data envelopment analysis (dea) models with interval inputs and outputs have been rarely discussed in dea literature. this paper, using the enhanced russell measurement proposes an extended model which permits the presence of interval scale variables which can take both negative and positive values. the model is compared with most well-known dea models of which include the ccr model, the bcc mo...

  In recent years, various time series models have been proposed for financial markets forecasting. In each case, the accuracy of time series forecasting models are fundamental to make decision and hence the research for improving the effectiveness of forecasting models have been curried on. Many researchers have compared different time series models together in order to determine more efficien...

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.

The basic assumption in data envelopment analysis patterns (DEA) (such as the CCR andBCC models) is that the value of data related to the inputs and outputs is a precise andpositive number, but most of the time in real conditions of business, determining precisenumerical value is not possible in for some inputs or outputs. For this purpose, differentmodels have been proposed in DEA for imprecis...

Data Envelopment Analysis (DEA) models with interval inputs and outputs have been rarely discussed in DEA literature. This paper, using the enhanced Russell measurement proposes an extended model which permits the presence of interval scale variables which can take both negative and positive values. The model is compared with most well-known DEA models of which include the CCR model, the BCC mo...

In this article, we investigate the measurement of performance in DMUs in which input and/or output values are given as imprecise data. By imprecise data, we mean that in some cases, we only know that the actual values are inside certain intervals, and in other cases, data are specified only as ordinal preference information. In this article, we present two distinct perspectives for determining...