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Author: | Cooper, W. W. Park, K. S. Yu, G. |
Title: | IDEA and AR-IDEA: Models for dealing with imprecise data in DEA. |
Journal: | Management Science
1999 : APR, VOL. 45:4, p. 597-607 |
Index terms: | Economic efficiency Effectiveness Decision making |
Language: | eng |
Abstract: | This paper addresses the problem of imprecise data in Data Envelopment Analysis (DEA). "Imprecise data" means that some data are known only to the extent that the true values lie within prescribed bounds while other data are known only to satisfy certain ordinal relations. DEA is a nonparametric approach to evaluating the relative efficiency of decision making units(DMUs) that use multiple inputs. The Imprecise Data Envelopment Analysis (IDEA) method developed in this paper permits mixtures of imprecisely- and exactly-known data, which the Idea models transform into ordinary linear programming forms. |
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