Data Envelopment Analysis (DEA) is a widely used mathematical programming approach for evaluating the relative efficiency of Decision Making Units (DMUs). Conventional DEA methods treat DMUs as ‘‘black boxes’’, focusing entirely on their relative efficiencies. We propose an efficient two-stage fuzzy DEA model to calculate the efficiency scores for a DMU and its sub-DMUs. We use the Stackelberg ...

Data Envelopment Analysis (DEA) as a non–parametric method is used to measure relative performance of organizational units. The aim of this paper is to develop a new model to evaluate the efficiency of a general two-stage network structures proposed by Li et al.  (2012) for measuring the performance of Decision Making Units (DMUs). In addition, this paper expands the work of Li et al. (2012) an...

Data Envelopment Analysis (DEA) is one of the best methods for measuring the efficiency and productivity of Decision Making Units (DMU). Evaluating the efficiency of DMUs which have two or several stages by using the conventional DEA models, is equal to consider them as black box. This method, omits the effect of intermediate measure on efficiency. Therefore, just the first network inputs and t...

this paper processes a combined method, based on vikor and data envelopment analysis (dea) to select the units with most efficiency. we utilize the vikor as compromise solution method. this research is a two-stage model designed to fully rank the alternatives, where each alternative has multiple inputs and outputs. the problem involves belief parameters in the solution procedure. first, the alt...

Analysis of production and investment efficiency in the Mexican food industry: Application two-stage DEA | Martin Flegl, Carlos Alberto Jiménez-Bandala, Isaac Sánchez-Juárez, Edgar Matus Agricultural Journals