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)...

Data Envelopment Analysis (DEA) has enjoyed a wide range of acceptance by researchers and practitioners alike as an instrument of performance analysis and management since its introduction in 1978. Many formulations and thousands of applications of DEA have been reported in a considerable variety of academic and professional journals all around the world. Almost all of the formulations and appl...

By employing the non-stochastic data envelopment analysis (DEA) method, the present paper provides empirical evidence on the efficiency of the Malaysian banking sector around the Asian financial crisis. The empirical findings suggest that the foreign banks (FB) have exhibited higher technical efficiency (TE) compared to their domestic bank counterparts. However, the results suggest that the FB ...

This research uses a new analytical approach for baseball evaluation, referred to as "A Bench Mark Approach," [1] by combining DEA (Data Envelopment Analysis) with OERA (Offensive Earned-Run Average). An important feature of the approach is that it can select a best performer among many baseball players and evaluate their ranking scores. The DEA is an evaluation technique of various entities in...

this paper presents a combination of data envelopment analysis (dea) and principal component analysis (pca) to reduce the dimensionality of data set. dea is known as effective tool for assessment and benchmarking. the weak point of dea, it is that the number of efficient dmus relies on the number of variables (inputs and outputs). for solving this, first, we do principal component analysis (pca...

Data envelopment analysis (DEA) has gained great popularity in environmental performance measurement because it can provide a synthetic standardized environmental performance index when pollutants are suitably incorporated into the traditional DEA framework. Past studies about the application of DEA to environmental performance measurement often follow the concept of radial efficiency measures....

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...

The paper deals with Data Envelopment Analysis (DEA) and Artificial Neural Network (ANN). We believe that solving for the DEA efficiency measure, simultaneously with neural network model, provides a promising rich approach to optimal solution. In this paper, a new neural network model is used to estimate the inefficiency of DMUs in large datasets.