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DATA ENVELOPMENT ANALYSIS and Confident-DEA. Edition No. 1
VDM Publishing House, March 2009, Pages: 180
This work contributes to the Data
Envelopment Analysis (DEA) literature at three ways.
First, it extends the roots of DEA by providing an
analytical approach deriving the basic Charnes-
Cooper-Rhodes (1978) model from the Weak Axiom of
Profit Maximization (WAPM) of Firm Theory.
Second, this work provides a systematic way for
classifying the existing DEA literature by offering
a taxonomy. Finally, a theoretical contribution to
the literature, Confident-DEA approach, is proposed
involving a bilevel convex optimization model to
which a Genetic-Algorithm-based solution method is
suggested. Complementing previous DEA methodologies,
which provides single valued efficiency measures,
Confident-DEA provides a range of values for the
efficiency measures, an efficiency confidence
interval and hence the name, reflecting the
imprecision in data. Monte-Carlo simulation is used
to determine the distribution of the efficiency
measures, taking into account the distribution of
the bounded imprecise data over their corresponding
intervals. Confident-DEA is applied to predict the
efficiency of banking systems in OECD countries.
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