In a relatively short period of time, data envelopment analysis
(DEA) has grown into a powerful analytical tool for measuring and
evaluating performance. DEA is computational at its core and this
book is one of several Springer aim to publish on the subject. This
work deals with the micro aspects of handling and modeling data
issues in DEA problems. It is a handbook treatment dealing with
specific data problems, including imprecise data and undesirable
outputs.
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