<efrbr:recordSet xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:efrbr="http://vfrbr.info/efrbr/1.1" xmlns:efrbr-work="http://vfrbr.info/efrbr/1.1/work" xmlns:efrbr-expression="http://vfrbr.info/efrbr/1.1/expression" xmlns:efrbr-manifestation="http://vfrbr.info/efrbr/1.1/manifestation" xmlns:efrbr-person="http://vfrbr.info/efrbr/1.1/person" xmlns:efrbr-corporateBody="http://vfrbr.info/efrbr/1.1/corporateBody" xmlns:efrbr-concept="http://vfrbr.info/efrbr/1.1/concept" xmlns:efrbr-structure="http://vfrbr.info/efrbr/1.1/structure" xmlns:efrbr-responsible="http://vfrbr.info/efrbr/1.1/responsible" xmlns:efrbr-subject="http://vfrbr.info/efrbr/1.1/subject" xmlns:efrbr-other="http://vfrbr.info/efrbr/1.1/other" xsi:schemaLocation="http://vfrbr.info/efrbr/1.1 http://vfrbr.info/schemas/1.1/efrbr.xsd"><efrbr:entities><efrbr-work:work identifier="http://purl.tuc.gr/dl/dias/7F763989-F8DF-4D75-AC15-F3C1D3E30A7C"><efrbr-work:titleOfTheWork>Preference disaggregation for measuring and analysing customer satisfaction: the MUSA method</efrbr-work:titleOfTheWork></efrbr-work:work><efrbr-expression:expression identifier="http://purl.tuc.gr/dl/dias/7F763989-F8DF-4D75-AC15-F3C1D3E30A7C"><efrbr-expression:titleOfTheExpression>Preference disaggregation for measuring and analysing customer satisfaction: the MUSA method</efrbr-expression:titleOfTheExpression><efrbr-expression:formOfExpression vocabulary="DIAS:TYPES">
            Peer-Reviewed Journal Publication
            Δημοσίευση σε Περιοδικό με Κριτές
         </efrbr-expression:formOfExpression><efrbr-expression:dateOfExpression type="issued">2015-11-08</efrbr-expression:dateOfExpression><efrbr-expression:dateOfExpression type="published">2002</efrbr-expression:dateOfExpression><efrbr-expression:languageOfExpression vocabulary="iso639-1">en</efrbr-expression:languageOfExpression><efrbr-expression:summarizationOfContent>The MUlticriteria Satisfaction Analysis (MUSA) method for measuring and analysing customer satisfaction is presented in this paper. The MUSA method is a preference disaggregation model following the principles of ordinal regression analysis (inference procedure). The integrated methodology evaluates the satisfaction level of a set of individuals (customers, employees, etc.) based on their values and expressed preferences. Using satisfaction survey's data, the MUSA method aggregates the different preferences in unique satisfaction functions. This aggregation–disaggregation process is achieved with the minimum possible errors. The main advantage of the MUSA method is that it fully considers the qualitative form of customers' judgements and preferences. The development of a set of quantitative indices and perceptual maps makes possible the provision of an effective support for the satisfaction evaluation problem. This paper also presents the reliability analysis of the provided results, along with a simple numerical example that demonstrates the implementation process of the MUSA method. Finally, several extensions and future research in the context of the presented method are discussed.</efrbr-expression:summarizationOfContent><efrbr-expression:useRestrictionsOnTheExpression type="creative-commons">http://creativecommons.org/licenses/by/4.0/</efrbr-expression:useRestrictionsOnTheExpression><efrbr-expression:note type="journal name">European Journal of Operational Research</efrbr-expression:note><efrbr-expression:note type="journal volume">143</efrbr-expression:note><efrbr-expression:note type="journal number">1</efrbr-expression:note><efrbr-expression:note type="page range">148-170</efrbr-expression:note></efrbr-expression:expression><efrbr-person:person identifier="http://users.isc.tuc.gr/~egrigoroudis"><efrbr-person:nameOfPerson vocabulary="TUC:LDAP">
            Grigoroudis Evangelos
            Γρηγορουδης Ευαγγελος
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            Siskos, Yannis
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            Elsevier
         </efrbr-corporateBody:nameOfTheCorporateBody></efrbr-corporateBody:corporateBody><efrbr-concept:concept identifier="E06E61D4-1524-4B1C-B82F-C723E846F1E9"><efrbr-concept:termForTheConcept>
            Multicriteria analysis
         </efrbr-concept:termForTheConcept></efrbr-concept:concept><efrbr-concept:concept identifier="1C82422A-915E-43B1-ADB4-7A93C4B22E88"><efrbr-concept:termForTheConcept>
            Preference disaggregation
         </efrbr-concept:termForTheConcept></efrbr-concept:concept><efrbr-concept:concept identifier="CDD02AC0-A52E-4A63-A31A-1F253D135716"><efrbr-concept:termForTheConcept>
            Ordinal regression
         </efrbr-concept:termForTheConcept></efrbr-concept:concept><efrbr-concept:concept identifier="B4E0D8BB-3DB8-4C97-A50E-A7B522AA07B3"><efrbr-concept:termForTheConcept>
            Customer satisfaction analysis
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