Modelling the value of location in the prediction of residential property value
The important of location to effect property value is widely acknowledged. However, traditional approaches in quantifying location influence on property value modelling are unsatisfactory. Value Residual Surface (VRS) has been suggested as an alternative to resolving the difficulty in the traditiona...
| Main Authors: | , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2005
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/1163/ http://eprints.utm.my/1163/1/A_Hamid_Chin.pdf |
| _version_ | 1848890073416728576 |
|---|---|
| author | Mar Iman, Abdul Hamid Chin, Chui Vui |
| author_facet | Mar Iman, Abdul Hamid Chin, Chui Vui |
| author_sort | Mar Iman, Abdul Hamid |
| building | UTeM Institutional Repository |
| collection | Online Access |
| description | The important of location to effect property value is widely acknowledged. However, traditional approaches in quantifying location influence on property value modelling are unsatisfactory. Value Residual Surface (VRS) has been suggested as an alternative to resolving the difficulty in the traditional modelling of location influence on property values in a particular area. This paper discusses the use of GIS generated VRS for delineating residential location value factors in the multiple regression analysis (MRA) model. A sample of 125 single and double-storey residential properties was used to construct regression model. Residuals generated from location-blind model were used to construct VRS to develop location adjustment factors. The results showed that using VRS integrative has allowed a clearer spatial visual picture of the location influence to be captured at all level in the study area. And, the location factors influence to property value can be modelled in a more effective way. |
| first_indexed | 2025-11-15T20:36:16Z |
| format | Conference or Workshop Item |
| id | utm-1163 |
| institution | Universiti Teknologi Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:36:16Z |
| publishDate | 2005 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utm-11632017-08-30T04:32:41Z http://eprints.utm.my/1163/ Modelling the value of location in the prediction of residential property value Mar Iman, Abdul Hamid Chin, Chui Vui H Social Sciences (General) The important of location to effect property value is widely acknowledged. However, traditional approaches in quantifying location influence on property value modelling are unsatisfactory. Value Residual Surface (VRS) has been suggested as an alternative to resolving the difficulty in the traditional modelling of location influence on property values in a particular area. This paper discusses the use of GIS generated VRS for delineating residential location value factors in the multiple regression analysis (MRA) model. A sample of 125 single and double-storey residential properties was used to construct regression model. Residuals generated from location-blind model were used to construct VRS to develop location adjustment factors. The results showed that using VRS integrative has allowed a clearer spatial visual picture of the location influence to be captured at all level in the study area. And, the location factors influence to property value can be modelled in a more effective way. 2005 Conference or Workshop Item NonPeerReviewed application/pdf en http://eprints.utm.my/1163/1/A_Hamid_Chin.pdf Mar Iman, Abdul Hamid and Chin, Chui Vui (2005) Modelling the value of location in the prediction of residential property value. In: First Real Estate Educators and Researchers Malaysia (REER) Seminar, 27-28 September 2005, UTM City Campus, Kuala Lumpur . (Unpublished) https://books.google.com.my/books/about/Modelling_the_Value_of_Location_in_the_P.html?id=w5qlnQAACAAJ&redir_esc=y |
| spellingShingle | H Social Sciences (General) Mar Iman, Abdul Hamid Chin, Chui Vui Modelling the value of location in the prediction of residential property value |
| title | Modelling the value of location in the prediction of residential property value |
| title_full | Modelling the value of location in the prediction of residential property value |
| title_fullStr | Modelling the value of location in the prediction of residential property value |
| title_full_unstemmed | Modelling the value of location in the prediction of residential property value |
| title_short | Modelling the value of location in the prediction of residential property value |
| title_sort | modelling the value of location in the prediction of residential property value |
| topic | H Social Sciences (General) |
| url | http://eprints.utm.my/1163/ http://eprints.utm.my/1163/ http://eprints.utm.my/1163/1/A_Hamid_Chin.pdf |