Data Envelopment Analysis (DEA) is a method for evaluating the performance of set homogeneous Decision Making Units (DMUs). When there are uncertainties in problem data, original DEA models might lead to incorrect results. In this study, we present two stochastic p-robust two-stage Network (NDEA) DMUs efficiency estimation under uncertainty based on Stackelberg (leader-follower) and centralized game theory models. This allows deleterious effect objective function better hedge against...

The slacks-based measure (SBM) and additive SBM (ASBM) models are two widely used DEA acting based on inputs outputs slacks giving efficiency scores between zero unity. In this paper, we use both with the application of weak disposability axiom for to evaluate in a two-stage structure presence undesirable outputs. external evaluation, model is reformulated as linear program ASBM second-order cone (SOCP) that convex programming problem. internal specific choice weights linearized while...

Purpose The purpose of this paper is to present a stochastic p-robust data envelopment analysis (DEA) model for decision-making units (DMUs) efficiency estimation under uncertainty. main contribution consists the development more robust system in situations inputs proposed used measurement commercial Iranian bank. Design/methodology/approach This has been arranged launch along following steps: classical Charnes, Cooper, and Rhodes (CCR) DEA was briefly reviewed. After that, introduced then...

The two-stage data envelopment analysis models are among the widely used mathematical programming approaches to evaluate performance of structures. In this paper, a structure with shared inputs and feedback is studied. To reduce undesirable outputs, an additive slack-based measure model proposed stages overall efficiencies, while outputs weakly disposable. As it does not require determining weights for combining stages’ all Pareto optimal efficiencies can be gained. addition, approach...

Uncertain data and undesirable outputs are two challenging issues in traditional envelopment analysis (DEA) models while dealing with the environmental efficiency estimation of decision-making units (DMUs). This study considers Stackelberg centralized game theory approach a two-stage DEA model for evaluating DMUs presence uncertainty simultaneously. To tackle uncertainty, we apply p-robust technique assume that weakly disposable. The proposed fractional linearized using Charnes Cooper...

Purpose This paper aims to apply a new approach for resource sharing and efficiency estimation of subunits in the presence non-discretionary factors partial impacts among inputs outputs data envelopment analysis (DEA) framework. Design/methodology/approach First, inspired by Imanirad et al. ’s model (2013), authors consider that each decision-making unit (DMU) may consist several subunits, which can be affected inputs. After that, Banker Morey’s (1996) is used modeling factors. For measuring...

Network Data Envelopment Analysis (NDEA) models assess the processes of underlying system at a certain moment and disregard dynamic effects in production process. Hence, distorted efficiency evaluation is gained that might give misleading information to decision-making units (DMUs). Malmquist–Luenberger Productivity Index (MPI) assesses changes over time, which are measured as product recovery frontier-shift terms, both coming from DEA framework. In this study, form MPI involving network...