DEA is a non-parametric and linear programming based technique that attempts to maximize a decision making unit’s (DMUs) relative efficiency, expressed as a ratio of outputs to inputs, by comparing a particular unit’s efficiency with the performance of a group of similar DMUs that are delivering the same service. The traditional DEA models treat DMUs as black boxes whose internal structure is i...

Performance evaluation in conventional data envelopment analysis (DEA) requires crisp numerical values. However, the observed values of the input and output data in real-world problems are often imprecise or vague. These imprecise and vague data can be represented by linguistic terms characterised by fuzzy numbers in DEA to reflect the decision-makers' intuition and subjective judgements. This ...

The blood group antigen Dog Erythrocyte Antigen (DEA) 1.1 is clinically the most important canine blood group as DEA 1.1 antibodies are capable of causing acute haemolytic, potentially life-threatening transfusion reactions. Dogs do not have naturally occurring antibodies to DEA 1.1 but are rapidly sensitised by the first incompatible transfusion. The prevalence of DEA 1.1 in the general dog po...

This study introduces a revised data envelopment analysis (DEA) model to explore a new use of DEA for the environmental assessment in which outputs are classified into desirable (good) and undesirable (bad). Such an output separation is important in the DEA-based environmental assessment. We used a Range-Adjusted Measure (RAM) DEA model that is a kind of non-radial DEA model for combining the t...

Management performance measurement is a complex task since multiple inputs and multiple outputs are involved in the process. This study attempted to develop a comprehensive framework to encompass the basic concepts of Balance Scorecard (BSC) and data envelope analysis (DEA) to measure the management performance. BSC and DEA are complemental to each other. On one hand, BSC can provide appropriat...

Airport efficiency is an area of increasing interest to academics, policy makers and practitioners. This has resulted in a body of literature applying various econometric techniques to compare efficiency between different samples of airports. This paper uses the multi-criteria decision making method Analytic Hierarchy Process (AHP) to incorporate the weightings of input and output variables int...

This paper processes a unification of Fuzzy TOPSIS and Data Envelopment Analysis DEA to select the units with most efficiency. This research is a two-stage model designed to fully rank the organizational alternatives, where each alternative has multiple inputs and outputs. First, the alternative evaluation problem is formulated byData Envelopment Analysis DEA and separately formulates each pair...

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...

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,...

Proposed in this study is a hybrid model for supporting the performance of a department within Amir Kabir University in Iran. The proposal is a two-stage model designed to fully rank the organizational departments where each faculty has multiple inputs and outputs. First, the Data Envelopment Analysis (DEA) separately formulates each pair of units. In the second stage, the pair-wise evaluation ...