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Impacts of public medical insurance reforms on households: An application of fuzzy cognitive map for scenario evaluation

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dc.contributor.authorYun, Yeonggyu-
dc.contributor.authorJung, Hye-Young-
dc.date.accessioned2023-08-16T07:36:08Z-
dc.date.available2023-08-16T07:36:08Z-
dc.date.issued2021-06-
dc.identifier.issn1432-7643-
dc.identifier.issn1433-7479-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/113925-
dc.description.abstractWe examine the effects of policy reforms on public medical insurance on households. We employ fuzzy cognitive map (FCM) since it allows for a parsimonious structure and still yields reliable simulation results. We adopt a hybrid approach to construct FCM and separately design maps for low-income households and general households. We further examine three scenarios in which government subsidies on public medical insurance, insurance coverage rates, and registration rates increase respectively. Our simulation based on the constructed FCM shows that government subsidy increases have the largest impacts on households. We demonstrate both flexibility and extensibility of FCM by assessing different scenarios. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.-
dc.format.extent10-
dc.language영어-
dc.language.isoENG-
dc.publisherSpringer Verlag-
dc.titleImpacts of public medical insurance reforms on households: An application of fuzzy cognitive map for scenario evaluation-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1007/s00500-021-05617-4-
dc.identifier.scopusid2-s2.0-85100678859-
dc.identifier.wosid000616036800001-
dc.identifier.bibliographicCitationSoft Computing, v.25, no.12, pp 7947 - 7956-
dc.citation.titleSoft Computing-
dc.citation.volume25-
dc.citation.number12-
dc.citation.startPage7947-
dc.citation.endPage7956-
dc.type.docType정기학술지(Article(Perspective Article포함))-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.subject.keywordAuthorFuzzy cognitive map-
dc.subject.keywordAuthorMedical service satisfaction-
dc.subject.keywordAuthorNonlinear Hebbian learning-
dc.subject.keywordAuthorPublic medical insurance-
dc.identifier.urlhttps://link.springer.com/article/10.1007/s00500-021-05617-4-
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ERICA 과학기술융합대학 (ERICA 수리데이터사이언스학과)
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