This paper studies the inverse data envelopment analysis using the nonradial enhanced Russell model. Necessary and sufficient conditions for inputs/outputs determination are introduced based on Pareto solutions of multiple-objective linear programming. In addition, an approach is investigated to identify extra input/lack output in each of input/output components (maximum/minimum reduction/incre...

In this paper we present a method for measuring the efficiency for any economical branch. We construct the econometric approach of production frontiers, using the DEA technique (Data envelopment analysis), based on the mathematical programming approach. We effectuate an analysis of some certain data concerning the efficiency or the inefficiency of the branches, using the Efficiency Measurement ...

Data envelopment analysis (DEA) is a nonparametric approach to estimate relative efficiency of Decision Making Units (DMUs). DEA is one of the best quantitative approaches and balanced scorecard (BSC) is one of the best qualitative methods to measure efficiency of an organization. Since simultaneous evaluation of network performance of the quad areas of BSC model is considered as a necessity an...

We introduce a simple method for detecting outliers in Data Envelopment Analysis. The method is based on two scalar measures. The first is the relative frequency with which an observation appears in the construction of the frontier when testing the efficiency of other observations, and the second is the cumulative weight of an observation in the construction of the frontier. We provide a link t...

OBJECTIVE To develop an assessment tool to evaluate the efficiency of federal university general hospitals. METHODS Data envelopment analysis, a linear programming technique, creates a best practice frontier by comparing observed production given the amount of resources used. The model is output-oriented and considers variable returns to scale. Network data envelopment analysis considers link...

The classification of fuzzy uncertain data is considered one of the most challenging issues in data analysis. In spite of the significance of fuzzy data in mathematical programming, the development of the analytical methods of fuzzy data is slow. Therefore, the current study proposes a new fuzzy data classification method based on fuzzy data envelopment analysis (DEA) which can handle strea...

Data Envelopment Analysis (DEA) is a linear programming based technique that was developed to evaluate relative efficiency of nonprofit and public sector Decision Making Units (DMU's) that use multiple inputs to produce multiple outputs. In this study, DEA is evaluated and tested for use as a managerial audit tool to identify and measure inefficiencies among a set of DI'IU's. Based on three app...

The classification of fuzzy uncertain data is considered one of the most challenging issues in data analysis. In spite of the significance of fuzzy data in mathematical programming, the development of the analytical methods of fuzzy data is slow. Therefore, the current study proposes a new fuzzy data classification method based on fuzzy data envelopment analysis (DEA) which can handle strea...

Data envelopment analysis (DEA) as introduced by Charnes et al [3] is a linear programming technique that has widely been used to evaluate the relative efficiency of a set of homogenous decision making units (DMUs). In many real applications, the input-output variables cannot be precisely measured. This is particularly important in assessing efficiency of DMUs using DEA, since the efficiency sc...