Data Envelopment Analysis (DEA) is a great approach used for measuring relative efficiencies and performance of a collection of Decision Making Units (DMUs). These used in the various forms, such as hospitals, universities, air force, banks, courts, business firms, and others, including the performance of countries, regions, etc. One of the earliest applications of DEA called Education. It was ...

performance evaluation of universities is an important issue between researchers. classic data envelopment analysis (dea) models with deterministic data have been used by many authors to measure efficiency of universities in different countries. however, dea with stochastic data are, rarely used to measure efficiency of universities. in this paper, input oriented model in stochastic data envelo...

Although data envelopment analysis (DEA) has been extensively used to assess the performance of mutual funds (MF), most of the approaches overestimate the risk associated to the endogenous benchmark portfolio. This is because in the conventional DEA technology the risk of the target portfolio is computed as a linear combination of the risk of the assessed MF. This neglects the important effects...

The purpose of this paper is to investigate the levels of technical efficiency in agricultural sector of MENA countries by using Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) approaches in 2007-2008. The results show that the total average of technical efficiency is as follows: DEABCC(0.770)>DEACCR(0.744)>SFA(0.479), and among all MENA countries, the best performanc...

Data Envelopment Analysis (DEA) is the methodology for evaluating the relative productive efficiency of decision making units (DMUs) that produce multiple-outputs using multiple-inputs. DEA was proposed for the first time in 1957 by Farrell; nonetheless, the wide usage of this method begun with its generalization and the linear programming formulation which is due to Charnes et al. (1978) (for ...

The purpose of conventional Data Envelopment Analysis (DEA) is to evaluate the performance of a set of firms or Decision-Making Units using deterministic input and output data. However, the input and output data in the real-life performance evaluation problems are often stochastic. The stochastic input and output data in DEA can be represented with random variables. Several methods have been pr...

  Performance evaluation of universities is an important issue between researchers. Classic data envelopment analysis (DEA) models with deterministic data have been used by many authors to measure efficiency of universities in different countries. However, DEA with stochastic data are, rarely used to measure efficiency of universities. In this paper, input oriented model in stochastic data env...

The study was carried out to provide empirical evidence on technical efficiency of maize production in Nigeria using parametric and non-parametric approaches. The study employed annual secondary data on maize production in Nigeria from 1971 to 2010.Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA) were used to estimate the technical efficiency of maize production. The resul...

The models described in this paper for treating congestion in DEA are extended by according them chance constrained programming formulations. The usual route used in chance constrained programming is followed here by replacing these stochastic models with their ‘‘deterministic equivalents.’’ This leads to a class of non-linear problems. However, it is shown to be possible to avoid some of the n...

Literature suggests two main approaches, parametric and non-parametric, for constructing efficiency frontiers using which efficiency scores of other units can be based. Parametric functions can be either deterministic or stochastic in nature. However, when multiple inputs and outputs are encountered, Data Envelopment Analysis (DEA), a non-parametric approach, is a powerful tool used for decades...