잠재계층분석기법(Latent Class Analysis)을 활용한 영화 소비자 세분화에 관한 연구
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 구교령 | - |
dc.contributor.author | 이장혁 | - |
dc.date.accessioned | 2021-09-07T17:29:29Z | - |
dc.date.available | 2021-09-07T17:29:29Z | - |
dc.date.created | 2021-06-17 | - |
dc.date.issued | 2011 | - |
dc.identifier.issn | 1225-1119 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/113666 | - |
dc.description.abstract | As movie demands become more and more diversified, it is necessary for movie related firms to segment a whole heterogeneous market into a number of small homogeneous markets in order to identify the specific needs of consumer groups. Relevant market segmentation helps them to develop valuable offer to target segments through effective marketing planning. In this article, we introduce various segmentation methods and compare their advantages and disadvantages. In particular, we analyze “2009~2010 consumer survey data of Korean Film Industry” by using Latent Class Analysis(LCA), a statistical segmentation method which identifies exclusive set of latent classes based on consumers’ responses to an observed categorical and numerical variables. It is applied PROC LCA, a new SAS procedure for conducting LCA and finally get the result of 11 distinctive clusters showing unique characteristics on their buying behaviors. | - |
dc.language | Korean | - |
dc.language.iso | ko | - |
dc.publisher | 한국경영과학회 | - |
dc.title | 잠재계층분석기법(Latent Class Analysis)을 활용한 영화 소비자 세분화에 관한 연구 | - |
dc.title.alternative | Segmentation of Movie Consumption:An Application of Latent Class Analysis to Korean Film Industry | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | 이장혁 | - |
dc.identifier.bibliographicCitation | 한국경영과학회지, v.36, no.4, pp.161 - 184 | - |
dc.relation.isPartOf | 한국경영과학회지 | - |
dc.citation.title | 한국경영과학회지 | - |
dc.citation.volume | 36 | - |
dc.citation.number | 4 | - |
dc.citation.startPage | 161 | - |
dc.citation.endPage | 184 | - |
dc.type.rims | ART | - |
dc.identifier.kciid | ART001613709 | - |
dc.description.journalClass | 2 | - |
dc.description.journalRegisteredClass | kci | - |
dc.subject.keywordAuthor | Segmentation | - |
dc.subject.keywordAuthor | Clustering Analysis | - |
dc.subject.keywordAuthor | Mixture Model | - |
dc.subject.keywordAuthor | Korean Movie Industry | - |
dc.subject.keywordAuthor | Latent Class Analysis | - |
dc.subject.keywordAuthor | K-Means | - |
dc.subject.keywordAuthor | SOM | - |
dc.subject.keywordAuthor | Segmentation | - |
dc.subject.keywordAuthor | Clustering Analysis | - |
dc.subject.keywordAuthor | Mixture Model | - |
dc.subject.keywordAuthor | Korean Movie Industry | - |
dc.subject.keywordAuthor | Latent Class Analysis | - |
dc.subject.keywordAuthor | K-Means | - |
dc.subject.keywordAuthor | SOM | - |
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