• Journal of Cadastre & Land InformatiX
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• v.44 no.1
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• pp.195-212
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• 2014

This study was performed in order to contributing the influence factors in the real estate marketing strategy which largely affects the success of a real estate sale and development projects. Articles have to be concluded with the Influence factors of Satisfaction based on the type of Real Estate through PLS Regression Analysis. Building data was conducted by the target population specializing in the real estate sale and development business. Classification of real estate business classified by the way of the residential and non-residential parted. In the case of Housing type in the analysis result, the main factors were made by calculating the each factor such as brand trust, Strengthening the alliance and partnership, Traffic environment, Relaxing the requirements for a Real estate sales, Business presentation, Unsold benefits and Relaxing the requirements for payment. Otherwise, In the case of non-residential in the analysis result, the factors such as Relaxing the requirements for payment, Customer Orientation, living environment, Unsold benefits, Strengthening the alliance and partnership and communication terms made an influence to satisfaction.

• Journal of Information Technology Services
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• v.12 no.2
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• pp.73-84
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• 2013

The development of the information on the internet brought a lot of changes in the real estate market. Because the real estate has local distinctiveness and individuality household who want to move must to visit place for housing information. But now household use internet real estate information at every decision-moving step and that is able to reduce not only the cost of real estate information but also social benefit like $CO_2$ emissions reduction effect. In this study, I analyzed the effect of $CO_2$ emissions reduction with Seoul household residential mobility data when household take informations from internet real estate site. As increasing a single family who is good at internet service, the effect of $CO_2$ reduction from the development of the Internet real estate information has more increased.

• Korea Real Estate Review
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• v.27 no.3
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• pp.87-102
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• 2017

The purpose of this study was to compare the taxation equity of non-residential collective real estate based on its standard market prices set by National Tax Service and those for taxation set by the Ministry of Government Administration and Home Affairs with that of the apartment houses in Seoul, South Korea. The study findings were as follows. First, the analysis results of the standard market price rates of non-residential collective real estate pointed to a huge gap in the assessment rate (AR) of the taxation standards among the Gu offices. Second, there was a big coefficient of dispersion (COD) in the standard market prices of non-residential collective real estate, which confirmed the presence of horizontal inequity. Finally, there was regressive vertical inequity, which leads to the undervaluation of high-value assets, in the standard market prices of non-residential collective real estate. The evaluation of the standard market prices of non-residential collective real state should thus reflect the market prices and the addition and assessment of the land and buildings to achieve taxation equity. Based on these findings, it is hoped that this study will make a significant contribution to the improvement of the official announcement system for non-residential real estate based on real transactions during the shift to such system.

• The Journal of the Korea Contents Association
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• v.19 no.12
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• pp.535-545
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• 2019

If the real estate auction market indicators are relevant and meaningful, they can be meaningful information to the real estate market in connection with general real estate. The purpose of this study is to examine whether time-supply logic is applied in auction market by identifying time series correlations for the number of auctions, the auction rate, and the auction price rate, which are major indicators of real estate auction market. The real estate types were classified into three categories: residential real estate, land, and commercial real estate. The monthly time series of auctions in the metropolitan real estate were compiled for 96 months. Based on this data, the auction market model for each type was established and the mutual influences between the indicators were analyzed. As a result, the supply and demand indicators, the number of auctions and the auction rate, showed the nature of supply and demand according to the supply and demand logic of the market. However, the correlation was high for residential real estate and relatively low for commercial real estate. the auction rate has a long-term impact on price indicators, especially residential real estate, which is quantitatively explanatory and significant. The three auction-related indicators differ in degree, but there is a correlation, especially for residential real estate, which can be useful information for policy making.

• Journal of the Economic Geographical Society of Korea
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• v.22 no.4
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• pp.592-609
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• 2019

This study attempts to expand the leverage cycle theory using the subprime real estate investors. The leverage cycle theory has demonstrated asset price fluctuations irrelevant to changes in fundamentals through the restructuring of transaction composition centered on optimistic buyers. However, it needs to understand how this theory works in the depressed housing market with low-income residential regions to explain the geographic origins of the financial crisis. In the depressed housing market, the subprime real estate investors focused on low-income residential regions. Through this spatial focus, the low-income residential regions solely have real estate investor-oriented composition of new purchase transactions in the depressed housing market. The discovery of the subprime real estate investors as new actors lays the foundation for applying the leverage cycle theory to the depressed housing market which has been a underserved area for capital investment. This attempt illustrates how the geographical reinterpretation of an economic theory reestablishes spatio-temporal context of economic phenomena.

