Development of Simulation Model for Proper Sales Price of Apartment House in Seoul
Author(s): |
Kihyuk Kim
Jiyeong Yun Sungjin Kim Dae Young Kim Donghoon Lee |
---|---|
Medium: | journal article |
Language(s): | English |
Published in: | Buildings, 24 November 2020, n. 12, v. 10 |
Page(s): | 244 |
DOI: | 10.3390/buildings10120244 |
Abstract: |
The number of new homes built in China in 2014 doubled compared to 2004, while Korea has built more than 3000 units every year since 2004 and Japan has built more than 6000 new units. Apartments account for 60% of homes in Korea, so it is anticipated that apartment construction projects will not cease in Korea. The current company assumes that the sale rate (pre-sale rate) of apartments may be completely controlled by the pre-sale prices. The study calculated appropriate pre-sale prices to maximize the revenue of companies based on that assumption. For that purpose, the study identified the factors affecting the pre-sale prices and analyzed its correlation with the pre-sale prices based on the apartments located in Seoul, Korea. As a result of the analysis, it was found that the pre-sale prices of apartments are correlated with the number of apartment complexes, local rates, and local development level. The final result of the study suggested a way to calculate the sale prices using the factors that are thought to be correlated with the pre-sale prices. A simulation model was created using the method. When tested, it yielded an average deviation rate of 10.32%. The current study will contribute to preventing the economic losses that may be caused by apartment construction projects. |
Copyright: | © 2020 by the authors; licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
Geographic Locations
2.48 MB
- About this
data sheet - Reference-ID
10535705 - Published on:
01/01/2021 - Last updated on:
02/06/2021