In the conventional data envelopment analysis (DEA) internal sub-processes of the production units are ignored. The current paper develops a network-DEA super-efficiency model to compare the performance of efficient network systems. A new ranking method is developed by aggregating the computed super-efficiency scores with a J-divergence measure. The proposed approach is then applied to evaluate...

evaluation of corporate performance has been one of the main issues in managing decision making. nowadays, evaluation of the suppliers is a completely strategic process because organizations rarely change their suppliers. thesuppliers also do their best to remain stable in the loop of supply chain. hence, it is important to evaluate the suppliers and not something to be done once at a time. it ...

Data envelopment analysis (DEA), based on mathematical programming techniques, is a popular method for assessing the relative efficiency of various decision-making units (DMUs). Efficient DEA computations need to circumvent intensive time-consuming calculations. This paper indicates that the “corner points” in single input and single output scatter plot has extreme efficiency with regard to the...

data envelopment analysis (dea) technique now widely use for efficiency evaluation of a set of decision making units (dmus). as regards of the necessity for ranking efficient units different dea models presented each of which has advantages and rank efficient units from special aspects. note that all the existing ranking models have disadvantages, as well and there is not a model in which all t...

Article history: Received 5 January 2014 Received in revised format 8 March 2014 Accepted 11 March 2014 Available online 12 March 2014 Measuring the relative efficiency of banking industry has been a popular subject among both practitioners and academicians. Data envelopment analysis (DEA) has been widely applied for different purposes. This paper presents an empirical investigation to measure ...

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...

‎the purpose of this paper is to offer the equitable method for ranking decision making units(dmus) based on the dynamic data envelopment analysis (ddea) concept, where quasi-fixed inputs or intermediate products are the source of inter-temporal dependence between consecutive periods. in fact, this paper originally makes the use of an approach extending the ranking of dmus in dea by khodabakhsh...

This article compares two techniques: Data Envelopment Analysis (DEA) and Factor Analysis (FA) to aggregate multiple inputs and outputs in the evaluation of decision making units (DMU). Dِata envelopment analysis (DEA), a popular linear programming technique, is useful to rate comparatively operational efficiency of DMUs based on their deterministic or stochastic input–output data. Factor analys...

  A data envelopment analysis (DEA) method can be regarded as a useful management tool to evaluate decision making units (DMUs) using multiple inputs and outputs. In some cases, we face with imprecise inputs and outputs, such as fuzzy or interval data, so the efficiency of DMUs will not be exact. Most researchers have been interested in getting efficiency and ranking DMUs recently. Models of th...

The paper deals with models and methods for evaluation of efficiency of production units. The standard modeling approach for evaluation of efficiency is data envelopment analysis (DEA) based on the definition of efficiency as the ratio of outputs produced by the unit and inputs spent in the production process. Standard data envelopment analysis models divide the units into inefficient and effic...