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An Analysis of the Price Determinants of Multiplex Houses through Spatial Regression Analysis

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dc.contributor.authorKim, Jae-Jong-
dc.contributor.authorCho, Mi-Jeong-
dc.contributor.authorLee, Myeong-Hun-
dc.date.accessioned2024-12-20T06:38:31Z-
dc.date.available2024-12-20T06:38:31Z-
dc.date.issued2022-06-
dc.identifier.issn2071-1050-
dc.identifier.issn2071-1050-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/203117-
dc.description.abstractThis study established a model for price determinants with the combination of the GIS technique and spatial regression model based on the parcel prices of multiplex houses in an effort to integrate and utilize spatial data and choose a suitable model. This study established a spatial weights matrix to apply interrelation with adjacent areas and performed row standardization to specify the effect of adjacent areas. Moran's I was used for measuring the spatial autocorrelation of the parcel prices of multiplex houses. Through this, the parcel price of multiplex houses was analyzed to have a strong spatial autocorrelation and be related to the jeonse price of an apartment. A lot of multiplex houses are supplied to Seoul. In previous studies, multiplex houses studies were analyzed through simple regression analysis excluding spatial effects, however, in this study, a suitable model was derived through spatial regression analysis. Moreover, the jeonse price of an apartment, which is a representative housing type, was firstly analyzed as a variable added and found whether the jeonse price of apartments would have an effect on the other housing types in the neighborhood. This study also found if the jeonse price of apartments would have an effect on the other housing types in the neighborhood. For creating a sustainable residential environment when redeveloping an aging residential area, there is a need to find various ways for coexistence by identifying the interrelation with the neighboring residential areas rather than simply focusing on the supply amount. In addition to this, it suggests that policies addressing the rise of housing prices should not be limited to a specific area or a specific dwelling and should not overlook the spatial interaction relationship.-
dc.format.extent14-
dc.language영어-
dc.language.isoENG-
dc.publisherMDPI-
dc.titleAn Analysis of the Price Determinants of Multiplex Houses through Spatial Regression Analysis-
dc.typeArticle-
dc.publisher.location스위스-
dc.identifier.doi10.3390/su14127116-
dc.identifier.scopusid2-s2.0-85132155634-
dc.identifier.wosid000816836600001-
dc.identifier.bibliographicCitationSUSTAINABILITY, v.14, no.12, pp 1 - 14-
dc.citation.titleSUSTAINABILITY-
dc.citation.volume14-
dc.citation.number12-
dc.citation.startPage1-
dc.citation.endPage14-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaScience & Technology - Other Topics-
dc.relation.journalResearchAreaEnvironmental Sciences & Ecology-
dc.relation.journalWebOfScienceCategoryGreen & Sustainable Science & Technology-
dc.relation.journalWebOfScienceCategoryEnvironmental Sciences-
dc.relation.journalWebOfScienceCategoryEnvironmental Studies-
dc.subject.keywordPlusSeoul [South Korea]-
dc.subject.keywordPlusSouth Korea-
dc.subject.keywordPlusautocorrelation-
dc.subject.keywordPlusGIS-
dc.subject.keywordPlushousing market-
dc.subject.keywordPlusprice dynamics-
dc.subject.keywordPlusregression analysis-
dc.subject.keywordPlusspatial analysis-
dc.subject.keywordPlusspatial data-
dc.subject.keywordPlusstandardization-
dc.subject.keywordAuthormultiplex houses-
dc.subject.keywordAuthorjeonse-
dc.subject.keywordAuthorMoran's I-
dc.subject.keywordAuthorspatial regression model-
dc.identifier.urlhttps://www.mdpi.com/2071-1050/14/12/7116-
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LEE, Myeong Hun
GRADUATE SCHOOL OF URBAN STUDIES (DEPARTMENT OF URBAN AND REGIONAL DEVELOPMENT)
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