Prediction Model of House Price in Chiang Mai Province

Authors

  • Damrongsak Rinchumphu Department of Civil Engineering, Faculty of Engineering, Chiang Mai University 50000, THAILAND, Civil Innovation and City Innovation Research Laboratory, Chiang Mai 50000, THAILAND
  • Pokpatapee Buosont Department of Civil Engineering, Faculty of Engineering, Chiang Mai University 50000, THAILAND, Civil Innovation and City Innovation Research Laboratory, Chiang Mai 50000, THAILAND
  • Nopnawat Lualai Department of Civil Engineering, Faculty of Engineering, Chiang Mai University 50000, THAILAND , Civil Innovation and City Innovation Research Laboratory, Chiang Mai 50000, THAILAND
  • Setthawut Ketklin Department of Civil Engineering, Faculty of Engineering, Chiang Mai University 50000, THAILAND , Civil Innovation and City Innovation Research Laboratory, Chiang Mai 50000, THAILAND
  • Warut Timprae Civil Innovation and City Innovation Research Laboratory, Chiang Mai 50000, THAILAND
  • Sarote Tepweerakun Civil Innovation and City Innovation Research Laboratory, Chiang Mai 50000, THAILAND
  • Choo Yit Yang Shin Yang Composite Sdn Bhd, Sarawak 98000, MALAYSIA
  • Non Phichetkunbodee Department of Civil Engineering, Faculty of Engineering, Chiang Mai University 50000, THAILAND, Civil Innovation and City Innovation Research Laboratory, Chiang Mai 50000, THAILAND

Keywords:

Prediction Model, House Price, Hedonic Price Model, Regression Analysis, Chiang Mai

Abstract

Pre-sale house price estimation has been a challenge for real estate developers, especially for emerging markets such as Chiang Mai. Therefore, this study calibrated and established a Hedonic Pricing Model to forecast the sales price of new houses from 125 residential development projects located in Chiang Mai, Thailand. In this study, a total of 22 variables were recorded, and the data were classified into 3 categories, which were location, physical attribute of the project and the nature of the house and land. The results showed 8 out of 22 variables were well incorporated in the model, and the Semi-Natural Logarithm form was determined as the most suitable model for predicting the pre-sale price at this target location. The asking price of a new detached housing project was found at 25.36% higher than other types of houses. Meanwhile, the newly-constructed house price was decreased by 9.98% if the project location was adjacent to or further away from the ring road, which was distant away from the Chiang Mai Metropolitan area. Furthermore, the house’s pre-sale price was dropped when the available number of units in the project was large. The outcomes of this study indicate the effectiveness of the developed model as a proficient tool for estimating the competitive price for newly built properties in Chiang Mai.

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Published

2020-12-29

How to Cite

Rinchumphu, D., Buosont, P., Lualai, N., Ketklin, S., Timprae, W., Tepweerakun, S., Yang, C. Y., & Phichetkunbodee, N. (2020). Prediction Model of House Price in Chiang Mai Province. International Journal of Building, Urban, Interior and Landscape Technology (BUILT), 16, 47–54. Retrieved from https://ph02.tci-thaijo.org/index.php/BUILT/article/view/242450

Issue

Vol. 16 (2020): July - December

Section

Research Article

License

Copyright (c) 2020 International Journal of Building, Urban, Interior and Landscape Technology (BUILT)

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.