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Adler, N. and Golany, B. (2002) Including Principal Component Weights to Improve Discrimination in Data Envelopment Analysis. Journal of the Operational Research Society, 53, 985-991.
https://doi.org/10.1057/palgrave.jors.2601400

has been cited by the following article:

• TITLE: The Use of Yanai’s Generalized Coefficient of Determination to Reduce the Number of Variables in DEA Models

  AUTHORS: Mauricio Benegas

  KEYWORDS: DEA, Yanai’s Generalized Coefficient of Determination, Pseudo-Rank, Dimension Reduction, Improving Discrimination

  JOURNAL NAME: American Journal of Operations Research, Vol.7 No.3, May 18, 2017

  ABSTRACT: This paper proposes a new method to reduce the dimensionality of input and output spaces in DEA models. The method is based on Yanai’s Generalized Coefficient of Determination and on the concept of pseudo-rank of a matrix. In addition, the paper suggests a rule to determine the cardinality of the subset of selected variables in a way to gain the maximal discretionary power and to suffer a minimal informational loss.