Modeling the Commercial Property Value Using Ordinary Least Squared (OLS): A Case Study of Putatan, Sabah and Limbang, Sarawak

  • Oliver Valentine Eboy Geography Programme, Faculty of Social Sciences & Humanities, Universiti Malaysia Sabah (UMS)
  • Avie Krista Jurah Geography Programme, Faculty of Social Sciences & Humanities, Universiti Malaysia Sabah (UMS)
Keywords: commercial property, rental value, property valuation, Ordinary Least Square (OLS)


Real Estate is an asset that provides profitable investment in return. Commercial property constitutes an important part of the real estate sector. In valuing commercial property, rental value is an essential component for valuers in applying valuation methods. Determining the rental value usually a difficult process as it involves a lot of influence factors. There are various factors that can be used but not the same for every commercial property. Therefore, this paper shows the modeling valuation comparison between two commercial property areas of Putatan and Limbang that represent the outskirts of the city in Sabah and Sarawak respectively. The purpose of this study is to find an effective approach to develop a suitable model for commercial property valuation using OLS and subsequently intends to identify factors that influence the commercial properties for both study areas. The OLS technique was used for this study to develop the property valuation model in Putatan and Limbang.  The outcome shows that both study areas can be modeled using OLS for property valuation using similar factors but the Limbang area produced higher accuracy than Putatan based on the adjusted R2 value. However, in terms of the significant of the property value influence factors, both Limbang and Putatan produced different significant factors. Thus, it shows that most of the outskirt city commercial property valuation must be modeled using different influence factors. The model will benefit the local authorities, especially for commercial property valuation. Ultimately, revaluation also can be done easily with low cost, less time and few people needed for this approach.

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Land and Survey Department of Limbang, Sarawak. (2017). Shophouses Lot in Limbang Town.

Alexander and Schuster. (1998). Regression Analysis for Social Sciences. Academic Press: USA.

Buang Alias. (2000). Analysis of factors that contribute to the accumulation of uncollected rates in local authorities in Malaysia. PhD, Universiti Teknologi Malaysia, Skudai, Johor.

Christy Onyo (2017). Personal COmmunication. Jabatan Tanah dan Ukur, Limbang. Pegawai Penilaian, Jabatan Tanah dan Ukur Bahagian Limbang, Sarawak.

Demaris, A.shophouses (2004). Regression With Social Data: Modelling Continuos and Limited Response Variables. John Wiley & Sons, Inc.

ESRI. (2018). How Exploratory Regression Works. Online:

ESRI. (2013). Geographically Weighted Regression (Spatial Statistics). Retrieved 1May 2013, from

Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically weighted regression: The analysis of spatially varying relationships. New York, NY: John Wiley & Sons.

Gallimore, P., Fletcher, M. and Carter, M. (1996), "Modelling the influence of location on value", Journal of Property Valuation and Investment, Vol. 14(1), 6-19.

Hishamuddin. M. Ali (1998). Pembentukan Model Penawaran Optimum bagi Harta Tanah Perdagangan di Taman Perumahan. Universiti Teknologi Malaysia. Laporan Akhir VOT 71932.

Hutcheson, G. and Sofroniou, N. (1999). The Multivariate Social Scientist Introductory Statistics Using Generalized Linear Models. SAGE Publications Ltd.

Ismail Omar (1997). Penilaian Harta Tanah. Dewan Bahasa Dan Pustaka: Kuala Lumpur.

Lemias Ibin (2007). Aplikasi Sistem Maklumat Geografi (GIS) dalam Pembangunan Peta Nilai Harta Tanah Di Kota Kinabalu Tahun 1995 Hingga Tahun 2006.

Lin, C. C. (2010). Critical analysis and effectiveness of key parameters in residential

property valuations. Unpublished PhD, State University of New York, Buffalo, NY.

McCluskey, W. J., & Borst, R. A. (2011). Detecting and validating residential housing submarkets: A geostatistical approach for use in mass appraisal. 4(3), pp. 290-318. DOI:10.1108/17538271111153040

Millington, A. F. (2001). An Introduction to Property Valuation (5th ed.): Estate Gazette, London.

