SCALING UNITS VIA THE CANONICAL CORRELATION-ANALYSIS IN THE DEA CONTEXT

This paper deals with the evaluation of decision making units which ha ve multiple inputs and outputs. A new method (CCA/DEA) is developed wh ere the Canonical Correlation Analysis (CCA) is utilized to provide a full rank scaling for all the units rather than a categorical classifi cation (for efficient and inefficient units) as done by the Data Envel opment Analysis (DEA). The CCA/DEA approach is an attempt to bridge th e gap between the frontier approach of DEA and the average tendencies of statistics (econometrics). Nonparametric statistical tests are empl oyed to validate the consistency between the classification from the D EA and the postclassification that was generated by the CCA/DEA. (C) 1 997 Elsevier Science B.V.