background: nowadays, healthcare systems are considered as important service sectors, and they are social development and welfare standards; hence the performance of this sector is highly important. evaluating performance is the first step of various departments to determine the efficiency of the healthcare system. in the meantime, diagnostic laboratories of hospitals play important roles as sp...

Data Envelopment Analysis (DEA) is a nonparametric approach for measuring the relative efficiency of a decision making units consists of multiple inputs and outputs. In all standard DEA models semi positive real valued measures are assumed, while in some real cases inputs and outputs may take complex valued. The question is related to measuring efficiency in such cases. As far as we are aware, ...

It is essential for most organizations and financial institutes to be able to evaluate their decision-making units (DMUs), when there is only a ratio of inputs to outputs (or vice versa) available. In this paper, we will propose our two-stage DEA-R models, which are a combination of data envelopment analysis and ratio data, based on value efficiency. Integrating value efficiency into data envel...

this paper introduces discretionary imprecise data in data envelopment analysis (dea) and discusses the efficiency evaluation of decision making units (dmus) with non-discretionary imprecise data. then, suggests a method for evaluation the efficiency of dmus with non-discretionary imprecise data. when some inputs and outputs are imprecise and non-discretionary, the dea model becomes non-linear ...

Data Envelopment Analysis (DEA) provides means for piecewise linear approximation of production functions. To improve the fit to the data we propose to improve the flexibility of the frontier by extending DEA towards a more general piecewise quadratic approximation, called Quadratic Data Envelopment Analysis (QDEA). In contrast to the linear approximation, the quadratic approximation allows for...

A technique used to assess relative performance in a multiple input–output framework is data envelopment analysis (DEA). In basic DEA models, an entitymay show its best performanceby selecting input and output factor weights different from those selected by the other entities in thesample. Hence, when usingbasic DEAmodels, divergence of weighting schemesacross the assessedentitiescannot beruled...

This study illustrates the use of data envelopment analysis to benchmark mutual funds on the basis of risk-adjusted performance, load, 12b-1 plan, and expense ratios. Using the DEA methodology, we calculate an efficiency score for 189 funds on a scale of 1 to 100 by maximizing twelve month total return and minimizing beta, standard deviation, load, 12b-1 charges, and expense ratios. This study ...

a new algorithm for classification of dmus to efficient and inefficient units in data envelopment analysis is presented. this algorithm uses the non-archimedean charnes-cooper-rhodes[1] (ccr) model. also, it applies an assurance value for the non-archimedean                          using only simple computations on inputs and outputs of dmus (see [18]). the convergence and efficiency of the ne...