This paper discusses and reviews the use of super-eciency approach in data envelopment analysis (DEA) sensitivity analyses. It is shown that super-eciency score can be decomposed into two data perturbation components of a particular test frontier decision making unit (DMU) and the remaining DMUs. As a result, DEA sensitivity analysis can be done in (1) a general situation where data for a tes...

Benchmarking is often claimed to be a powerful means of continuous improvement for facility managers but benchmarking tools in facility management are less developed than for other services businesses. The most common information which Facility Managers can get from benchmarking results is their positions of performance. Rankings on performance, without further analysis, cannot help much for th...

data envelopment analysis (dea) is a nonparametric technique that includes models to evaluate the relative efficiency of decision making units (dmus). it has the ability to separate efficient units and inefficient units. one of the applications of this mathematical technique is evaluating performance of supply chain. according to such as the inefficiency factors of one dmu, is existence congest...

The evaluation of productivity of educational units during the last decades has become an important priority for many countries. A current approach considers the schools as production units that use multiple inputs and produce multiple outputs. Data Envelopment Analysis (DEA) is a very effective methodology for the estimation of relative efficiencies in the presence of multiple inputs and outpu...

This paper provides simulation evidence concerning some statistical properties of two different approaches to technical efficiency estimation for multipleoutput production under noisy conditions: The Ray Frontier Approach (RFA) from Löthgren (1997) and DEA+ proposed in Gstach (1996). RFA, unlike earlier approaches in the realm of stochastic frontier analysis, is capable of efficiency estimation...

Cross-efficiency evaluation is an effective approach to ranking decision making units (DMUs) that utilize multiple inputs to produce multiple outputs. Its models can usually be developed in a way that is either aggressive or benevolent to other DMUs, depending upon the decision maker (DM)’s subjective preference to the two extreme cases. This paper proposes several new data envelopment analysis...

Many types of facility location/allocation models have been developed to find optimal spatial patterns with respect to location criteria such as: cost, time, coverage, and access. In this paper we develop and test location modeling formulations that utilize aspects of the data envelopment analysis (DEA) efficiency measure to find optimal and efficient facility location/allocation patterns. Solv...

Here, we examine the capability of artificial neural networks (ANNs) in sensitivity analysis of the parameters of efficiency analysis model, namely data envelopment analysis (DEA). We are mainly interested to observe the required change of a group of parameters when another group goes under a managerial change, maintaining the score of the efficiency. In other words, this methodology provides a...

the evaluation and selection of recommender systems is a difficult decision making process. this difficulty is partially due to the large diversity of published evaluation criteria in addition to lack of standardized methods of evaluation. as such, a systematic methodology is needed that explicitly considers multiple, possibly conflicting metrics and assists decision makers to evaluate and find...