Title: Integration of directional distance formulation of DEA and canonical correlation

Authors: Udaya Shetty; T.P.M. Pakkala

Addresses: Bangalore Urban District, Government of Karnataka, Bangalore – 560 073, India ' Department of PG Studies and Research in Statistics, Mangalore University, Mangalagangotri – 574 199, Mangalore, India

Abstract: Data envelopment analysis (DEA) which has been widely used in recent times for measuring productive efficiency of decision making units (DMUs). The main limitation of DEA is that many numbers of DMUs comes out to be efficient when there are relatively large number of input and output variables as compared to number of DMUs under evaluation. In extreme cases may cause the majority of the units to be efficient. Tackle this limitation canonical correlation analysis (CCA) is applied in this paper. This paper develops a method that integrates the directional distance formulation of DEA and CCA to measure the efficiency and rank the DMUs. There are situations in which more than one significant canonical correlation exists with both positive and negative values. This problem is addressed in this paper by using directional distance function approach to measure the efficiency, where negative canonical correlation exists. This method can also be applied where two or more canonical correlations are significant.

Keywords: data envelopment analysis; DEA; canonical correlation; directional distance function; DMU efficiency; decision making units; DMUs.

DOI: 10.1504/IJBPSCM.2016.076003

International Journal of Business Performance and Supply Chain Modelling, 2016 Vol.8 No.1, pp.66 - 77

Accepted: 27 Jul 2012
Published online: 21 Apr 2016 *

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