The effect of correlation coefficient among multiple input vectors on the efficiency mean in data envelopment analysis

R. Farzipoor Sean*, A. Memariani, F. Hosseinzadeh Lotfi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Citations (SciVal)


In some of the papers on data envelopment analysis (DEA), there have been explained that if correlation coefficient between each pair of input (output) vectors is strong and positive, one of the input (output) vector could be omitted. The objective of this paper is to determine correlation coefficient threshold that beyond which omission of one or more input vectors have no statistically significant effect on the efficiency mean. The threshold identification in terms of some of the DEA models including CCR, CCRCSW, BCC and BCCCSW are performed. To analyze the data, analysis of variance (ANOVA) is used.

Original languageEnglish
Pages (from-to)503-521
Number of pages19
JournalApplied Mathematics and Computation
Issue number2
Publication statusPublished - Mar 15 2005


  • Analysis of variance
  • Correlation coefficient
  • Data envelopment analysis

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics

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