in a recent paper in this journal, yang et al. [feng yang, dexiang wu,liang liang, gongbing bi & desheng dash wu (2009), supply chaindea:production possibility set and performance evaluation model] definedtwo types of supply chain production possibility set which were proved to beequivalent to each other. they also proposed a new model for evaluatingsupply chains. there are, however, some short...

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...

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...

For the issue of the lack in plotting analysis method in the research of DEA, this paper introduces a new graphic method—Co-Plot. It can demonstrate DMUs and variables visually in two-dimensional space, and enable the analysis of them at the same time. By applying the ratio relationship among variables, Co-Plot can be combined with DEA in a way to display the results of DEA easily and intuitive...

A fundamental weakness of the Data Envelopment Analysis (DEA) is its weak discrimination in cases when a small number of decision making units are compared. Therefore, in such cases the basic DEA model (optimistic and pessimistic) is used in combination with other methods or additional constraints are added to the model. In this paper, the cross-efficiency method was combined with a self-rankin...

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...

Data envelopment analysis (DEA) is a popular non-parametric approach to examine performance and productivity of airlines; however, it could not provide statistical information such as confidence intervals on the estimated efficiency scores. We combined stochastic frontier DEA into single framework disentangle noise ‘pure’ inefficiency from scores accordingly for Monte-Carlo simulation verified ...

In order to rationalize material selection in green design, this study presents an attempt combine the methods of generalized Data Envelopment Analysis (DEA) and Technique for Order Preference by Similarity Ideal Solution (TOPSIS). By establishing a index system, G-CCR model DEA was first used select effective materials from candidate samples, TOPSIS then sort suppliers. The combined DEA/TOPSIS...

Life-cycle (LC) approaches play a significant role in energy policy making to determine the environmental impacts associated with the choice of energy source. Data envelopment analysis (DEA) can be combined with LC approaches to provide quantitative benchmarks that orientate the performance of energy systems towards environmental sustainability, with different implications depending on the sele...