• Journal of the Korean Professional Engineers Association
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• v.38 no.4
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• pp.7-9
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• 2005

The recent speculation fever in Kangnam and its southern vicnity of Seoul resulted in surging apartment prices. The government is determined to employ more effective anti-speculation policy measures to control the property speculative demand. The Government plans to implement support measures to discourage people from owning multiple homes by reinforcing tax measures. To meet the increasing demand for more large-sized apartments in Seoul, the Government may allow to build more large sized units. By the end of August, 'a comprehensive package tool of real estate policy measures' ,as a real estate controlling guidelines, is scheduled to be presented by the Government. We hope that the package tool will stabilize housing market more effectively and enhance the national economy.

• Journal of the Korea Institute of Building Construction
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• v.22 no.1
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• pp.81-90
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• 2022

With apartment purchase prices rising, small and medium-sized cities have been highlighted as areas in which real estate speculation is overheated, and thus designated as target districts for adjustment. In addition, tax policy is constantly being adjusted in an attempt to stabilize real estate prices. The purpose of this study is to analyze the basic effect of tax policy on the purchase price of apartments in small and medium-sized cities. This study selected apartments in the Daejeon area that were constructed between 1990 and 2015. In addition, tax policy was divided into regulatory policy and easing policy based on tax increase and tax cut. This study analyzes the short-term difference of one year before and after the change in the purchase price of apartment houses. In addition, this study set the time when real estate policy was implemented and the actual transaction price of apartments in Daejeon as the analysis targets, and analyzed the correlation between tax policy and apartment sales prices through the NPV technique and T-test results. Through the study, it was found that most tax policies changed apartment purchase prices in the short term.

• Journal of the Korean housing association
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• v.18 no.3
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• pp.63-72
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• 2007

The purpose of this study is to identify the impact of the building, site, and region characteristic factors on the annual average price rising rate of apartment housing in Seoul. The data were consisted of 272 apartment units in Seoul. A survey included checking the drawing documents and interview with apartment maintenance staffs and real estate agencies from October 2006 to February 2007. Data were analyzed with descriptives, frequency, crosstabs, and linear regression by SPSS/PC for Window. The linear regression model was employed to evaluate the price rising rate in apartment housing. Following results were obtained. The price rising rate for pyeong ($3.3m^2$) of apartment housing was determinated by the district zone, the construction company's brand name, the building age, the building stories, the floor space index, the building-to-land ratio, the green space rate, and the distance from the downtown. Especially, the district zone was the most important factor that affected the price rising of apartment housing in Seoul. Therefore, the policy has to focus to solve the imbalance between autonomous districts with the collaborated tax.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.5-20
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• 2018

This paper aims to analyze characteristic by the cities focused on the ratio of new apartment resale that is one of the apartment unit sale market, which has been increased recently. So, this study examined characteristics of population, apartment trade & sale, housing with 162 cities and counties and performed multiple regression analysis with dependent variable, ratio of new apartment resale. As a result. the factors affecting the ratio of new apartment resale are 7variables, apartment sales rate, transfer of ownership, apartment turnover rate, sale volume, regional apartment rate, population increasing rate, housing average apartment sale price rate. In terms of the increase in apartment sales prices, the rate of sales price increase was relatively low in areas where the transaction rate for apartment sales is high, and the number of apartment sales right transactions increased as the number of other ownership transfers rose. As a result, the data will be based on the improvement of the government's policies and systems to stimulate the transaction focused on the real estate agents in the apartment market.

• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.274-283
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• 2022

Korea is facing a number difficulties arising from rising housing prices. As 'housing' takes the lion's share in personal assets, many difficulties are expected to arise from fluctuating housing prices. The purpose of this study is creating housing price prediction model to prevent such risks and induce reasonable real estate purchases. This study made many attempts for understanding real estate instability and creating appropriate housing price prediction model. This study predicted and validated housing prices by using the LSTM technique - a type of Artificial Intelligence deep learning technology. LSTM is a network in which cell state and hidden state are recursively calculated in a structure which added cell state, which is conveyor belt role, to the existing RNN's hidden state. The real sale prices of apartments in autonomous districts ranging from January 2006 to December 2019 were collected through the Ministry of Land, Infrastructure, and Transport's real sale price open system and basic apartment and commercial district information were collected through the Public Data Portal and the Seoul Metropolitan City Data. The collected real sale price data were scaled based on monthly average sale price and a total of 168 data were organized by preprocessing respective data based on address. In order to predict prices, the LSTM implementation process was conducted by setting training period as 29 months (April 2015 to August 2017), validation period as 13 months (September 2017 to September 2018), and test period as 13 months (December 2018 to December 2019) according to time series data set. As a result of this study for predicting 'prices', there have been the following results. Firstly, this study obtained 76 percent of prediction similarity. We tried to design a prediction model of real estate transaction price with the LSTM Model based on AI and Bigdata. The final prediction model was created by collecting time series data, which identified the fact that 76 percent model can be made. This validated that predicting rate of return through the LSTM method can gain reliability.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.543-548
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• 2002

