Model for predicting price change patterns in multi-family houses post renovation work in South Korea
Renovation work on deteriorated multi-family houses (MFHs) is often undertaken to improve their physical performance. However, due to uncertainties in economic benefits from renovation, many MFHs frequently withdraw their renovation plans in South Korea. Despite this problem, there has been very lit...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2020-05-01
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| Series: | Journal of Asian Architecture and Building Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/13467581.2020.1723595 |
| _version_ | 1797755651041001472 |
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| author | Kyuman Cho Jaesung Kim Taehoon Kim Taehoon Hong |
| author_facet | Kyuman Cho Jaesung Kim Taehoon Kim Taehoon Hong |
| author_sort | Kyuman Cho |
| collection | DOAJ |
| description | Renovation work on deteriorated multi-family houses (MFHs) is often undertaken to improve their physical performance. However, due to uncertainties in economic benefits from renovation, many MFHs frequently withdraw their renovation plans in South Korea. Despite this problem, there has been very little research on countering this issue. With this background, this study aims to develop a model for predicting the price change patterns (MPPCP) of deteriorated MFHs upon renovation in South Korea. An artificial neural network (ANN)-based MPPCP was developed to detect the relationship between project attributes and price change patterns due to renovations. By combining the parameters of the ANN method, 108 candidate models were identified and a final MPPCP was proposed after conducting simulation tests to verify the level of correct for the candidate`s models. The results of model application to actual MFH renovation cases show that the developed model can facilitate a project owner’s decision-making by estimating price change patterns for the deteriorated MFH in the project planning stage itself. |
| first_indexed | 2024-03-12T17:50:11Z |
| format | Article |
| id | doaj.art-0d0aa712fda94cfaaf7943fe170a6dce |
| institution | Directory Open Access Journal |
| issn | 1347-2852 |
| language | English |
| last_indexed | 2024-03-12T17:50:11Z |
| publishDate | 2020-05-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Asian Architecture and Building Engineering |
| spelling | doaj.art-0d0aa712fda94cfaaf7943fe170a6dce2023-08-03T09:07:49ZengTaylor & Francis GroupJournal of Asian Architecture and Building Engineering1347-28522020-05-0119323024110.1080/13467581.2020.17235951723595Model for predicting price change patterns in multi-family houses post renovation work in South KoreaKyuman Cho0Jaesung Kim1Taehoon Kim2Taehoon Hong3Chosun UniversityChosun UniversityChosun UniversityYonsei UniversityRenovation work on deteriorated multi-family houses (MFHs) is often undertaken to improve their physical performance. However, due to uncertainties in economic benefits from renovation, many MFHs frequently withdraw their renovation plans in South Korea. Despite this problem, there has been very little research on countering this issue. With this background, this study aims to develop a model for predicting the price change patterns (MPPCP) of deteriorated MFHs upon renovation in South Korea. An artificial neural network (ANN)-based MPPCP was developed to detect the relationship between project attributes and price change patterns due to renovations. By combining the parameters of the ANN method, 108 candidate models were identified and a final MPPCP was proposed after conducting simulation tests to verify the level of correct for the candidate`s models. The results of model application to actual MFH renovation cases show that the developed model can facilitate a project owner’s decision-making by estimating price change patterns for the deteriorated MFH in the project planning stage itself.http://dx.doi.org/10.1080/13467581.2020.1723595renovation workmulti-family houseartificial neural networkeconomic benefit due to renovation |
| spellingShingle | Kyuman Cho Jaesung Kim Taehoon Kim Taehoon Hong Model for predicting price change patterns in multi-family houses post renovation work in South Korea Journal of Asian Architecture and Building Engineering renovation work multi-family house artificial neural network economic benefit due to renovation |
| title | Model for predicting price change patterns in multi-family houses post renovation work in South Korea |
| title_full | Model for predicting price change patterns in multi-family houses post renovation work in South Korea |
| title_fullStr | Model for predicting price change patterns in multi-family houses post renovation work in South Korea |
| title_full_unstemmed | Model for predicting price change patterns in multi-family houses post renovation work in South Korea |
| title_short | Model for predicting price change patterns in multi-family houses post renovation work in South Korea |
| title_sort | model for predicting price change patterns in multi family houses post renovation work in south korea |
| topic | renovation work multi-family house artificial neural network economic benefit due to renovation |
| url | http://dx.doi.org/10.1080/13467581.2020.1723595 |
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