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In the determination of weight sets to compute cross-efficiency ratios in DEA / K. F. Lam in Journal of the operational research society (JORS), Vol. 61 N° 1 (Issue spécial) (Janvier 2010) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 61 N° 1 (Issue spécial) (Janvier 2010) . - pp. 134–143 Titre : In the determination of weight sets to compute cross-efficiency ratios in DEA Type de document : texte imprimé Auteurs : K. F. Lam, Auteur Année de publication : 2011 Article en page(s) : pp. 134–143 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Data  envelopment  analysis  Discriminant  analysis  Linear  programming  Mixed-integer  linear  programming  Performance  measurement Résumé : Data envelopment analysis (DEA) measures the production performance of decision-making units (DMUs) which consume multiple inputs and produce multiple outputs. Although DEA has become a very popular method of performance measure, it still suffers from some shortcomings. For instance, one of its drawbacks is that multiple solutions exist in the linear programming solutions of efficient DMUs. The obtained weight set is just one of the many optimal weight sets that are available. Then why use this weight set instead of the others especially when this weight set is used for cross-evaluation? Another weakness of DEA is that extremely diverse or unusual values of some input or output weights might be obtained for DMUs under assessment. Zero input and output weights are not uncommon in DEA. The main objective of this paper is to develop a new methodology which applies discriminant analysis, super-efficiency DEA model and mixed-integer linear programming to choose suitable weight sets to be used in computing cross-evaluation. An advantage of this new method is that each obtained weight set can reflect the relative strengths of the efficient DMU under consideration. Moreover, the method also attempts to preserve the original classificatory result of DEA, and in addition this method produces much less zero weights than DEA in our computational results. DEWEY : 001.424 ISSN : 0160 En ligne : http://www.palgrave-journals.com/jors/journal/v61/n1/abs/jors2008138a.html [article] In the determination of weight sets to compute cross-efficiency ratios in DEA [texte imprimé] / K. F. Lam, Auteur . - 2011 . - pp. 134–143. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 61 N° 1 (Issue spécial) (Janvier 2010) . - pp. 134–143 Mots-clés : Data  envelopment  analysis  Discriminant  analysis  Linear  programming  Mixed-integer  linear  programming  Performance  measurement Résumé : Data envelopment analysis (DEA) measures the production performance of decision-making units (DMUs) which consume multiple inputs and produce multiple outputs. Although DEA has become a very popular method of performance measure, it still suffers from some shortcomings. For instance, one of its drawbacks is that multiple solutions exist in the linear programming solutions of efficient DMUs. The obtained weight set is just one of the many optimal weight sets that are available. Then why use this weight set instead of the others especially when this weight set is used for cross-evaluation? Another weakness of DEA is that extremely diverse or unusual values of some input or output weights might be obtained for DMUs under assessment. Zero input and output weights are not uncommon in DEA. The main objective of this paper is to develop a new methodology which applies discriminant analysis, super-efficiency DEA model and mixed-integer linear programming to choose suitable weight sets to be used in computing cross-evaluation. An advantage of this new method is that each obtained weight set can reflect the relative strengths of the efficient DMU under consideration. Moreover, the method also attempts to preserve the original classificatory result of DEA, and in addition this method produces much less zero weights than DEA in our computational results. DEWEY : 001.424 ISSN : 0160 En ligne : http://www.palgrave-journals.com/jors/journal/v61/n1/abs/jors2008138a.html