• Journal of Digital Convergence
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• v.19 no.9
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• pp.9-18
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• 2021

Constructing the Metropolitan Railway Express (the GTX) may have an impact on consumer confidence and housing sales price located near the planned route. This study looked at how consumers' psychology and housing prices change as the large-scale transport infrastructure plane was planned. Also, it looked at the relationship between consumer sentiment and housing prices to analyze the impact of new transportation facilities inflows. Using a correlation analysis, the relationship between the consumer sentiment index and the actual transaction price of apartments was identified. The impact of GTX on the consumer sentiment index and the actual transaction price of apartments was looked at using the Difference-in-Differences methodology. Our finding shows that the construction plan of a large-scale transportation infrastructure in the metropolitan area affects the sentiment of housing consumption and actual transactions. In a situation where the government is speeding up the construction of a wide-area transportation network such as GTX with the goal of becoming a city where people can commute to downtown Seoul within 30 minutes, policies that can stabilize the housing market in transportation hubs should be suggested.

• The Journal of the Korea Contents Association
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• v.16 no.7
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• pp.168-178
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• 2016

The purpose of the study is to present an analysis of the expatriate leasing market for highly-paid professionals residing in Seoul. The effects of physical and locational attributes, range of amenities along with expat's national and industrial attributes on housing rents are being empirically evaluated based on transactions. Using lease transaction data for the period of 1994 through 2013, the results show that physical and locational attributes which have been proved to affect conventional housing value are also confirmed to affect leasing housing rent for expatriate. Also this study finds the following results. First, housing rent is found to be influenced by foreign residents' occupation. Therefore banking, petrochemical, insurer and pharmaceutical company affect positively on housing rent while mechanic firms influenced negatively to rent. Second, housing rent is found to be affected by foreign residents' nationalities. The results indicate USA and the United Kingdom have a positive effect while French has a negative effect on rent.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.95-118
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• 2017

Recent centrally the downtown area, the transaction between the row housing and multiplex housing is activated and platform services such as Zigbang and Dabang are growing. The row housing and multiplex housing is a blind spot for real estate information. Because there is a social problem, due to the change in market size and information asymmetry due to changes in demand. Also, the 5 or 25 districts used by the Seoul Metropolitan Government or the Korean Appraisal Board(hereafter, KAB) were established within the administrative boundaries and used in existing real estate studies. This is not a district classification for real estate researches because it is zoned urban planning. Based on the existing study, this study found that the city needs to reset the Seoul Metropolitan Government's spatial structure in estimating future housing prices. So, This study attempted to classify the area without spatial heterogeneity by the reflected the property price characteristics of row housing and Multiplex housing. In other words, There has been a problem that an inefficient side has arisen due to the simple division by the existing administrative district. Therefore, this study aims to cluster Seoul as a new area for more efficient real estate analysis. This study was applied to the hedonic model based on the real transactions price data of row housing and multiplex housing. And the K-Means Clustering algorithm was used to cluster the spatial structure of Seoul. In this study, data onto real transactions price of the Seoul Row housing and Multiplex Housing from January 2014 to December 2016, and the official land value of 2016 was used and it provided by Ministry of Land, Infrastructure and Transport(hereafter, MOLIT). Data preprocessing was followed by the following processing procedures: Removal of underground transaction, Price standardization per area, Removal of Real transaction case(above 5 and below -5). In this study, we analyzed data from 132,707 cases to 126,759 data through data preprocessing. The data analysis tool used the R program. After data preprocessing, data model was constructed. Priority, the K-means Clustering was performed. In addition, a regression analysis was conducted using Hedonic model and it was conducted a cosine similarity analysis. Based on the constructed data model, we clustered on the basis of the longitude and latitude of Seoul and conducted comparative analysis of existing area. The results of this study indicated that the goodness of fit of the model was above 75 % and the variables used for the Hedonic model were significant. In other words, 5 or 25 districts that is the area of the existing administrative area are divided into 16 districts. So, this study derived a clustering method of row housing and multiplex housing in Seoul using K-Means Clustering algorithm and hedonic model by the reflected the property price characteristics. Moreover, they presented academic and practical implications and presented the limitations of this study and the direction of future research. Academic implication has clustered by reflecting the property price characteristics in order to improve the problems of the areas used in the Seoul Metropolitan Government, KAB, and Existing Real Estate Research. Another academic implications are that apartments were the main study of existing real estate research, and has proposed a method of classifying area in Seoul using public information(i.e., real-data of MOLIT) of government 3.0. Practical implication is that it can be used as a basic data for real estate related research on row housing and multiplex housing. Another practical implications are that is expected the activation of row housing and multiplex housing research and, that is expected to increase the accuracy of the model of the actual transaction. The future research direction of this study involves conducting various analyses to overcome the limitations of the threshold and indicates the need for deeper research.

