data envelopment analysis (dea) is a nonparametric approach to estimate relative efficiency of decision making units (dmus). dea and is one of the best quantitative approach and balanced scorecard (bsc) is one of the best qualitative method to measure efficiency of an organization. since simultaneous evaluation of network performance of the quad areas of bsc model is considered as a necessity a...

Data Envelopment Analysis (DEA) has been applied in many efficiency studies in the banking sector. Conventional DEA models consider the system as a single-process black box. There are however a number of so-called network DEA approach that consider the system as composed by distinct processes or stages, each one with its own inputs and outputs and with intermediate flows among the stages. In th...

Efficiency evaluation is vital as it is able to determine the financial performance of the companies. Efficiency describes how well the companies in utilizing their inputs to generate outputs. The objective of this study is to propose a financial ratio based Data Envelopment Analysis (DEA) model to evaluate and compare the efficiency of listed technology companies in Malaysia for the period of ...

The conventional paradigm in data envelopment analysis (DEA) is to develop an efficiency measurement model that assumes the input and output data are precise and equal to some nominal values. However, this paradigm does not take into consideration the inherent uncertainties in real-life performance measurement problems. As a result of these uncertainties, the input and output data may take non-...

This paper established a comprehensive model of Delphi-AHP-DEA-FCE to evaluate competitiveness of sports tourism destinations. Research shows that, this model effectively constructed an indicator system for the competitiveness of sports tourism destination, and weights for all indicators were obtained by analysis. Second, the comprehensive model translated fuzzy evaluation into numerical values...

In this paper, we discuss the relationship between multi-attribute utility theory and DEA models without explicit inputs (DEA-WEI), including dual models and some theoretical analysis of DEA-WEI models. We then propose generic DEA-WEI models with quadratic utility terms. Finally, we provide illustrative examples to show that DEA-WEI with suitable quadratic utility terms are able to reflect some...

The advent of data envelopment analysis (DEA) enabled the measurement of efficiency to be extended to the case of multiple outputs. Prior to DEA we had the parametric approach based on multiple regression. We highlight some difficulties associated with these two approaches and present a hybrid which overcomes them whilst maintaining the respective advantages of each. This hybrid models the effi...

In this paper using DEA technique, four-stage DEA model mooted in order to consider the situation in which returned products exist. Returned products are the inputs of the previous sub-processes that need to be reprocessed due to existence of flaws. Here, a supply chain with four stages as supplier, manufacture, distributor, and retailer with intermediate and return products has been considered...

Most of ex-ante impact assessment policy models have been based on a parametric approach. We develop a novel non-parametric approach, called Inverse DEA. We use non parametric efficiency analysis for determining the farm’s technology and behaviour. Then, we compare the parametric approach and the Inverse DEA models to a known data generating process. We use a bio-economic model as a data genera...