• The Transactions of the Korea Information Processing Society
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• v.13 no.5
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• pp.209-216
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• 2024

Real estate market prices are determined by various factors, including macroeconomic variables, as well as the influence of a variety of unstructured text data such as news articles and social media. News articles are a crucial factor in predicting real estate transaction prices as they reflect the economic sentiment of the public. This study utilizes sentiment analysis on news articles to generate a News Sentiment Index score, which is then seamlessly integrated into a real estate price prediction model. To calculate the sentiment index, the content of the articles is first summarized. Then, using AI, the summaries are categorized into positive, negative, and neutral sentiments, and a total score is calculated. This score is then applied to the real estate price prediction model. The models used for real estate price prediction include the Multi-head attention LSTM model and the Vector Auto Regression model. The LSTM prediction model, without applying the News Sentiment Index (NSI), showed Root Mean Square Error (RMSE) values of 0.60, 0.872, and 1.117 for the 1-month, 2-month, and 3-month forecasts, respectively. With the NSI applied, the RMSE values were reduced to 0.40, 0.724, and 1.03 for the same forecast periods. Similarly, the VAR prediction model without the NSI showed RMSE values of 1.6484, 0.6254, and 0.9220 for the 1-month, 2-month, and 3-month forecasts, respectively, while applying the NSI led to RMSE values of 1.1315, 0.3413, and 1.6227 for these periods. These results demonstrate the effectiveness of the proposed model in predicting apartment transaction price index and its ability to forecast real estate market price fluctuations that reflect socio-economic trends.

• Communications for Statistical Applications and Methods
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• v.18 no.1
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• pp.23-34
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• 2011

Property auctions have become a new method for real estate investment because the property auction market grows in tandem with the growth of the real estate market. This study focused on the statistical model for predicting bid price rates which is the main index for participants in the real estate auction market. For estimating the monthly bid price rate, we proposed a new method to make up for the mean of regions and terms as well as to reduce the prediction error using a decision tree analysis. We also proposed a linear regression model to predict a bid price rate for individual auction property. We applied the proposed model to apartment auction property and tried to predict the bid price rate as well as categorize individual auction property into an auction grade.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.47-53
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• 2021

With increasing interest in the 4th industrial revolution, data-driven scientific methodologies have developed. However, there are limitations of data collection in the real estate field of research. In addition, as the public becomes more knowledgeable about the real estate market, the qualitative sentiment comes to play a bigger role in the real estate market. Therefore, we propose a method to collect quantitative data that reflects sentiment using text mining and k-means algorithms, rather than the existing source data, and to predict the direction of housing index through artificial neural network learning based on the collected data. Data from 2012 to 2019 is set as the training period and 2020 as the prediction period. It is expected that this study will contribute to the utilization of scientific methods such as artificial neural networks rather than the use of the classical methodology for real estate market participants in their decision making process.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.256-263
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• 2021

This paper studies the problems and improvements of government real estate policies. Moon Jae-in government shifted toward regulation and pledge to curb the tax imposed by speculators. It strengthened regulations on reconstruction and bank loans rather than supply, and raised capital gains taxes. As the government implemented measures, emphasizing political logic rather than the economy, the market is unstable and the economy is in a recession. Land has increased the vicious cycle of problems due to population growth, industrialization, urbanization, and wealth growth. Mis-established land policies not only accelerate land prices, but also accelerate the use of disordered land and lead to disruptions in the trading order. In addition, real estate is so difficult to recover from the land problem that it is difficult to contain water that has been spilled once. This is called the irreversible nature of land. Once the land price rises, it is difficult to regain control and reckless development leads to the destruction of the ecosystem, making it difficult to return. This is why such a complex real estate issue should not be implemented as if it were a punishment in a short period of time with government policies. This paper aims to examine the problems of real estate policies and to examine ways to improve them.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.38-50
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• 2020

The purpose of this study is to identify the risks to financial institutions in terms of expanding potential risks due to the deferral of exposure, by identifying the structures in which real estate finance and financial institutions affect real estate prices at low interest rates. To this end, real estate financing is categorized according to the method of financing and the type of value measurement from a risk management perspective and analyzed for each case. As a result of analysis, in the case of profitable real estate, the rate of real estate is increased by directly decreasing the cap rate and directly affecting the fair value calculation method. In the case of non-profitable real estate, the real estate price is increased by expanding the leverage width of investors or financial institutions. Through the analysis of this case, the continuous increase in real estate prices over the past 10 years has the potential to prevent financial institutions from losing under the circumstances such as the growth of real estate finance due to the advancement of the financial market and the continued low interest rate trend that has continued for 10 years. It is judged that the deferred delay is part of the cause, which leads to an increase in the risk to financial institutions.

