Scaling units via the canonical correlation analysis in the DEA context

Research output: Contribution to journalArticlepeer-review

166 Scopus citations


This paper deals with the evaluation of decision making units which have multiple inputs and outputs. A new method (CCA/DEA) is developed where the Canonical Correlation Analysis (CCA) is utilized to provide a full rank scaling for all the units rather than a categorical classification (for efficient and inefficient units) as done by the Data Envelopment Analysis (DEA). The CCA/DEA approach is an attempt to bridge the gap between the frontier approach of DEA and the average tendencies of statistics (econometrics). Nonparametric statistical tests are employed to validate the consistency between the classification from the DEA and the postclassification that was generated by the CCA/DEA.

Original languageEnglish
Pages (from-to)629-637
Number of pages9
JournalEuropean Journal of Operational Research
Issue number3
StatePublished - 1 Aug 1997


  • Canonical correlation analysis
  • Data envelopment analysis
  • Rank scaling

ASJC Scopus subject areas

  • Computer Science (all)
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management


Dive into the research topics of 'Scaling units via the canonical correlation analysis in the DEA context'. Together they form a unique fingerprint.

Cite this