• Journal of Construction Engineering and Project Management
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• v.7 no.2
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• pp.19-33
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• 2017

Various forms of procurement are open to companies when constructing new owner-occupied properties. The selection of a form of procurement is an important decision-making problem for companies and their Corporate Real Estate Management (CREM) departments. With this in mind, a decision support tool has been developed to optimise the outcome and success of company's proposed real estate development projects and is presented in this paper. This model can also be used for current real estate portfolios to optimise returns in the long term. In pursuit of this objective and in order to provide an academic basis for this study, decision-relevant goals and parameters were initially identified from the referenced literature used in our research. These were subsequently evaluated in a case study of a corporate development project and identified as specific decision criteria from the perspective of the CREM. The investigation identified 15 criteria that are relevant to the corporate decision-making process in procuring and/or developing property. A model for supporting and resolving decision-making problems of this type was derived from decision theory. In this paper, a decision-making tool is presented that takes into account all the decision criteria from the CREM point of view for the first time. This model should therefore serve as an aid in implementing the decision-making process for the development of real estate projects in a more structured and transparent manner.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.349-356
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• 2012

Entering the era of globalization, international real estate companies to advance into the country are increasing. And real estate transactions, the need for transparency and reliability are becoming even more. The alternative that real estate transactions in advance to avoid an accident is just an escrow system. Analysing the status and actual conditions of escrow in the country's real estate market and presenting the activation plans are as follows. First, the government should support building bulk service for real estate transactions. Second, tax benefits should be developed.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.549-556
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• 2020

Real estate markets play an essential role in the economic development of both developed and developing countries. Investment decisions in private real estate demand the consideration of several qualitative and quantitative criteria. Especially in Vietnam, demand for housing, apartments are rising which has resulted because of the migration from rural to urban areas. This study aims to determine the influencing factors of the real estate purchasing behavior and then recommend a grey Multi-Criteria Decision Making (MCDM) support model to evaluate real estate alternatives based on a numerical example in Vietnam. A set of essential criteria are identified based on experts' opinion, and the proposed determinants are initial investment, maintenance cost, prestige location, distance to interesting places, parking lot, public transportation, property condition, total area size, number of rooms, and neighbors. The subjective weights were obtained by using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) model, and the Grey Relational Analysis (GRA) technique is employed to prioritize and rank real estate alternatives. The results reveal that this approach can be useful to make purchasing decisions for many kinds of real estate property under uncertain business environments. These findings indicate that the presented hybrid model has advantages in granting flexibility to the preferences of decision makers.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.45-63
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• 2019

Until recently, most people have invested in a traditional portfolio consisting of stocks, bonds and real estates based on the three-division method of properties in Korea. However, this study analyzed the impact of the composition of a portfolio combining representative real estate indirect investment products such as Reits and real estate funds on the investment performance. For this purpose, the empirical analysis using the mean variance model, which is the most appropriate method for the portfolio composition, was used. For variables used in this study, mixed asset portfolios were classified into Portfolio A through Portfolio G depending on the composition of assets, and the price indices selected as Kospi, Krx bond, Reits Trus Y7, Hanwha-Lasal fund, and Office (Seoul). The results are as follows; first Portfolio D, which combined bonds, stocks, Reits and Real Estate funds, and Portfolio G, which added the office, the actual real estate, were shown to have the lowest risk. second, Portfolio B composed of bonds, stocks and Reits and Portfolio D with added real estate funds had the lowest risk while Portfolio F composed of bonds, stocks, offices and real estate funds, and Portfolio G with added Reits were the most profitable. As a result, it has been analyzed that it was more effective to compose a portfolio including Reits and real estate funds, which were real estate indirect investment products that eliminated the illiquidity limitation of real estates than real estates, the traditional three-division method of properties. Therefore, it is possible to minimize the risk of investors and reduce the cost of ownership of the real estate by solving the illiquidity problem that is the biggest disadvantage of the direct investment, In addition, it is considered that it is more necessary to reinvigorate the real estate indirect investment market where small amounts can be invested.

