This paper develops a new radial super-efficiency data envelopment analysis (DEA) model, which allows input-output variables to take both negative and positive values. Compared with existing DEA models capable of dealing with negative data, the proposed model can rank the efficient DMUs and is feasible no matter whether the input-output data are nonnegative or not. It successfully addresses the...

in the commercial banking activities, efficiency is an important issue for the bank managers, monitoring part and clients. this study has appraised the efficiency performance of the commercial banks in iran. the research method has been using windows data envelopment analysis with constant and variable returns to scale and input oriented model at the period of 1991-2006. the sample of study was...

evaluate the performance of companies on the stock exchange using non-parametric methods is very important. dea and dea-r with the strategies for piecewise linear frontier production function and use of available data, assess the stock company. in this study, using a neural network algorithm dea and dea-r is suggested to classify the first companies in the stock exchange; secondly, using the co...

Malmquist Productivity Index (MPI) is a numeric index that is of great importance in measuring productivity and its changes. In recent years, tools like DEA have been utilized for determining MPI. In the present paper, some models are recommended for calculating MPI when there are just ratio data available. Then, using DEA and DEA-R, some models are proposed under the constant returns to scale ...

capital asset pricing model (capm) has been among the common models to estimate expected returns rate. since the linearity assumption is considered in the standard version of the capital asset pricing model, estimating beta in nonlinear setting will be inconsistent and bias-oriented. therefore, this study tries to evaluate predictive power of nonlinear capital asset pricing model as well as sta...

We present efficiency models to evaluate data warehouse operations and analyze a preliminary data set using one of the models. The macro model represents the efficiency of operating a collection of data warehouses for both refresh processing and query production over a monthly horizon. The micro models represent the efficiency of daily operations an individual data warehouse for either refresh ...

Data envelopment analysis (DEA) provides an optimization methodology for deriving an efficiency score for each member of a set of peer decision-making units. Under the original DEA model it was assumed that there is constant returns to scale (CRS). This idea was later extended to the more general case that allowed for variable returns to scale (VRS). In both of these structures, it is assumed t...