 Recently, Khodabakhshi and Aryavash have introduced a ranking method [Applied Mathematics Letters, 25 (2012) 2066-2070.], which is based on an optimistic-pessimistic approach of data envelopment analysis (DEA). This method ranks all decision making units according to a combination of their minimum and maximum possible efficiency scores which are determined by solving two linear programming mo...

Data Envelopment Analysis (DEA) is one of the most widely used methods in the measurement efficiency and productivity of Decision Making Units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper introduces a neural network backpropagation Data Envelopment Analysis. Neural network requirements of computer memo...

More than 200 papers have been published in the last 20 years on the topic of health supply chains (HSC). Looking at the research methodologies employed, less than 15 papers apply data envelopment analysis (DEA) models. This is in contrast to, for example, A Network Data Envelopment Analysis (NDEA) Model for Supply Chain Performance Evaluation where several reviews on respective NDEA models hav...

Literature of productive efficiency analysis is currently divided between two main paradigms: the parametric Stochastic Frontier Analysis (SFA) and the deterministic, nonparametric Data Envelopment Analysis (DEA). This paper develops a new encompassing framework that melds the SFA-style stochastic composite error term to the DEA-type nonparametric frontier that satisfies monotonicity and concav...

Data envelopment analysis (DEA) has been a wildly used powerful method to measure efficiencies of decision making units (DMUs). However, DEA efficiency scores are influenced by uncontrollable factors for respective DMUs. Previous studies attempted separating such factors from DEA scores. Fried et al. [4] proposed a multi-stage data adjustment approach using DEA and a regression model, and sever...

We developed an alternative approach for measuring information and communication technology (ICT), applying Data Envelopment Analysis (DEA) using data from the International Telecommunications Union as a sample of 183 economies. We compared the ICT-Opportunity Index (ICT-OI) with our DEAOpportunity Index (DEA-OI) and found a high correlation between the two. Our findings suggest that both indic...

This study proposes the Data Envelopment Analysis (DEA) ranking for resource allocation between Iran's Medical Universities based on a five years observation data (2004-2008). We compared the DEA ranking results with the traditional ranking approach applied by the Ministry of Health and Medical Education of Iran. Based on the DEA score the amount of budget is proposed for each university for th...

Efficiency measurement is an important issue for any firm or organization. Efficiency measurement allows organizations to compare their performance with their competitors’ and then develop corresponding plans to improve performance. Various efficiency measurement tools, such as conventional statistical methods and non-parametric methods, have been successfully developed in the literature. Among...

Data envelopment analysis (DEA) is a non-parametric method for evaluating the relative efficiency of decision making units (DMUs) on the basis of multiple inputs and outputs. The context-dependent DEA is introduced to measure the relative attractiveness of a particular DMU when compared to others. In real-world situation, because of incomplete or non-obtainable information, the data (Input and ...