• The Journal of the Korea Contents Association
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• v.8 no.10
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• pp.129-141
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• 2008

Comprehensive real estate taxes needs to be improved so that it performs its intended functions by realizing fair taxation and stabilizing the price of real estate, and ultimately attains social justice in Korea. This study analyzed the current state of comprehensive real estate taxes through a questionnaire survey, and the results are summarized as follows. First, in the analysis of people's perception on the adequacy of the tax rate of comprehensive real estate taxes, those who owned a house worthy of 600 million won or a higher value as an object of real estate tax perceived the adequacy of the tax rate more negatively than those who owned a house of less than 600 million won. The same result was observed for comprehensive real estate taxes on lands. Second, in the analysis of the contribution of comprehensive real estate taxes to the accomplishment of policies, the respondents showed a high frequency of positive replies to some of policies related to comprehensive real estate taxes.

• Journal of Digital Convergence
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• v.16 no.9
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• pp.125-132
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• 2018

Despite the fact that corporate real estate ratio accounts for a considerable proportion of the assets, such researches and studies are lacking and there is not enough such policies to utilize real estate more effectively in Korea. In particular, after IFRS adoption, the owner and manager needs to utilize corporate real estate assets as the assets are revalued. In this study, we analyzed the relationship between corporate governance, corporate real estate holding policies and firm value based on financial data from 2010 to 2016. As a result of regression analysis, this study showed that more Dictatorship Portfolio, the higher proportion of corporate real estate holdings. Next, the higher proportion of corporate real estate holdings, the lower the firm value. This study suggests that corporate real estate is recognized an important factor and should have proper holding ratio. I will continue my research to show that the corporate holding policies are an important asset impact by verifying the mediating effect between corporate governance and firm value in the future.

• 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.

• The Journal of the Korea Contents Association
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• v.20 no.5
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• pp.585-594
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• 2020

After the launch of Jeju Special Self-Governing Province in 2006, a number of real estate development projects were carried out; the real estate industry has relatively largely grown as compared with other regions since 2011. This growth has slowed down in 2017, along with the increase of unsold houses and the short of its incoming population, causing its real estate market recession. This study analyzed the source of real estate industry growth in Jeju: either affected by national growth power or its regional competitiveness. This study applied Shift-Share Analysis and Growth Differential Analysis, by dividing the recovery period ('06~'10) and expansion period ('11~'16). According to the result, sales amount and the number of employees in the real estate industry in Jeju had grown in the recovery period based on the national growth power. Its regional competitiveness and stable industrial structure grew in the growth period. Development and subdividing of real estate contributed to the growth of the real estate industry in Jeju. On the other hand, management of real estate weakened its market.

• Korea Real Estate Review
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• v.27 no.3
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• pp.71-86
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• 2017

The purpose of this study was to apply the deep running method to real estate price index predicting and to compare it with the time series analysis method to test the possibility of its application to real estate market forecasting. Various real estate price indices were predicted using the DNN (deep neural networks) and LSTM (long short term memory networks) models, both of which draw on the deep learning method, and the ARIMA (autoregressive integrated moving average) model, which is based on the time seies analysis method. The results of the study showed the following. First, the predictive power of the deep learning method is superior to that of the time series analysis method. Second, among the deep learning models, the predictability of the DNN model is slightly superior to that of the LSTM model. Third, the deep learning method and the ARIMA model are the least reliable tools for predicting the housing sales prices index among the real estate price indices. Drawing on the deep learning method, it is hoped that this study will help enhance the accuracy in predicting the real estate market dynamics.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.163-180
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• 2022

Real estate data can be big data. Because the amount of real estate data is growing rapidly and real estate data interacts with various fields such as the economy, law, and crowd psychology, yet is structured with complex data layers. The existing Relational Database tends to show difficulty in handling various relationships for managing real estate big data, because it has a fixed schema and is only vertically extendable. In order to improve such limitations, this study constructs the real estate data in a Graph Database and verifies its usefulness. For the research method, we modeled various real estate data on MySQL, one of the most widely used Relational Databases, and Neo4j, one of the most widely used Graph Databases. Then, we collected real estate questions used in real life and selected 9 different questions to compare the query times on each Database. As a result, Neo4j showed constant performance even in queries with multiple JOIN statements with inferences to various relationships, whereas MySQL showed a rapid increase in its performance. According to this result, we have found out that a Graph Database such as Neo4j is more efficient for real estate big data with various relationships. We expect to use the real estate Graph Database in predicting real estate price factors and inquiring AI speakers for real estate.