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Land Price Forecasting Research by Macro and Micro Factors and Real Estate Market Utilization Plan Research by Landscape Factors: Big Data Analysis Approach.

Authors :
Lee, Sang-Hyang
Kim, Jae-Hwan
Huh, Jun-Ho
Zavadskas, Edmundas Kazimieras
Antuchevičienė, Jurgita
Turskis, Zenonas
Source :
Symmetry (20738994); Apr2021, Vol. 13 Issue 4, p616, 1p
Publication Year :
2021

Abstract

In real estate, there are various variables for the forecasting of future land prices, in addition to the macro and micro perspectives used in the current research. Examples of such variables are the economic growth rate, unemployment rate, regional development and important locations, and transportation. Therefore, in this paper, data on real estate and national price fluctuation rates were used to predict the ways in which future land prices will fluctuate, and macro and micro perspective variables were actively utilized in order to conduct land analysis based on Big Data analysis. We sought to understand what kinds of variables directly affect the fluctuation of the land, and to use this for future land price analysis. In addition to the two variables mentioned above, the factor of the landscape was also confirmed to be closely related to the real estate market. Therefore, in order to check the correlation between the landscape and the real estate market, we will examine the factors which change the land price in the landscape district, and then discuss how the landscape and real estate can interact. As a result, re-explaining the previous contents, the future land price is predicted by actively utilizing macro and micro variables in real estate land price prediction. Through this method, we want to increase the accuracy of the real estate market, which is difficult to predict, and we hope that it will be useful in the real estate market in the future. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20738994
Volume :
13
Issue :
4
Database :
Complementary Index
Journal :
Symmetry (20738994)
Publication Type :
Academic Journal
Accession number :
150434017
Full Text :
https://doi.org/10.3390/sym13040616