Intelligent quality planning for quality deployment based on the balanced score card: Application to the mobile communication industry

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dc.contributor.authorYun, U.T.ko
dc.contributor.authorPark, Sang Chanko
dc.date.accessioned2013-03-03T18:25:26Z-
dc.date.available2013-03-03T18:25:26Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2003-03-
dc.identifier.citationINTERNATIONAL JOURNAL OF MANUFACTURING TECHNOLOGY AND MANAGEMENT, v.5, no.1-2, pp.52 - 61-
dc.identifier.issn1368-2148-
dc.identifier.urihttp://hdl.handle.net/10203/79890-
dc.description.abstractIn this paper, we suggest an intelligent quality measures method for the quality deployment based on BSC (Balanced Score Card). More specifically, we unfold them by selecting critical elements from Service Survey data in the mobile communication industry using Factor Analysis and Partial Correlation. Then we find potential customers who fit into the demographic is features of the target customer group identified as a result of applying machine learning modules such as Self Organising Map and Classifiers to the above-mentioned data. Finally we perform loyalty analysis that distinguishes the loyalty group from the potentially profitable one by using the same machine learning modules. The first step relates to the internal perspective of BSC, the second step relates to BSC's customer perspective and the third step relates to the financial perspective of BSC.-
dc.languageEnglish-
dc.publisherInderscience Publishers-
dc.titleIntelligent quality planning for quality deployment based on the balanced score card: Application to the mobile communication industry-
dc.typeArticle-
dc.identifier.scopusid2-s2.0-1342306068-
dc.type.rimsART-
dc.citation.volume5-
dc.citation.issue1-2-
dc.citation.beginningpage52-
dc.citation.endingpage61-
dc.citation.publicationnameINTERNATIONAL JOURNAL OF MANUFACTURING TECHNOLOGY AND MANAGEMENT-
dc.contributor.nonIdAuthorYun, U.T.-
dc.subject.keywordAuthorBalanced score card-
dc.subject.keywordAuthorLoyalty analysis-
dc.subject.keywordAuthorMachine learning-
dc.subject.keywordAuthorMobile communication industry-
dc.subject.keywordAuthorService survey-
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