• Land and Housing Review
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• v.12 no.2
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• pp.33-45
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• 2021

Due to recent changes in government policy, officetels have received attention as alternative assets, along with the uplift of office and apartment prices in Seoul. However, the current officetel price indexes use small-size samples and, thus, there is a critique on their accuracy. They rely on valuation prices which lag the market trend and do not properly reflect the volatile nature of the property market, resulting in 'smoothing'. Therefore, the purpose of this paper is to create the officetel price index using transaction data. The data, provided by the Ministry of Land, Infrastructure and Transport from 2005 to 2020, includes sales prices and rental prices - Jeonsei and monthly rent (and their combinations). This study employed a repeat sales model for sales, jeonsei, and monthly rent indexes. It also contributes to improving conversion rates (between deposit and monthly rent) as a supplementary indicator. The main findings are as follows. First, the officetel price index and jeonsei index reached 132.5P and 163.9P, respectively, in Q4 2020 (1Q 2011=100.0P). However, the rent index was approximately below 100.0. Sales prices and jeonsei continued to rise due to high demand while monthly rent was largely unchanged due to vacancy risk. Second, the increase in the officetel sales price was lower than other housing types such as apartments and villas. Third, the employed approach has seen a potential to produce more reliable officetel price indexes reflecting high volatility compared to those indexes produced by other institutions, contributing to resolving 'smoothing'. As seen in the application in Seoul, this approach can enhance accuracy and, therefore, better assist market players to understand the market trend, which is much valuable under great uncertainties such as COVID-19 environments.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.43-53
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• 2014

This study aims to improve the openness of administrative data and to make extensive use of it in the academic and policy development, analyzing the quality requirements as the users' view of administrative data using statistical purposes. Conducted the exploratory analysis on the case of the Transaction-based Price Index of Housing, applying the administrative data of Realestate Transaction Management System in Korea, based on Denmark's 7 quality indicators for the statistical use of administrative data. According to the results of this study, the administrative data could improve the efficacy of the policy by facilitating the collection of the statistical data which help analyzing the actual market situations. On the other hand, the data have some constraints in adding the required items to producing the statistics, or improving the timeliness problem, due to the characteristics focused on the civil service.

• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.358-366
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• 2022

Recently, 'Apartment community facilities' have emerged as the most optional factor in the apartment market, and their level is becoming very important. Therefore, this study derived each type through latent profile analysis centering on health-related community facilities in 126 domestic main apartment complexes, and as a result of the analysis, it was confirmed that it was divided into a Pilates group, GX and Yoga group, Golf and Table Tennis practice range group, and overall low group. Among the four groups, Pilates, GX, and yoga groups are more likely to belong to Gangnam, Seocho and Songpa compared to complexes with many golf and table tennis practice ranges, and at the same time, the transaction price is also the highest. Through these analysis results, it was suggested that changes in the preference for leisure activities should be reflected when constructing community facilities, and that health-related community facilities should be deeply considered in residential welfare policies in consideration of high preference for fitness facilities in youth housing.

• Korean Business Review
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• v.19 no.2
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• pp.1-21
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• 2006

The purpose of this study is to analysis of the policy and problems of the capital gain tax. So this study identified the problems in the tax system and the method, suggested some ideas that can be useful for reforming the current capital gain tax system. The followings are the concise of some ideas. First, government should adopt the housing market stabilization policy in the long-term period, not in the short-term period which depend on the financial market and the part of home supply. Second, determining the capital gains tax should be transferred to actual market prices system rather than based on the standard assessed prices by government through the nations. By doing so, the desired principles of taxation come true such as principle of taxation on economic substance, principle of taxation on solid foundation and principle of taxation on tax paying ability. Third, transaction taxes should be minimized in the aborting the property speculations and the stabilizing the actual market prices. Fourth, the system of non tax to the owners of 'one family, one house' should be excluded to the tune of principle of tax equity. By doing so, tax payers could be induced to pay taxes on a timely basis not commit to wrong doings. In conclusion, anti-speculation policy should be progressed in such a comprehensive and sustained way as to wipe out the psychology of expectation about the transfer gain's incomes.

• Journal of the Economic Geographical Society of Korea
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• v.24 no.1
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• pp.76-101
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• 2021

This paper analyzes two cases of space tokenization, Meridio and QuantmRE, to explore the potential of tokenization as a new means of space financialization. Space tokenization is based on blockchain technology and security token offering (STO). Although some financial geographers noted the possible impact of blockchain technology on space financialization, it has not been examined in depth. Therefore, this paper demonstrates space tokenization cases in detail. Meridio and QuantmRE suggest financial structures that convert space into tokens based on fractional ownership transactions. QuantmRE, specifically, allows a homeowner to secure cash without either debt or ownership relinquishment through sales of tokenized home equity. As this method takes a form of sale transaction rather than a loan, it enables financial institutions to circumvent strengthened regulation on loans after the 2008 global financial crisis. Moreover, even "house poor" households, who own houses but lack cash due to excessive loans, can cash out from their properties through QuantmRE. As such, space tokenization enables financial institutions to overcome constrained conditions after the global financial crisis, thereby reproducing space financialization. Space tokenization also has the potential to geographically expand space financialization through stimulating investment in the depressed housing market.

• 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.

• The Journal of Bigdata
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• v.6 no.1
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• pp.91-113
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• 2021

Despite the influence of real estate in the Korean asset market, it is not easy to predict market trends, and among them, apartments are not easy to predict because they are both residential spaces and contain investment properties. Factors affecting apartment prices vary and regional characteristics should also be considered. This study was conducted to compare the factors and characteristics that affect apartment prices in Seoul as a whole, 3 Gangnam districts, Nowon, Dobong, Gangbuk, Geumcheon, Gwanak and Guro districts and to understand the possibility of price prediction based on this. The analysis used machine learning algorithms such as neural networks, CHAID, linear regression, and random forests. The most important factor affecting the average selling price of all apartments in Seoul was the government's policy element, and easing policies such as easing transaction regulations and easing financial regulations were highly influential. In the case of the three Gangnam districts, the policy influence was low, and in the case of Gangnam-gu District, housing supply was the most important factor. On the other hand, 6 mid-lower-level districts saw government policies act as important variables and were commonly influenced by financial regulatory policies.