Data envelopment analysis (DEA) is a non-parametric approach for measuring the relative efficiencies of peer decision making units (DMUs). Many studies have examined DEA efficiencies of two-stage systems, where all the outputs from the first stage are the only inputs to the second stage. Although single-stage DEA models with undesirable input-outputs have been extensively studied, there still l...

As data envelopment analysis (DEA) has been developed both in theory and application, the calculation of models become more and more important. Although many DEA software tools have been built for the calculation of the DEA models, there are some deficiencies in embedding them into enterprise management information system (MIS). As an extension of this work, an idea was generated in this paper,...

The conventional data envelopment analysis (DEA) measures the relative efficiencies of a set of decision making units (DMUs) with exact value of inputs and outputs. For imprecise data, i.e., mixtures of interval data and ordinal data, some methods have been developed to calculate the interval of the efficiency scores. This paper constructs a procedure to measure the efficiencies of DMUs with mi...

Data envelopment analysis (DEA) is a non-parametric technique for evaluation of relative efficiency of decision making units described by multiple inputs and outputs. It is based on solving linear programming problems. Since 1978 when basic DEA model was introduced many its modifications were formulated. Among them are two or multi-stage models with serial or parallel structure often called net...

This paper describes the DEA-based investment strategy for constructing of a stock portfolio in the Croatian stock market. The relative efficiency of the DMUs, which are in this case the selected stocks from Zagreb Stock Exchange, is obtained from the output oriented CCR and BCC models. The set of inputs consists of risk measures, namely return variance, Value at Risk (VaR) and beta coefficient...

This paper is drawn from the use of Data Envelopment Analysis (DEA) in helping a Portuguese bank to manage the performance of its branches. The bank wanted to set targets for the branches on such variables as growth in number of clients, growth in funds deposited and so on. Such variables can take positive and negative values but traditional DEA models, with some specialised exceptions, have hi...

Return-To-Scale (RTS) is a most important topic in DEA. Many methods are not obtained for estimating RTS in DEA, yet. In this paper has developed the Banker-Trall approach to identify situation for RTS for the BCC model "multiplier form" with virtual weight restrictions that are imposed to model by DM judgments. Imposing weight restrictions to DEA models often has created problem of infeasibili...

Mathematical programming is one of the areas to which fuq set theoq has been applied extensively. Primarily based on Bellman and Zadeh’s model of decision in fuzzy environments, models have been suggested which allow flexibility in constraints and nonlinear programming. Data envelopment analysis (DEA) is a method of evaluating relative efJiciencies for a group of similar units based on an efici...

A technique used to assess relative performance in a multiple input–output framework is data envelopment analysis (DEA). In basic DEA models, an entitymay show its best performanceby selecting input and output factor weights different from those selected by the other entities in thesample. Hence, when usingbasic DEAmodels, divergence of weighting schemesacross the assessedentitiescannot beruled...

Data envelopment analysis (DEA) literature has proposed alternative models for performance assessment in the presence of undesirable outputs, such as pollutant emissions, where increased outputs imply reduced performance. However, the case where global equilibrium of outputs should be imposed has not yet been considered. We propose that the zero sum gains DEA (ZSG-DEA) models look especially su...