Literature of productive efficiency analysis is currently divided between two main paradigms: the parametric Stochastic Frontier Analysis (SFA) and the deterministic, nonparametric Data Envelopment Analysis (DEA). This paper develops a new encompassing framework that melds the SFA-style stochastic composite error term to the DEA-type nonparametric frontier that satisfies monotonicity and concav...

In the evaluation of non-efficient units by Data Envelopment Analysis (DEA) referenced Decision Making Units (DMU’s) have an important role. Unfortunately DMU’s with extra ordinary output can lead to a monopoly in a reference set, the fact called abnormality due to the outliers' data. In this paper, we introduce a DEA model for evaluating DMU’s under this circumstance. The layer model can resul...

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...

Marketing has a tradition in conducting scientific research with cutting-edge techniques developed in management science, such as data envelopment analysis (DEA) (Charnes et al. 1985). Two decades ago, Kamakura, Ratchford, and Agrawal (1988) applied DEA to examine market efficiency and consumer welfare loss. In this review of three new books, my purpose is (1) to provide a background of DEA for...

data envelopment analysis (dea) is a technique for measuring the efficiency of decision making units. in all models of the dea, for each unit under assessment, the numerical efficiency is obtained which may be less than or equal to one. given the possible large number of functional units, we use various ranking methods for evaluating units. one of the rating methods is balance index and topsis....

data envelopment analysis (dea) is a technique for measuring the efficiency of decision making units. in all models of the dea, for each unit under assessment, the numerical efficiency is obtained which may be less than or equal to one. given the possible large number of functional units, we use various ranking methods for evaluating units. one of the rating methods is balance index and topsis....

Data quality is critical to a successful data envelopment analysis (DEA) study. Outlier detection not only identifies suspicious data points and thus prevents the drawing of erroneous conclusions, but also can lead to the discovery of unexpected knowledge. This study develops a unified model to identify outliers in DEA studies by examining how they effect on the boundaries of a data set. The pr...

One of the main problems in efficiency analysis is to determinate the environmental variables that have an impact on the production process. This paper shows that applying bootstrap to data envelopment analysis (DEA) before performing classification and regression trees (CART) increase the quality of the results. In particular, employing data on the Italian Health System, the paper highlights t...

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...