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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.
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.