As data envelopment analysis (DEA) has been developed both in theory and application, the calculation of models become more and more important. Although many DEA software tools have been built for the calculation of the DEA models, there are some deficiencies in embedding them into enterprise management information system (MIS). As an extension of this work, an idea was generated in this paper,...

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...

Data envelopment analysis (DEA) is recognized as a powerful analytical research tool for performance evaluations by obtaining empirical estimates of relations between multiple inputs and multiple outputs. In order to further embody the hierarchical structures of numerous performance evaluation problems in the DEA framework, a generalized multiple layer DEA (MLDEA) model is proposed, and its lin...

Data Envelopment Analysis (DEA) has been widely studied in the literature since its inception with Charnes, Cooper and Rhodes work in 1978. The methodology behind the classical DEA method is to determine how much improvements in the outputs (inputs) dimensions is necessary in order to render them efficient. One of the underlying assumptions of this methodology is that the units consume and prod...

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...

This paper investigated the performance of Malaysian power plants from year 2015 to 2017 using Malmquist Total Factor Productivity (TFP) index, which is based on Data Envelopment Analysis (DEA). approach offers substantial advantages as compared other existing methods it can measure productivity changes over time for a variety inputs and outputs. Moreover, comprises two primary components: tech...

This study consists of three types of vendor selection models in supply chains and presents a decision making scheme for choosing appropriate method for supplier selection under certainty, uncertainty and probabilistic conditions. These models are, Data Envelopment Analysis (DEA), Fuzzy Data Envelopment Analysis (FDEA), and Chance Constraint Data Envelopment Analysis (CCDEA). In FDEA model we u...

The paper uses Data Envelopment Analysis (DEA) to assess the efficiency of the Depertments of the University of Trieste, considering both research and teaching issues. General guidelines for selecting input and output flows are proposed, different DEA models are considered and discussed, and the quantitative outcomes of the evaluation are analyzed.

The purpose of this paper is to develop an output oriented methodology for calculating productivity growth by using Malmquist productivity index (MPI) and two different data envelopment analysis (DEA) views (optimistic and pessimistic) simultaneously, and apply it to five Iranian Commercial Banks over the four time period (2009-2013). Consequently, we have proposed a new approach called the dou...

An original data envelopment analysis (DEA) model is to evaluate each decision-making unit (DMU) with a set of most favorable weights of performance indices. The efficient DMUs obtained from the original DEA construct an efficient (bestpractice) frontier. The original DEA can be considered to identify good (efficient) performers in the most favorable scenario. For the purpose of identifying bad...