• The Journal of Industrial Distribution & Business
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• v.12 no.2
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• pp.41-52
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• 2021

Purpose: This study aims to provide implications for the government's housing supply policy by analyzing the factors that determine the type of real estate holding and household debt. This study started from the awareness that the determinants of household debt differ depending on the type of real estate holding. Research design, data and methodology: Real estate ownership type was classified and analyzed into 4 models: model 1 (1 household 1 house and self-resident), model 2 (1 household multiple real estate ownership and self-resident), model 3 (1 household 1 house and rent residence), model 4 (1 household holds a large number of real estate and rent residence). The analysis method used multiple regression analysis. The dependent variable was household total debt. As independent variables, household debt, annual gross household income, financial assets, real estate net assets, annual repayment, demographic & residential characteristics were used. Results: 1) Model 4 has the highest household debt and the highest gross income, Model 2 has the most real estate mortgage loans and real estate net asset, and Model 1 has the highest real estate mortgage payments. 2) The positive factor of common household debt determinants is real estate net assets, and the negative factor is financial assets. 3) It was the net assets of real estate that acted as a positive factor in common for the four models. In other words, the more financial assets, the less household debt. It was analyzed that the more net assets of real estate, the more household debt. The annual repayment of financial liabilities had no influence on household debt, while the annual repayment of loan liabilities and household debt had a positive relationship. Conclusions: 1) It is necessary to introduce benefits and systems that can increase the proportion of household financial asset. Specific alternatives include tax benefits and reduced fees for financial asset investment. 2) In the case where a homeless person prepares one house for one household, it is necessary to prepare various support measures according to the income level. The specific alternative is to give additional points for pre-sale or apply an interest rate cut incentive for mortgage loans.

• Korean Journal of Construction Engineering and Management
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• v.21 no.5
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• pp.29-37
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• 2020

This study analyzed the importance of factors according to the investor's perspective through a survey of residential real estate experts using AHP and fuzzy theory. Analysis results showed that rent, profitability, traffic accessibility, commercial and infrastructure, and financial regulation are important in common. By expert group, financial and credit groups cited profitability, rent, traffic accessibility, supply and tax benefits, construction and development groups cited traffic accessibility, rent, direct access, profitability, commercial area and infrastructure, and appraisal and evaluation groups cited rent, profitability, transportation accessibility, financial regulation and supply as the most important factors. This showed that it had a preference characteristic that was associated with work. In other words, it focuses most on the financial perspective in investment characteristics, and it values convenience such as accessibility to transportation and commercial districts and infrastructure as its location characteristics. In addition, it was found that easing financial regulations in the market is important to expand investment in real estate. This study aims to help the business feasibility analysis of residential property developers and rational decision-making of general investors who are consumers, taking into account the various perspectives of the expert group.

• Journal of Multimedia Information System
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• v.4 no.3
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• pp.151-156
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• 2017

As Internet services have spread centering on mobiles, diverse services used in everyday life have become mobile services. For humans, residential spaces have significant implications as physical and psychological environments. Therefore, being provided with accurate information on the room that must be sought to find out the residential space wanted by the user can be said to be an important element of real estate apps. However, when buying real estate, people prefer searching for information using mobiles and verifying the information by visiting the real estate firsthand due to increases in damage due to false offerings. This way approaches as inconvenience in cases where the buyer lives far away or if the conditions are not suitable. Therefore, in the present study, a 'room finding application using VR' was designed and implemented using virtual reality (VR) used for diverse purposes. VR is a technology that provides the user with the sense of presence as if the user is actually present in the space. It was used in the present study as a means to provide more accurate information. The use of the application designed and implemented in the present study is expected to reduce false offerings information at least slightly so that users can be provided with more accurate information on the real estate of interest.

• The Journal of the Korea Contents Association
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• v.18 no.3
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• pp.286-298
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• 2018

This study presents determinants of resettlement considering population, economy, residential environment, policy characteristic, proposes implications for increase of resettlement. The research method deducted determinants of resettlement by union groups using logistic regression, union members are divided to more 10 years group and under 10 years group focused on real estate ownership duration. The analysis results are summarized as follows. More 10 years group has higher age, neighborship, satisfaction about pre-sale price, inside region in redevelopment promotion project, satisfaction about increase of real estate price, the higher resettlement decision probability. Under 10 years group has higher satisfaction about increase of real estate price, satisfaction about pre-sale price, satisfaction about floor area ratio incentive, the higher resettlement decision probability. the political implications must be customized financial support considering economic situations and increase of asset value by real estate ownership duration.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.15-20
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• 2020

Recently, the real estate is of high interest. This is because real estate, which was considered only a residential environment in the past, is recognized as a stable investment target due to the ever-growing demand on it. In particular, in the case of the domestic market, despite the decrease in the number of people, the number of single-person households and the influx of people to large cities are accelerating, and real estate prices are rising sharply around the metropolitan area. Therefore, accurately predicting the prospects of the future real estate market becomes a very important issue not only for individual asset management but also for government policy establishment. In this paper, we developed a program to predict future real estate market prices by learning past real estate sales data using machine learning techniques. The data on the market price of real estate provided by the Korea Appraisal Board and the Ministry of Land, Infrastructure and Transport were used, and the average sales price forecast for 2022 by region is presented. The developed program is publicly available so that it could be used in various forms.