this paper proposes an alternative approach for efficiency analysis when a set of dmus uses interval scale variables in the productive process. to test the influence of these variables, we present a general approach of deriving dea models to deal with the variables. we investigate a number of performance measures with unrestricted-in-sign interval and/or interval scale variables.

Data Envelopment Analysis (DEA) requires that the data for all inputs and outputs are known exactly. When some outputs and inputs are known decision variables, such as interval data and ordinal data, the DEA models becomes a nonlinear programming problem and is called imprecise DEA (IDEA). When data assume to be interval, decision making units (DMUs) can divide to three classes as follows: (I) ...

Data Envelopment Analysis (DEA) is widely used in banking sector to measure the efficiency of the banks. This paper evaluates the performance of the banks in India using cost, revenue and profit models of DEA and comes out with a comprehensive efficiency index for banks, by combing the efficiency scores of various DEA models, using the Shannon entropy. In general, the banks included in this stu...

copies of this document for non-commercial purposes by any means, provided that this copyright notice appears on all such copies. This article integrates fuzzy set theory in Data Envelopment Analysis (DEA) framework to compute technical efficiency scores when input and output data are imprecise. The underlying assumption in convectional DEA is that inputs and outputs data are measured with prec...

This paper proposes a data envelopment analysis (DEA) approach to measurement and benchmarking of service quality. Dealing with measurement of overall service quality of multiple units with SERVPERF as multiple-criteria decision-making (MCDM), the proposed approach utilizes DEA, in particular, the pure output model without inputs. The five dimensions of SERVPERF are considered as outputs of the...

The aim of this paper is to estimate the overall performance of mutual funds in Croatia in terms of their relative efficiency based on several performance indicators using data envelopment analysis (DEA). DEA is a non-parametric method that can provide an overall relative efficiency score of a certain fund given a number of risk, cost or reward or profitability measures. Since traditional mutua...

Supplier evaluation and selection, an important element in supplier-based manufacturing and supply chain management has been gaining attention in both academic literature and industrial practice. In this paper, we presented a modified data envelopment analysis (DEA) method for supplier selection which can operate under conditions of imprecise information. A brief description of the importance o...

Conventional data envelopment analysis (DEA) models assume real-valued inputs and outputs. In many occasions, some inputs and/ or outputs can only take integer values. In some cases, rounding the DEA solution to the nearest whole number can lead to misleading efficiency assessments and performance targets. This paper develops the axiomatic foundation for DEA in the case of integer-valued data, ...

Sensitivity of the returns to scale (RTS) classifications in data envelopment analysis is studied by means of linear programming problems. The stability region for an observation preserving its current RTS classification (constant, increasing or decreasing returns to scale) can be easily investigated by the optimal values to a set of particular DEA-type formulations. Necessary and sufficient co...