduced many its modifications were formulated. among them are two or multi-stage models with serial or parallel structure often called net...

The study presents an empirical analysis of best practice production and cost frontiers for a sample of 94 acute care hospitals by applying Data Envelopment Analysis (DEA) and a regression model, in a two-stage approach. This paper contributes to the DEA and efficiency measurement literatures by adding results from a homogeneous method of partitioning cost efficiency into its allocative (or pri...

By using the DEA method, paper measures market efficiency of banks in Bosnia and Herzegovina period 2017-2020, context challenges caused by COVID-19. The aims research are: a) to measure rank them method (applying three models CCR-O, BCC-O, Window-I-C), b) establish effect COVID-19 pandemic on observed banks, c) established link between volume digital banking services usage banks. results show ...