inthis article we offer a method of ranking contractors by using dea based onanalysis deficit and ahp. the process of hierarchical analysis (ahp) byproviding scales from paired comparison matrix, performs the contractor’sprioritizing choice. but ahp has some problems and to solve those problems,jahanshahloo and his colleagues presented a new model which uses dea andstandard deviation. in this a...

Current studies that use traditional data envelopment analysis (DEA) neglect the 100% market share restriction. This study adopts zero-sum gains data envelopment analysis to measure the efficiency scores of securities firms (SFs) and indicates that the traditional DEA model underestimates the efficiency scores of inefficient SFs. This research analyses 266 integrated securities firms in Taiwan ...

In many organizations and financial institutions, we don't always have acsses to inputs and outputs to evaluate the decision-making units (DMUs), but rather only a ratio of inputs to outputs ( or reverse) might be available. In DEA, cost efficiency determines input standards based on input costs. In multi-stage network DEA processes, in addition to input standards, cost efficiency would determi...

This paper examines three essential components which comprise efficiency evaluation in data envelopment analysis. The three components are present in each DEA model and determine the implicit evaluation scheme associated with the model. These components provide a framework for classifying the various DEA models with respect to (i) the form of envelopment surface, (ii) the orientation, and (iii)...

In this paper, we discuss three-stage models that control for exogenous, non-discretionary inputs in data envelopment analysis. In a recent article in this journal, Monte Carlo analysis was employed to compare and contrast alternative DEA models that measure efficiency in the presence of exogenous variables. The methodology for comparison was flawed, calling into question the results presented....

Supplier selection is a multi-Criteria problem. This study proposes a hybrid model for supporting the suppliers’ selection and ranking. This research is a two-stage model designed to fully rank the suppliers where each supplier has multiple Inputs and Outputs. First, the supplier evaluation problem is formulated by Data Envelopment Analysis (DEA), since the regarded decision deals with uncertai...

Benchmarking cleaner production performance is an effective way of pollution control and emission reduction in coal-fired power industry. A benchmarking method using two-stage super-efficiency data envelopment analysis for coal-fired power plants is proposed – firstly, to improve the cleaner production performance of DEA-inefficient or weakly DEA-efficient plants, then to select the benchmark f...

data envelopment analysis (dea) is a method for measuring the efficiency of peer decision making units (dmus) which uses a set of inputs to produce a set of outputs. in some cases, dmus have a two-stage structure, in which the first stage utilizes inputs to produce outputs used as the inputs of the second stage to produce final outputs. one important issue in two-stage dea is the sensitivity of...

In the banking industry, the production process can be described as a two-stage process. There are a number of published data envelopment analysis (DEA) papers that study the bank performance with two-stage model. However, none of them is applied to identify bank failure. In fact, only one of them deals with negative profit data. In the real world, failed banks or firms often produced negative ...

the present study is an attempt toward evaluating the performance of portfolios using mean-variance-skewness model with negative data. mean-variance non-linear framework and mean-variance-skewness non- linear framework had been proposed based on data envelopment analysis, which the variance of the assets had been used as an input to the dea and expected return and skewness were the output. conv...