data envelopment analysis (dea) as a non-parametric method for efficiency measurement allows decision making units (dmus) to select the most advantageous weight factors in order to maximize their efficiency scores.  in most practical applications of dea presented in the literature, the presented models assume that all inputs are fully desirable. however, in many real situations undesirable inpu...

Deriving weights from a pairwise comparison matrix (PCM) is a subject for which a wide range of methods have ever been presented. This paper proposes a common weight multi criteria decision analysis-data envelopment analysis (MCDA-DEA) approach with assurance region for weight derivation from a PCM. The proposed model has several merits over the competing approaches and removes the drawbacks of...

abstract. a practical common weight scalarizing function methodology with an improved discriminating power for technology selection is introduced. the proposed scalarizing function methodology enables the evaluation of the relative efficiency of decision-making units (dmus) with respect to multiple outputs and a single exact input with common weights. its robustness and discriminating power are...

There is increasing interest in fully ranking the performance of organizational units with multiple inputs and outputs. We smooth the congenital differences of efficient and inefficient units. The concept of the secondary frontier is to eliminate the effects of super-efficiency and inefficiency. The pseudo secondary frontier is constructed to lie between the efficient and inefficient units. Lo...