This paper suggests that the efficiency of a system (decision-making unit) and its subsystem cannot be properly measured using two-stage data envelopment analysis (DEA) model either in cooperative or non-cooperative evaluation. Indeed, existing methods subjectively determine status subsystems whole system. The DEA models, game game, are used to analyze environmental efficiency. However, when ac...

D-eritadenine (DEA) is a potent inhibitor (IC(50) = 7 nm) of S-adenosyl-l-homocysteine hydrolase (AdoHcyase). Unlike cyclic sugar Ado analogue inhibitors, including mechanism-based inhibitors, DEA is an acyclic sugar Ado analogue, and the C2' and C3' have opposite chirality to those of the cyclic sugar Ado inhibitors. Crystal structures of DEA alone and in complex with AdoHcyase have been deter...

Data envelopment analysis technique which is developed based on the mathematical programming, evaluates the relative efficiency of a set of homogeneous decision making units. This paper shows the method of Discriminant Analysis (DA), on Imprecise Data by Data Envelopment 724 F. Hosseinzadeh Lotfi et al Analysis (DEA). DEA-Discriminant Analysis (DEA-DA) is designed to identify the existence or n...

Proposed in this study is a hybrid model for supporting the performance of a department within Amir Kabir University in Iran. The proposal is a two-stage model designed to fully rank the organizational departments where each faculty has multiple inputs and outputs. First, the Data Envelopment Analysis (DEA) separately formulates each pair of units. In the second stage, the pair-wise evaluation ...

Data envelopment analysis (DEA) is a non-parametric approach for measuring the relative efficiencies of peer decision making units (DMUs). Many studies have examined DEA efficiencies of two-stage systems, where all the outputs from the first stage are the only inputs to the second stage. Although single-stage DEA models with undesirable input-outputs have been extensively studied, there still l...

Two-stage data envelopment analysis (2-DEA) is commonly used in productive efficiency analysis to estimate the effects of operational conditions and practices on performance. In this method the DEA efficiency estimates are regressed on contextual variables representing the operational conditions. We reexamine the statistical properties of the 2-DEA estimator, and find that it is statistically c...

BACKGROUND The prevalence of dog erythrocyte antigen (DEA 1) in canine population is approximately 40-60%. Often data are limited to a small number of breeds and/or dogs. The aims of this study were to evaluate frequency of DEA 1 in a large population of purebred and mongrel dogs including Italian native breeds and to recognize a possible association between DEA 1 and breed, sex, and genetic an...

In this paper, we compare the properties of the traditional additive-based data envelopment analysis (hereafter, referred to as DEA) models and propose two generalized DEA models, i.e., the big M additive-based DEA (hereafter, referred to as BMA) model and the big M additive-based super-efficiency DEA (hereafter, referred to as BMAS) model, to evaluate the performance of the biomass power plant...

In Chen, Cook, Kao, and Zhu (2013), it is demonstrated, as a network DEA pitfall, that while the multiplier and envelopment DEA models are dual models and equivalent under the standard DEA, such is not necessarily true for the two types of network DEAmodels in deriving divisional efficiency scores and frontier projections. As a reaction to this work, we demonstrate that the duality in the stand...

Utilizing recent developments in data envelopment analysis (DEA), this paper examines the performance of the top 55 U.S. commercial banks via a two-stage production process that separates profitability and marketability. Substantial performance inefficiency is uncovered in both dimensions. Relatively large banks exhibit better performance on profitability, whereas smaller banks tend to perform ...