This paper concentrates on methods for comparing activity units found relatively efficient by data envelopment analysis (DEA). The use of the basic DEA models does not provide direct information regarding the performance of such units. The paper provides a systematic framework of alternative ways for ranking DEA-efficient units. The framework contains criteria derived as by-products of the basi...

Some specific geometric data envelopment analysis (DEA) models are well known to the researchers in DEA through so-called multiplicative or log-linear efficiency models. Valuable properties of these models were noted by several authors but the models still remain somewhat obscure and rarely used in practice. The purpose of this paper is to show from a mathematical perspective where the geometri...

Author Steven Zeisel believes DEA could induce fetal neural abnormalities in humans, too. “It’s hard to estimate human exposure, but we believe the mice had exposures about ten times higher,” he says, assuming that people bathe and shampoo daily with DEA-containing products, and use DEAcontaining sunscreen. “There’s no reason to believe we wouldn’t see similar effects in humans.” The authors no...

In this paper, a novel approach combining fuzzy data envelopment analysis (DEA) and the analytical hierarchical process (AHP) is proposed to rank units with multiple fuzzy criteria. The hybrid fuzzy DEA/AHP approach derives the AHP pairwise comparisons by fuzzy DEA and utilizes AHP to fully rank units. It shows that the proposed approach generates a logical ranking of units that has perfect com...

BACKGROUND Denitrification is an important ecosystem service that removes nitrogen (N) from N-polluted watersheds, buffering soil, stream, and river water quality from excess N by returning N to the atmosphere before it reaches lakes or oceans and leads to eutrophication. The denitrification enzyme activity (DEA) assay is widely used for measuring denitrification potential. Because DEA is a fun...

Despite the large uses of inverse DEA models, there is not any single application of inverse linear programming in DEA when the definition of inverse linear programming is taken under account. Thus the goal of this paper is applying the inverse linear programming into DEA field, and to provide a streamlined approach to DEA and Additive model. Having the entire efficient DMUs in DEA models is a...

Amiodarone (AM) is a potent antidysrhythmic agent that can cause potentially life-threatening pulmonary fibrosis, and N-desethylamiodarone (DEA), an AM metabolite, may contribute to AM toxicity. Apoptotic cell death in nontransformed human peripheral lung epithelial 1A (HPL1A) cells was assessed by annexin V-fluorescein isothiocyanate (ann-V) staining and terminal deoxynucleotidyl transferase-m...

BACKGROUND Dog erythrocyte antigen (DEA) 1.1 is the most important RBC antigen clinically, as it is highly immunogenic and causes acute hemolytic transfusion reactions (HTR) in sensitized dogs. OBJECTIVES The aims of this study were to determine the frequency of DEA 1.1 expression in 4 Turkish dog breeds, and to estimate the potential risk of HTR when blood from a DEA 1.1-positive donor is ad...

This paper proposes a new efficiency benchmarking methodology that is capable of incorporating probability while still preserving the advantages of a distribution-free and nonparametric modeling technique. This new technique developed in this paper will be known as the DEA-Chebyshev model. The foundation of DEA-Chebyshev model is based on the model pioneered by Charnes, Cooper, and Rhodes in 19...

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...