{"title":"Joint Use of Factor Analysis (FA) and Data Envelopment Analysis (DEA) for Ranking of Data Envelopment Analysis","authors":"Reza Nadimi, Fariborz Jolai","volume":13,"journal":"International Journal of Computer and Information Engineering","pagesStart":155,"pagesEnd":160,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/13961","abstract":"This article combines two techniques: data\r\nenvelopment analysis (DEA) and Factor analysis (FA) to data\r\nreduction in decision making units (DMU). Data envelopment\r\nanalysis (DEA), a popular linear programming technique is useful to\r\nrate comparatively operational efficiency of decision making units\r\n(DMU) based on their deterministic (not necessarily stochastic)\r\ninput\u2013output data and factor analysis techniques, have been proposed\r\nas data reduction and classification technique, which can be applied\r\nin data envelopment analysis (DEA) technique for reduction input \u2013\r\noutput data. Numerical results reveal that the new approach shows a\r\ngood consistency in ranking with DEA.","references":"[1] A. Charnes, W.W. Cooper, E. Rhodes, \"Measuring the efficiency of\r\ndecision making units\", European Journal of Operations Research 2\r\n(1978) 429 -444.\r\n[2] L. Easton, D.J. Murphy, J.N. Pearson, \"Purchasing performance\r\nevaluation: with data envelopment analysis\", European Journal of\r\nPurchasing & Supply Management 8 (2002) 123-134.\r\n[3] N. Adler, B. Golany, \"Evaluation of deregulated airline networks using\r\ndata envelopment analysis combined with principal component analysis\r\nwith an application to Western Europe\", European Journal of\r\nOperations Research 132, (2001) 260-273.\r\n[4] N. Adler, J. Berechman, \"Measuring airport quality from the airlines-\r\nviewpoint: an application of data envelopment analysis\", Transport\r\nPolicy 8 (2001) 171-181.\r\n[5] R.D.Banker, A.Charnes,W.W.Cooper, \"Some models for estimating\r\ntechnical and scale inefficiencies in data envelopment analysis\",\r\nManagement Science 30(9)(1984)1079-1092\r\n[6] How to perform and interpret Factor analysis using SPSS,\r\nwww.ncl.ac.Uk\/iss\/statistics\/docs\/Factoranalysis.html, 2002.\r\n[7] J.Zhu, \"Data envelopment analysis vs principal component analysis : An\r\nillustrative study of economic performance of Chinese cities\", European\r\nJournal of Operation Research 111,(1998) 50-61.\r\n[8] M.K. Epstein, J.C. Henderson, \"Data envelopment analysis for\r\nmanagerial control and diagnosis\", Decision Science 20, (1989) 90-119.\r\n[9] B.S. Everitt & G. Dunn, \"Applied Multivariate Data Analysis\", Edward\r\nArnold, London, pp304 (1991).\r\n[10] T. Hastie, R. Tibshirani, \"Discriminant analysis by Gaussian mixtures\",\r\nJ. Roy. Statist. Soc, B 58 (1996) 155-176.\r\n[11] J.D. Banfield, A.E. Raftery, \"Model-based Gaussian and non-Gaussian\r\nclustering\", Biometrics, 49 (1993) 803-821.\r\n[12] J.D. Banfield, A.E. Raftery, \"Model-based clustering, discriminant\r\nanalysis, and density estimation\", J. Amer. Statist. Assoc, 97 (2002)\r\n611-631.\r\n[13] D.G. Cal\u251c\u2593, \"Gaussian mixture model classification: a projection pursuit\r\napproach\", Comput. Statist. Data Anal., 52 (2007) 471-482.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 13, 2008"}