Documents disponibles écrits par cet auteur

A portfolio model for performance assessment: the Financial Times MBA ranking / Jessop, A. in Journal of the operational research society (JORS), Vol. 61 N° 4 (Avril 2010) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 61 N° 4 (Avril 2010) . - pp. 632–639 Titre : A portfolio model for performance assessment: the Financial Times MBA ranking Type de document : texte imprimé Auteurs : Jessop, A., Auteur Année de publication : 2010 Article en page(s) : pp. 632–639 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Multicriteria  Quadratic  programming  Performance  MBA Index. décimale : 001.424 Résumé : The ranking of MBA programmes by newspapers and magazines is common and usually controversial. This paper discusses the use of the most popular method of making these rankings via a multicriteria model which uses the weighted sum of a number of performance measures to give an overall score on which selection or ranking may be based. The weights are a quantitative model of the preferences of those making the evaluation. Many methods are available to obtain weights from preference statements so that for any set of preferences a number of different weight sets can be found depending on the method used. Cognitive limits lead to inconsistency in preference judgements so that weights may be subject both to uncertainty and to bias. It is proposed that choosing weights to minimize discrimination between alternatives (not weights) guards against unjustified discrimination between alternatives. Applying the method to data collected by the Financial Times shows the effect of varying the level of discrimination between weights and also the effect of using a reduced data set made necessary by the partial publication of information. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v61/n4/abs/jors2008193a.html [article] A portfolio model for performance assessment: the Financial Times MBA ranking [texte imprimé] / Jessop, A., Auteur . - 2010 . - pp. 632–639. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 61 N° 4 (Avril 2010) . - pp. 632–639 Mots-clés : Multicriteria  Quadratic  programming  Performance  MBA Index. décimale : 001.424 Résumé : The ranking of MBA programmes by newspapers and magazines is common and usually controversial. This paper discusses the use of the most popular method of making these rankings via a multicriteria model which uses the weighted sum of a number of performance measures to give an overall score on which selection or ranking may be based. The weights are a quantitative model of the preferences of those making the evaluation. Many methods are available to obtain weights from preference statements so that for any set of preferences a number of different weight sets can be found depending on the method used. Cognitive limits lead to inconsistency in preference judgements so that weights may be subject both to uncertainty and to bias. It is proposed that choosing weights to minimize discrimination between alternatives (not weights) guards against unjustified discrimination between alternatives. Applying the method to data collected by the Financial Times shows the effect of varying the level of discrimination between weights and also the effect of using a reduced data set made necessary by the partial publication of information. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v61/n4/abs/jors2008193a.html

Using imprecise estimates for weights / Jessop, A. in Journal of the operational research society (JORS), Vol. 62 N° 6 (Juin 2011) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 62 N° 6 (Juin 2011) . - pp. 1048–1055 Titre : Using imprecise estimates for weights Type de document : texte imprimé Auteurs : Jessop, A., Auteur Année de publication : 2011 Article en page(s) : pp. 1048–1055 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Multi-criteria  Weights  Probability  Dirichlet Index. décimale : 001.424 Résumé : In multi-attribute decision problems the decision to differentiate between alternatives will be affected by the precision with which weights are specified. Specifications are imprecise because of the uncertainty characteristic of the judgements on which weights are based. Uncertainties are from two sources, the accuracy with which judgements are articulated and the inconsistency when multiple judgements are made and must be reconciled. These uncertainties are modelled using probabilistic weight estimates integrated by the Dirichlet distribution. This ensures the consistency of the estimates and leads to the calculation of significance of the differences between alternatives. A simple plot of these significant differences helps in the final decision whether this is selection or ranking. The method is used to find weight estimates in the presence of both types of uncertainty acting separately and together. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n6/abs/jors201046a.html [article] Using imprecise estimates for weights [texte imprimé] / Jessop, A., Auteur . - 2011 . - pp. 1048–1055. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 62 N° 6 (Juin 2011) . - pp. 1048–1055 Mots-clés : Multi-criteria  Weights  Probability  Dirichlet Index. décimale : 001.424 Résumé : In multi-attribute decision problems the decision to differentiate between alternatives will be affected by the precision with which weights are specified. Specifications are imprecise because of the uncertainty characteristic of the judgements on which weights are based. Uncertainties are from two sources, the accuracy with which judgements are articulated and the inconsistency when multiple judgements are made and must be reconciled. These uncertainties are modelled using probabilistic weight estimates integrated by the Dirichlet distribution. This ensures the consistency of the estimates and leads to the calculation of significance of the differences between alternatives. A simple plot of these significant differences helps in the final decision whether this is selection or ranking. The method is used to find weight estimates in the presence of both types of uncertainty acting separately and together. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n6/abs/jors201046a.html