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Sensitivity and stability of efficiency classifications in Data Envelopment Analysis

โœ Scribed by Abraham Charnes; John J. Rousseau; John H. Semple


Publisher
Springer
Year
1996
Tongue
English
Weight
788 KB
Volume
7
Category
Article
ISSN
0895-562X

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โœฆ Synopsis


A new technique for assessing the sensitivity and stability of efficiency classifications in Data Envelopment Analysis (DEA) is presented. Here developed for the ratio (CCR) model, this technique extends easily to other DEA variants. An organization's input-outut vector serves as the center for a cell within which the organization's classification remains unchanged under perturbations of the data. For the ll, l~. and generalized l~. norms, the radius of the maximal cell can be computed using linear programming formulations. This radius can be interpreted as a measure of the classifications stability, especially with respect to errors in the data.


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