Modeling property rating valuation using Geographical Weighted Regression (GWR) and Spatial Regression Model (SRM): the case of Kota Kinabalu, Sabah

Property revaluation or reassessment is a compulsory activity for property tax to be imposed on all properties. It was conducted manually, involving exhaustive, time consuming and costly processes. As such there is a growing need to develop alternative valuation models capable of estimating proper...

Full description

Bibliographic Details
Main Authors:	Oliver Valentine Eboy, Narimah Samat
Format:	Article
Language:	English
Published:	Faculty of Social Sciences and Humanities, UKM,Bangi 2015
Online Access:	http://journalarticle.ukm.my/9546/ http://journalarticle.ukm.my/9546/ http://journalarticle.ukm.my/9546/1/10x.full-geookt15-oliver-edam.pdf

id	ukm-9546
recordtype	eprints
spelling	ukm-95462016-12-14T06:50:16Z http://journalarticle.ukm.my/9546/ Modeling property rating valuation using Geographical Weighted Regression (GWR) and Spatial Regression Model (SRM): the case of Kota Kinabalu, Sabah Oliver Valentine Eboy, Narimah Samat, Property revaluation or reassessment is a compulsory activity for property tax to be imposed on all properties. It was conducted manually, involving exhaustive, time consuming and costly processes. As such there is a growing need to develop alternative valuation models capable of estimating property values of large numbers in a short time with little manpower and low costs. The spatial statistics of geographical weighted regression (GWR) and spatial regression model (SRM) are two of them. This study demonstrates the development of the GWR and SRM in estimating residential property value in areas under the Kota Kinabalu City Hall (DBKK) jurisdiction. It collected and cleaned 5,524 data items. Five valid and significant variables were identified and utilized in the modeling exercise. By using GWR and SRM various tests were conducted to identify and remove modeling errors such as multicollinearity, heteroscedasticity and spatial autocorrelation. It was found that the SRM stood out as the best property rating valuation model for DBKK area compared to the GWR. The SRM analysis also identified the building quality as the main positive influence of the property rates while the location factor provides the least in influence. In short, this study had proved the effectiveness of SRM in producing a property rating valuation model even with problematic dataset. It could also, in addition, easily produce property value maps to indicate variations in property rates and thus improve the management of property rating valuation in local authority areas. Faculty of Social Sciences and Humanities, UKM,Bangi 2015-10 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/9546/1/10x.full-geookt15-oliver-edam.pdf Oliver Valentine Eboy, and Narimah Samat, (2015) Modeling property rating valuation using Geographical Weighted Regression (GWR) and Spatial Regression Model (SRM): the case of Kota Kinabalu, Sabah. Geografia : Malaysian Journal of Society and Space, 11 (11). pp. 98-109. ISSN 2180-2491 http://www.ukm.my/geografia/v2/index.php?cont=a&item=2&thn=2015&vol=11&issue=11&ver=loc
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Kebangasaan Malaysia
building	UKM Institutional Repository
collection	Online Access
language	English
description	Property revaluation or reassessment is a compulsory activity for property tax to be imposed on all properties. It was conducted manually, involving exhaustive, time consuming and costly processes. As such there is a growing need to develop alternative valuation models capable of estimating property values of large numbers in a short time with little manpower and low costs. The spatial statistics of geographical weighted regression (GWR) and spatial regression model (SRM) are two of them. This study demonstrates the development of the GWR and SRM in estimating residential property value in areas under the Kota Kinabalu City Hall (DBKK) jurisdiction. It collected and cleaned 5,524 data items. Five valid and significant variables were identified and utilized in the modeling exercise. By using GWR and SRM various tests were conducted to identify and remove modeling errors such as multicollinearity, heteroscedasticity and spatial autocorrelation. It was found that the SRM stood out as the best property rating valuation model for DBKK area compared to the GWR. The SRM analysis also identified the building quality as the main positive influence of the property rates while the location factor provides the least in influence. In short, this study had proved the effectiveness of SRM in producing a property rating valuation model even with problematic dataset. It could also, in addition, easily produce property value maps to indicate variations in property rates and thus improve the management of property rating valuation in local authority areas.
format	Article
author	Oliver Valentine Eboy, Narimah Samat,
spellingShingle	Oliver Valentine Eboy, Narimah Samat, Modeling property rating valuation using Geographical Weighted Regression (GWR) and Spatial Regression Model (SRM): the case of Kota Kinabalu, Sabah
author_facet	Oliver Valentine Eboy, Narimah Samat,
author_sort	Oliver Valentine Eboy,
title	Modeling property rating valuation using Geographical Weighted Regression (GWR) and Spatial Regression Model (SRM): the case of Kota Kinabalu, Sabah
title_short	Modeling property rating valuation using Geographical Weighted Regression (GWR) and Spatial Regression Model (SRM): the case of Kota Kinabalu, Sabah
title_full	Modeling property rating valuation using Geographical Weighted Regression (GWR) and Spatial Regression Model (SRM): the case of Kota Kinabalu, Sabah
title_fullStr	Modeling property rating valuation using Geographical Weighted Regression (GWR) and Spatial Regression Model (SRM): the case of Kota Kinabalu, Sabah
title_full_unstemmed	Modeling property rating valuation using Geographical Weighted Regression (GWR) and Spatial Regression Model (SRM): the case of Kota Kinabalu, Sabah
title_sort	modeling property rating valuation using geographical weighted regression (gwr) and spatial regression model (srm): the case of kota kinabalu, sabah
publisher	Faculty of Social Sciences and Humanities, UKM,Bangi
publishDate	2015
url	http://journalarticle.ukm.my/9546/ http://journalarticle.ukm.my/9546/ http://journalarticle.ukm.my/9546/1/10x.full-geookt15-oliver-edam.pdf
first_indexed	2023-09-18T19:55:10Z
last_indexed	2023-09-18T19:55:10Z
_version_	1777406480417292288

Modeling property rating valuation using Geographical Weighted Regression (GWR) and Spatial Regression Model (SRM): the case of Kota Kinabalu, Sabah

Similar Items