because of the piecewise linear nature of the data envelopment analysis (dea) frontier, the optimal multipliers of the dea models may not be unique. choosing weights from alternative optimal solutions of dual multiplier models is one of the most frequently studied subjects in the context of dea. in this paper, the authors have been inspired by the idea of cooper et al. (2011) to propose a linea...

the performance of a decision making unit (dmu) can be evaluated in either across-sectional or a time-series manner, and data envelopment analysis (dea) is a useful method for both types of evaluation. the malmquist productivity index (mpi) evaluates the change in efficiency of a dmu between two time periods. it is defined as the product of the catch-up and frontier-shift terms. in this paper, ...

bankruptcy in the same amount of time and history is very rampant and therefore the vision of the future can be prevented. using data envelopment analysis (dea) and malmquist index can precise evaluating of the performances of many different kinds of decision making units (dmu) such as hospitals, universities, business firms, etc. in this paper, we will modify directional distance formulation o...

in data envelopment analysis, the relative efficiency of a decision making unit (dmu) is defined as the ratio of the sum of its weighted outputs to the sum of its weighted inputs allowing the dmus to freely allocate weights to their inputs/outputs. however, this measure may not reflect a the true efficiency of a dmu because some of its inputs/outputs may not contribute reasonably in computing t...

Data Envelopment Analysis (DEA) is a management tool aimed to determine relative eeciency of independent decision making units. Each unit is fully characterized by a set of incommensurable input and output values. This technique is able, by solving linear programming problems, to discriminate between eecient and ineecient units and to provide targets for the ineecient units. The work of the aut...

the problem of utilizing undesirable (bad) outputs in dea models often need replacing the assumption of free disposability of outputs by weak disposability of outputs. the kuosmanen technology is the only correct representation of the fully convex technology exhibiting weak disposability of bad and good outputs. also, there are some specific features of non-radial data envelopment analysis (dea...

one of the difficulties of data envelopment analysis(dea) is the problem of de ciency discriminationamong efficient decision making units(dmus) and hence, yielding large number of dmus as efficientones. the main purpose of this paper is to overcome this inability. one of the methods for rankingefficient dmus is minimizing the coefficient of variation (cv) for inputs-outputs weights. in this pap...

in this paper, by investigating the common weights concept and dea models with nonlinear virtual inputs/outputs, we introduce a model for evaluating the decision making units with nonlinear virtual inputs and outputs based on the common weights.

performance evaluation of universities is an important issue between researchers. classic data envelopment analysis (dea) models with deterministic data have been used by many authors to measure efficiency of universities in different countries. however, dea with stochastic data are, rarely used to measure efficiency of universities. in this paper, input oriented model in stochastic data envelo...