The brand value of apartment which affects not only sale percent and profit but also the worth of real estate is rising as an important point of apartment competition. But now the apartment brand market is occupied by some large-sized construction companies with strong recognition. So it's difficult for newly joined construction companies to enter the apartment market and the companies that made inroads into the market don't have the brand effects because of consumers' ignorance. Therefore, through the analysis of example from construction and industrial companies, I suggest the marketing strategy which consists of target market, positioning strategy, brand naming strategy, PR strategy and distinct strategy.

• Journal of the Korea Furniture Society
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• v.18 no.3
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• pp.166-176
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• 2007

Thanks to the recent apartment housing sales in new cities and metropolitan area, the public-use furniture market is greatly animated with the development of customized furniture. Nevertheless, the situation becomes difficult because of the fierce competition among the furniture suppliers with quoting at the lower price to get the order. In order to produce unique and stylish living cabinets, it is required for the furniture designer to create the design under the systematic design process collaborated with the construction company and make the design proposal thereby to the construction company. The present paper is focused on the re-usability of TV set currently possessed by the tenant, variability, uniqueness, pricing level suitable for the cost of real estate sales, modern design and so on. in the development of apartment living room cabinet. Thus, it is important for the furniture supplier to realize the importance of the design field in order to enhance the competitiveness of the customized furniture in the apartment housing. Accordingly the present researcher has developed the modem variable living room cabinet in accordance with the systemic design process by realizing the leads of tenant of the apartment housing and then establishing the concept focused on the design required by both the tenant and construction company.

• Journal of the Korean Regional Science Association
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• v.39 no.2
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• pp.47-61
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• 2023

Satisfaction on the residential environment is a major factor influencing the choice of residence and migration, and is directly related to the quality of life in the city. As online services of real estate increases, people's evaluation on the residential environment can be easily checked and it is possible to analyze their satisfaction and its determining factors based on their evaluation. This means that a larger amount of evaluation can be used more efficiently than previously used methods such as surveys. This study analyzed the residential environment reviews of about 30,000 apartment residents collected from 'Zigbang', an online real estate service in Seoul. The apartment review of Zigbang consists of an evaluation grade on a 5-point scale and the evaluation content directly described by the dweller. At first, this study labeled apartment reviews as positive and negative based on the scores of recommended reviews that include comprehensive evaluation about apartment. Next, to classify them automatically, developed a model by using Bidirectional Encoder Representations from Transformers(BERT), a deep learning-based natural language processing model. After that, by using SHapley Additive exPlanation(SHAP), extract word tokens that play an important role in the classification of reviews, to derive determining factors of the evaluation of the residential environment. Furthermore, by analyzing related keywords using Word2Vec, priority considerations for improving satisfaction on the residential environment were suggested. This study is meaningful that suggested a model that automatically classifies satisfaction on the residential environment into positive and negative by using apartment review big data and deep learning, which are qualitative evaluation data of residents, so that it's determining factors were derived. The result of analysis can be used as elementary data for improving the satisfaction on the residential environment, and can be used in the future evaluation of the residential environment near the apartment complex, and the design and evaluation of new complexes and infrastructure.

• Korean Journal of Construction Engineering and Management
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• v.7 no.2 s.30
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• pp.162-170
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• 2006

Neural network analysis is expected to enhance the forecasting ability for the real estate market. This paper reviews definition, structure, strengths and weaknesses of neural network analysis, and verifies the applicability of neural network analysis for the real estate market. Neural network analysis is compared with regression analysis using the same sample data. The analyses model the macroeconomic parameters that influence the sales price of apartments. The results show that neural network analysis provides better forecasting accuracy than regression analysis does, what confirms the applicability of neural network analysis for the real estate market.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.2
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• pp.301-306
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• 2013

The Ratio of APT jeonse to purchase price was still rising. The interaction of APT Purchase and Jeonse price indices by region analysis in order to analyze this phenomenon, and results were summarized as follows. First, because the regional APT purchase and jeonse prices appears the rise and fall differently by region, regional polarization was deepening. Second, the recently real estate market was analyzed the province's booming real estate and the downturn of the metropolitan area. So, the ratio of APT jeonse to purchase price was continued to rise. Finally, the Ratio of APT jeonse to purchase price changing rate is (+) increased if the APT purchase price changing rate is larger then the APT purchase price changing rate and smaller then is (-) decreased.