This paper develops a method based on data envelopment analysis (DEA) for efficiency assessments taking into account the effect of non-discretionary factors. A typology that classifies the non-discretionary factors into two groups is proposed: the factors that characterize the external conditions where the decision making units (DMUs) operate (external factors), and the factors that are interna...

In the banking industry, the production process can be described as a two-stage process. There are a number of published data envelopment analysis (DEA) papers that study the bank performance with two-stage model. However, none of them is applied to identify bank failure. In fact, only one of them deals with negative profit data. In the real world, failed banks or firms often produced negative ...

Data envelopment analysis (DEA) is a non-parametric approach for measuring the relative efficiencies of peer decision making units (DMUs). Many studies have examined DEA efficiencies of two-stage systems, where all the outputs from the first stage are the only inputs to the second stage. Although single-stage DEA models with undesirable input-outputs have been extensively studied, there still l...

Anaerobic lagoons are commonly used for the treatment of swine wastewater. Although these lagoons were once thought to be relatively simple, their physical, chemical, and biological processes are very complex. This study of anaerobic lagoons had two objectives: (i) to quantify denitrification enzyme activity (DEA) and (ii) to evaluate the influence of lagoon characteristics on the DEA. The DEA ...

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...

One of the main problems in efficiency analysis is to determinate the environmental variables that have an impact on the production process. This paper shows that applying bootstrap to data envelopment analysis (DEA) before performing classification and regression trees (CART) increase the quality of the results. In particular, employing data on the Italian Health System, the paper highlights t...

Model misspecification has significant impacts on Data Envelopment Analysis (DEA) efficiency estimates. This paper discusses the four most widely-used approaches to guide variable specification in DEA. We analyze Efficiency Contribution Measure (ECM), Principal Component Analysis (PCA-DEA), a regression-based test, and bootstrapping for variable selection via Monte Carlo simulations to determin...

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 ...