Netzell, O. (2013). The effect of accessibility on retail rents: testing integration value as a measure of geographic location. Journal of Property Research, 30(1), 1-23.

Oliver V. Eboy (2008). The Role of GIS for Property Valuation Support. The New Era for Asia GIS: Asia GIS 2008 Joint Conference of KAGIS Fall Symposium. Busan, Korea. 26-27September 2008.

Oliver V. Eboy (2006). Determining the Influence of Location Shop House’s Rental Value Using Spatial Statictics Techniques. Proceedings of The Interational Real Estate Research Symposium (IRERS) 11 – 13 April 2006, PWTC Kuala Lumpur, Malaysia.

Oliver V. Eboy and Edmund Sepikit (2010). Spatial Statistics Modelling in Property Valuation. ICT & Geospatial Technology Conference For Local Authority 2010. Delivering Quality Services Through Innovation (Green & Smart Tecnology. Geospatial Techonology. eValuation) 23-24 November 2010. Kota Kinabalu, Sabah.

Oliver V. Eboy and Ibrahim Sipan (2007). Modelling Interaction of Location Influence with Rental Value on Commercial Properties Using Spatial Statistic Techniques. Journal of Valuation and Property Services. Vol 7. No 1. 2007.

Renigier-Biłozor, M., Biłozor, A., Wiśniewski, R. (2017). Rating Engineering of Real Estate Markets as The Condition of Urban areas Assessment. Land Use Policy 61, 511–525

Ring, A. A and Dasso, J. (1972). Real Estate Principles and Practices. Englewood Cliff, N. J: Prentice Hall Inc.

Scott, I,. (1988). A Knowledge Based Approach to Computer – Assisted Mortagage Valuation of Residential Property. Pontypridd: University of Glamorgan.

Scott, L. M., and Janikas, M. V. (2010). Spatial Statistics in ArcGIS: Software Tools, Methods and Applications. In M. M. Fischer & A. Getis (Eds.), Handbook of Applied Spatial Analysis (pp. 27-41). Berlin Heidelberg: Springer.

Selamat Jati Yanjah (2017). Personal Communication. Pejabat Residen Daerah Limbang. Timbalan Residen (Pembangunan) Bahagian Limbang, Sarawak.

Shapiro, E., Mackmin, D., and Sams, G. (2009). Modern methods of valuation (10 ed.). London: EG Books.

Shaw, G. and Wheeler, D. (1985). (in Nurul Ainin Mukhatar. 2005). Kesan Peruntukan Efektif Syarikat Harta Tanah Di Bursa Malaysia. Universiti Teknologi Malaysia.

So, H. M., Tse, R. Y. C. and Ganesan, S,. (1997). Estimation the Influence of Transport on House Prices: Evidence from Hong Kong. Journal of Property Valuation and Investment. 15(1): 40 – 47

Tabachnick, B. G. and Fidell, L. S. (1989). Using Multivariate Statistics. Second Edition. New York: Harper Collins.

Watson Jeffry Kaling (2018). Temu bual. Jabatan Penilaian dan Perkhidmatan Harta. Penolong Pegawai Penilaian, Jabatan Penilaian dan Perkhidmatan Harta (JPPH) Cawangan Miri, Sarawak.

Wyatt, P. J. (1997). The Development of Property Information Systems for Real Estate Valuation. International Journal of Geographical Information Systems. 11(5): 435-450

Wyatt , P. J. and Ralphs, M. (2003). GIS in Land and Property Management. Spon Press, Taylor and Francis Group: London.
How to Cite
Eboy, O. V. and Jurah, A. K. (2021) “Modeling the Commercial Property Value Using Ordinary Least Squared (OLS): A Case Study of Putatan, Sabah and Limbang, Sarawak”, Malaysian Journal of Social Sciences and Humanities (MJSSH), 6(3), pp. 290 - 296. doi: