Traditional cost-efficiency analysis methods require exact and precise values for inputs, outputs and input prices. However, this is not the case in many real-life applications. This study proposes a rough costefficiency approach to the problem of ranking efficient decision making units (DMUs). Based on rough set theory, a nonparametric methodology for cost-efficiency analysis is developed. The...

Ranking efficiency based on DEA results can be used for grouping DMUs. The resulting group membership can be partly related to environmental characteristics of DMU, which are not used either as input or output. Utilizing the expert knowledge on super efficiency DEA results, we propose a multinomial Dirichlet regression model which can be used for the purpose of selection of new projects. A case...

Nowadays most of manufacturing firms in accordance with continuous changes in the market and the today’s competitiveness world are competing for meeting demand, increasing quality and decreasing costs. For reaching these goals, it is necessary to select a suitable flexible manufacturing system (FMS) for the most of manufactures. The aim of this paper is applying a method for evaluating the flex...

In this article, I propose a hybrid data envelopment analysis (DEA) system that utilizes a methodology combining the tier analysis with the neural clustering method. I aim to show that the hybrid system can be used to evaluate the inter-organizational efficiency in the life insurance companies. The application is unfolded in two phases. In the first phase, DEA is repetitively used to evaluate t...

Data Envelopment Analysis models are based on linear programming problems (LPP) to determine the efficiency of Decision-Making Units (DMUs). This process can be computationally intense, as a LPP has to be run for each unit. Besides, a typical DEA LPP has a large number of redundant constraints concerning the inefficient DMUs. That results in degenerate LPPs and in some cases multiple efficient ...

The purpose of the current paper is to clarify the misunderstanding in using the constant returns to scale (CRS) model in data envelopment analysis (DEA) to estimate returns to scale (RTS) classi®cation. By illustrating the following two di€erent assumptions: (a) all decision making units (DMUs) are assumed to be compared to a CRS frontier in the CCR model, i.e., all DMUs are assumed to be capa...

DEA is a non-parametric and linear programming based technique that attempts to maximize a decision making unit’s (DMUs) relative efficiency, expressed as a ratio of outputs to inputs, by comparing a particular unit’s efficiency with the performance of a group of similar DMUs that are delivering the same service. The traditional DEA models treat DMUs as black boxes whose internal structure is i...

This paper deals with the selection of the profiles of weights to be used in cross-efficiency evaluations. In an attempt to prevent unrealistic weighting schemes, one of the issues of main interest that we address here is that of the zero weights, since their use implies that some of the variables considered are excluded from the assessments to be made. In the calculation of cross-efficiency sc...

Data Envelopment Analysis (DEA) is a powerful tool for measuring the relative efficiency for a set of Decision Making Units (DMUs) that transform multiple inputs into multiple outputs. In centralized decisionmaking systems, management normally imposes common resource constraints to maximize operating revenues and minimize operating expenses. In this study, we propose an alternative DEA model fo...

Data envelopment analysis (DEA) is a linear programming based non-parametric technique for evaluating the relative efficiency of homogeneous decision making units (DMUs) on the basis of multiple inputs and multiple outputs. There exist radial and non-radial models in DEA. Radial models only deal with proportional changes of inputs/outputs and neglect the input/output slacks. On the other hand, ...