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...

A DEA-based stochastic estimation framework is presented to evaluate contextual variables affecting productivity. Conditions are identified under which a two-stage procedure consisting of DEA followed by regression analysis yields consistent estimators of the impact of contextual variables. Conditions are also identified under which DEA in the first stage followed by maximum likelihood estimati...

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...

Data envelopment analysis (DEA) has proven to be a useful tool for assessing efficiency or productivity of organizations, which is of vital practical importance in managerial decision making. DEA provides a significant amount of information from which analysts and managers derive insights and guidelines to promote their existing performances. Regarding to this fact, effective and methodologic a...

This short communication complements the DEA model proposed by Lovell and Pastor (Eur. J. Oper. Res. 118 (1999), 46-51), by incorporating both positive and negative criteria in the model. As such, we propose a DEA model, known as pure DEA, using a directional distance function approach.

An original data envelopment analysis (DEA) model is to evaluate each decision-making unit (DMU) with a set of most favorable weights of performance indices. The efficient DMUs obtained from the original DEA construct an efficient (bestpractice) frontier. The original DEA can be considered to identify good (efficient) performers in the most favorable scenario. For the purpose of identifying bad...

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 ...

The paper deals with models and methods for evaluation of efficiency of production units. The standard modeling approach for evaluation of efficiency is data envelopment analysis (DEA) based on the definition of efficiency as the ratio of outputs produced by the unit and inputs spent in the production process. Standard data envelopment analysis models divide the units into inefficient and effic...

A theorem prover f o r part of ar i thmet ic in described which proves theorems by represent ing them in the form of a diagram or network. The nodes of t h i s network represent ' i d e a l i n t e g e r s ' , i . e . objects which have a l l the propert ies of in tegers , without being any p a r t i cular in toger . The l i nks in the network represent re la t ionsh ips between ' i dea l i n t...

There has been recent concern about the impact of increased nutrient loading on the northern Everglades ecosystem. We investigated the spatial and temporal distribution of denitrifying enzyme activity (DEA) along a P-enrichment gradient in the Water Conservation Area 2A (WCA-2A) and determined the effects of added P and NO., on DEA. The DEA in soil and detritus layers was measured under anaerob...