• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.151-152
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• 2021

The sale price of apartment buildings is a key factor in the success or failure of apartment projects, and the factors that affect the sale price of apartments vary widely, including location, environmental factors, and economic conditions. Existing methods of predicting the sale price do not reflect the nonlinear characteristics of apartment prices, which are determined by the complex impact factors of reality, because statistical analysis is conducted under the assumption of a linear model. To improve these problems, a new analysis technique is needed to predict apartment sales prices by complex nonlinear influencing factors. Using machine learning techniques that have recently attracted attention in the field of engineering, it is possible to predict the sale price reflecting the complexity of various factors. Therefore, this study aims to conduct a basic study for the development of a machine learning-based prediction model for apartment sale prices.

• Journal of the Korean Professional Engineers Association
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• v.40 no.5
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• pp.73-78
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• 2007

The apartment sale in lots price upper limit system was propelled from this month for stabilization of the residential policy that will lower the apartment sale in lots price. the private constructive industry presents how make activated the apartment enterprise, presents what kind of problems it has and points the complementary problems when the government enforcing it.

• Journal of the Korea Institute of Building Construction
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• v.6 no.3 s.21
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• pp.67-73
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• 2006

This study aims to evaluate the feasibility of remodeling business by predicting the future price of apartment house after remodeling using Hedonic Price Model. The data concerning such 9 independent variables as location, unit size, unit plan, landscape, parking, the number of elapsed years after completion, number of units, mechanical performance, interior from 25 regions in Seoul metropolitan city were collected and evaluated by established evaluation criteria. The coefficients affecting the price of apartment unit were made by Ivay of linear multi-regression and put into Hedonic Price Model. The feasibility evaluation model for apartment was made and verified by data of remodelled apartment. The predicted results using suggested evaluation model coincide with actual apartment market situations.

• Smart Media Journal
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• v.11 no.3
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• pp.62-73
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• 2022

Researches on the prediction of domestic apartment sales price have been continuously conducted, but it is not easy to accurately predict apartment prices because various characteristics are compounded. Prior to predicting apartment sales price, the analysis of major factors, influencing on sale prices, is of paramount importance to improve the accuracy of sales price. Therefore, this study aims to analyze what are the factors that affect the apartment sales price in Gwangju, which is currently showing a steady increase rate. With 6 years of Gwangju apartment transaction price and various social factor data, several maching learning techniques such as multiple regression analysis, random forest, and deep artificial neural network algorithms are applied to identify major factors in each model. The performances of each model are compared with RMSE (Root Mean Squared Error), MAE (Mean Absolute Error) and R² (coefficient of determination). The experiment shows that several factors such as 'contract year', 'applicable area', 'certificate of deposit', 'mortgage rate', 'leading index', 'producer price index', 'coincident composite index' are analyzed as main factors, affecting the sales price.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3747-3756
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• 2012

This paper examines the effect of price ceiling regulation on the new apartment price. The analysis procedure of the study is divided into two parts, which stand for a case study on the effect of price control on the new apartment price and the survey of real estate experts on price ceiling regulation. The empirical results of our case study show that the selling price under price ceiling regulation is generally lower than that in the situation of price deregulation, in terms of the land development expense and construction cost. With regard to the survey results, more than half of respondents have opinions that price ceiling regulation has an impact on the new apartment price and lowers the price. They are equally divided pro and con regarding the problem of keeping or discarding the regulation.

• KIEAE Journal
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• v.7 no.3
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• pp.11-20
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• 2007

The purpose of this study is to analyse the effects of the eco-friendly factors on the apartment housing price rise and to suggest the desirable way of marketing strategy for apartment housing. For the analysis, the data of apartment sites in Seoul had been collected from September 2006 to February 2007. The data consisted of 95 apartment sites in Seoul. Data were analyzed with descriptives, crosstabs, and discriminant analysis by SPSS/PC for Window. Following result was obtained. The eco-friendly apartment housing price rate in Seoul was determined by eco-friendly landscape, green space rate, house unit size, installment sale price per pyeong, floor space index, distance from subway station when it was not considered the impact of building age, construction company's brand, and autonomous districts. Findings of this research can provide valuable information for marketing strategy of housing construction company.

• Journal of the Korean housing association
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• v.14 no.4
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• pp.131-138
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• 2003

The purpose of this study was to examine how the purchasers perceive the effects of the unit characteristics within the complex on the apartment prices. Six major characteristics of the apartments : orientations and floors; views; structures; conditions and maintenances of interior materials; interior alterations; and access to the outdoor facilities were included for the analysis. The data were gathered from 284 households in seven private apartment complexes in Ulsan. It was found that the price of the apartment was higher if it was southward, on the royal or semi-royal floors, with the nice view for the riverside or any other landscape resources, or openness. Other characteristics which increase the price were the hall type not the corridor one, inner side of the building, good conditions of interior materials, and extended balcony.

• Communications for Statistical Applications and Methods
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• v.15 no.2
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• pp.173-191
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• 2008

The goal of this paper is analyzing and modeling the trend of apartment market price in Seoul using the dynamic linear model(DLM). We use the market price per pyeong of 30-pyeong-apartment provided by "KB apartment market price database" of Kookmin bank. The data is collected from June $24^{th}$, 2003 to August $28^{th}$, 2006. The inspection of the data reveals that the trend of apartment market price in Seoul can be divided into two groups and we assume that the price is expressed by the common trend of divided groups. We try to estimate the price of apartment by DLM using the Bayesian method.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.111-119
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• 2024

The purpose of study is to analyze the effect of population inflow on apartment price growth. For this purpose, proxy for population structure is employed: (i) net population inflow based on 'resident registration criteria', (ii) buyer's transaction. The major findings are as followed. First, net population inflow of total and 50 over gives no significant effects on the apartment price growth in Seoul and Jeju. However, there are significant and positive effects of 50s and 60s in Seoul, and 60s in Jeju on the apartment price growth, respectively. Second, buyer's transactions of 'total and 50 over' give positive effect on apartment price growth only in Seoul. However, 60s and 50s of buyers' transaction give positive effect on the apartment price growth both in Seoul and Jeju. This study implies that more detailed population inflow like age group provide more meaningful information to the study on apartment price growth.

• Korea Real Estate Review
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• v.24 no.1
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• pp.7-14
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• 2014

This study, as the temporal and spatial data for the real price apartment in Seoul from January 2006 to June 2013, empirically compared and analyzed the estimation result of apartment price using OLS by hedonic price model for the problem of space-time correlation, temporal autoregressive model (TAR) considering temporal effect, spatial autoregressive model (SAR) spatial effect and spatiotemporal autoregressive model (STAR) spatiotemporal effect. As a result, the adjusted R-square of STAR model was increased by 10% compared that of OLS model while the root mean squares error (RMSE) was decreased by 18%. Considering temporal and spatial effect, it is observed that the estimation of apartment price is more correct than the existing model. As the result of analyzing STAR model, the apartment price is affected as follows; area for apartment(-), years of apartment(-), dummy of low-rise(-), individual heating (-), city gas(-), dummy of reconstruction(+), stairs(+), size of complex(+). The results of other analysis method were the same. When estimating the price of real estate using STAR model, the government officials can improve policy efficiency and make reasonable investment based on the objective information by grasping trend of real estate market accurately.