Utilizing recent developments in data envelopment analysis (DEA), this paper examines the performance of the top 55 U.S. commercial banks via a two-stage production process that separates profitability and marketability. Substantial performance inefficiency is uncovered in both dimensions. Relatively large banks exhibit better performance on profitability, whereas smaller banks tend to perform ...

MCDA in general and multiple objective linear programming (MOLP) in particular can be used for planning future performances. The model structures of DEA and MOLP have much in common and research on integrating DEA and MOLP has attracted increasing attentions to support both past performance assessment and future target setting in integrated manners (Cooper, 2004). For instance, Golany (1988) de...

Data envelopment analysis (DEA) is a widely used mathematical programming approach for comparing the input and output of a set of comparable decision-making units (DMUs) by evaluating their relative efficiency. The traditional DEA methods require accurate measurement of both the inputs and outputs. However, the real evaluation of the DMUs is often characterized by imprecision and uncertainty in...

data envelopment analysis (dea) is a widely recognized approach for evaluating the efficiencies of decision making units (dmus). because of easy and successful application and case studies, dea has gained much attention and widespread use by business and academy researchers. the conventional dea models (e.g. bcc and ccr) make an assumption that input and output data are exact values on a ratio ...

The purpose of conventional Data Envelopment Analysis (DEA) is to evaluate the performance of a set of firms or Decision-Making Units using deterministic input and output data. However, the input and output data in the real-life performance evaluation problems are often stochastic. The stochastic input and output data in DEA can be represented with random variables. Several methods have been pr...

The previously-published physiologically based pharmacokinetic model for atrazine (ATZ), deisopropylatrazine (DIA), deethylatrazine (DEA), and diaminochlorotriazine (DACT), which collectively comprise the total chlorotriazines (TCT) as represented in this study, was modified to allow for scaling to humans. Changes included replacing the fixed dose-dependent oral uptake rates with a method that ...

Data Envelopment Analysis (DEA) is a linear programming methodology for measuring the efficiency of Decision Making Units (DMUs) to improve organizational performance in private and public sectors. However, if new DMU needs be known its score, DEA analysis would have re-conducted, especially nowadays, datasets from many fields been growing rapidly real world, which will need huge amount computa...

Data Envelopment Analysis (DEA) is a great approach used for measuring relative efficiencies and performance of a collection of Decision Making Units (DMUs). These used in the various forms, such as hospitals, universities, air force, banks, courts, business firms, and others, including the performance of countries, regions, etc. One of the earliest applications of DEA called Education. It was ...

the ahp/dea methodology is an integration of analytical hierarchical process (ahp) and data envelopment analysis. this method uses the capabilities of both ahp and dea. however, it has some problems: it illogically compares two decision-making units in a data envelopment analysis (dea) model, it is not compatible with dea ranking in the case of multiple inputs/multiple outputs, and it leads to ...