malmquist productivity index (mpi) is a numeric index that is of great importance in measuring productivity and its changes. in recent years, tools like dea have been utilized for determining mpi. in the present paper, some models are recommended for calculating mpi when there are just ratio data available. then, using dea and dea-r, some models are proposed under the constant returns to scale ...

This paper considers the problem of interval scale data in the most widely used models of Data Envelopment Analysis (DEA), the CCR and BCC models. Radial models require inputs and outputs measured on the ratio scale. Our focus is on how to deal with interval scale variables especially when the interval scale variable is a difference of two ratio scale variables like profit or the decrease/incre...

In data envelopment analysis (DEA), mul-tiplier and envelopment CCR models eval-uate the decision-making units (DMUs) under optimal conditions. Therefore, the best prices are allocated to the inputs and outputs. Thus, if a given DMU was not efficient under optimal conditions, it would not be considered efficient by any other models. In the current study, using common weights in DEA, a number of...

Data envelopment analysis (DEA) is a mathematical programming technique for identifying efficiency scores of decision making units (DMUs). Since DEA models cannot present efficient frontiers of PPS, in order to do this, we introduce a method for identifying efficient frontier for DMUs with interval data.

One of the major problems in Data Envelopment Analysis (DEA) is to determine the projection of inefficient Decision Making Units (DMUs) into the efficient frontier. In conventional DEA models, inputs and outputs of inefficient DMUs alter arbitrarily for reaching to the efficient frontier. Nevertheless, sometimes the ability of DMUs is defined and restricted. Moreover, there are situations in th...

Data envelopment analysis (DEA) is a common technique in measuring the relative efficiency of a set of decision making units (DMUs) with multiple inputs and multiple outputs. ‎‎Standard DEA models are ‎‎quite limited models‎, ‎in the sense that they do not consider a DMU ‎‎at different times‎. ‎To resolve this problem‎, ‎DEA models with dynamic ‎‎structures have been proposed‎.‎In a recent pape...

Traditional data envelopment analysis (DEA) models deal with measurement of relative efficiency of decision making units (DMUs) in which multiple-inputs consumed to produce multiple-outputs. One of the drawbacks of these models is neglecting internal processes of each system, which may have intermediate products and/or independent inputs and/or outputs. In this paper some methods which are usab...

Malmquist Productivity Index (MPI) is a numeric index that is of great importance in measuring productivity and its changes. In recent years, tools like DEA have been utilized for determining MPI. In the present paper, some models are recommended for calculating MPI when there are just ratio data available. Then, using DEA and DEA-R, some models are proposed under the constant returns to scale ...

The existing data envelopment analysis (DEA) models for measuring the relative efficiencies of a set of decision making units (DMUs) using various inputs to produce various outputs are limited to crisp data. The notion of fuzziness has been introduced to deal with imprecise data. Fuzzy DEA models are made more powerful for applications. This paper develops the measure of efficiencies in input o...