• Korean System Dynamics Review
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• v.3 no.1
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• pp.43-60
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• 2002

This paper describes the forecast of wholesale price in competitive Korean electricity market using the system dynamics approach. The system dynamics concepts have been implemented with the Ithink software. This software facilitates the development of stock and flow model with information feedback. Using this model, the future wholesale electricity price can be computed hour by hour, quarterly, and yearly. This model also gives the energy planner the opportunity to create different scenarios for the future of deregulated wholesale markets in Korea. Also It will lead to increased understanding of competitive wholesale market as a complex, dynamic system. Research results show that the plant construction appeared in waves of boom and bust in Korean electricity market like real estate construction. That is, the Korea wholesale market's new power plants and the market price will appear the Boom and Bust cycle. It is very similar behavior as real estate industry. In case of consideration of DSM program, The DSM savings lead to a somewhat different timing of the booms in construction and of price spikes. But the DSM programs do not eliminated the fundamental dynamics of the boom and bust. And the wholesale price is maintained at the lower level compared to the case of without DSM program. However, the unexpected result is found that due to the lower market price, Investor make significantly less investment in new CCs, which leads to the higher wholesale price after 2010. It suggests that the DSM Policy must be implemented with the dynamics of competitive Electricity Market.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1073-1080
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• 2013

Owing to 88 Olympic, social atmosphere changed to more freely and abundant liquidity, which caused by trade surplus, had led to the surge in real estate prices. Accordingly, The Roh Taewoo government announced the construction of five new towns, Bun-dang, Il-san etc. The Kim Youngsam government had dramatically enhanced the transparency of transactions on real estate field by introducing real-name transaction system. Whereas the Kim Daejung government carried out real estate stimulus package to early recovery from Asian financial cirsis. But, the Roh Muhyeon government conducted strongly suppressing polices. This report want to testify governments' real estate polices and their effectiveness on the real estate market after '90s using VAR model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.83-88
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• 2022

The purpose of this study is to present an analysis and implications for the metaverse-based virtual real estate transaction service. Through blockchain-based technology and metaverse, the world we live in is expanding naturally. Therefore, changes in the environment and perceptions of market participants are also very important factors. The concept and thinking about the existing asset value change and investment are also changing. This means that you can generate profits through value and investment in intangible assets. The service user aspect is a case of investing in the future value of virtual real estate that if more users participate rather than the present value, the principle of supply and demand will be applied to increase the number of consumers and the price will naturally rise according to the principle of scarcity. The service provider provides a technical platform for the service to directly transact the portion of the virtual area considered of interest directly through the virtual real estate purchase business. As the number of participants increases as well as funds and transaction fees, various revenue models such as advertisements can be discovered and provided. It plays the role of providing jobs and information through new services. As a stakeholder, governments can exploit the emergence of new technologies and products to create people and services and secure economic benefits. Of course, various institutional supports should be provided so that new services can settle in the market while mitigating risk factors. This study is meaningful in that it contributes to the establishment of a domestic metaverse-based environment and related research and is utilized in the study of virtual space real estate services.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.267-277
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• 2020

The present research evaluates the public engagement approach in various project stages. Hong Kong had long been criticized as top-down and executive-led jurisdiction by overlooking the importance of cultural heritage and public concerns on public projects. It was suggested to the government to engage public and provide sufficient public consultation. Thereby, the government announced a series of revitalization and conversion measures in Policy Address in 2008. To carry out the measures, there were voices, because of diverse and sometimes conflicting interests, over the effect of revitalization project. On the other hand, studies reveal that there are benefits of revitalization and enhancement of public engagement approach. In pursuit of the subject, the present research aims at studying the Central Market as a case study pilot project. In October 2009, the Policy Address announced that the Central Market be revitalized. Tasked to implement the project, Urban Renewal Authority (URA) continued to adopt the people-oriented approach as the guiding principle in its core business and in heritage preservation and revitalization so as to create a sustainable development. Between government and the public, URA acts as a bridge for communication. As between URA and the public, URA conducted public consultation, set up an ad-hoc committee in January 2016 to be in charge of the project and will continuously inform the government and public with the updates and project progress. The main objectives of the present research are to assess the advantages and challenges in different stages of public engagement approach, to evaluate the engagement system, to give a comprehensive view for participation of stakeholders, and to find out effective strategies to enhance civil engagement. Research was achieved through interviews to key persons in the project, questionnaire that was distributed to community and experts in the field. Case Study of the Central Market was studied and investigated using different sources, such as newspapers, journals, etc, to evaluate the degree of public engagement in the project. Both detailed qualitative methodological approaches of interview, questionnaire, and case study, act as a synergy to demonstrate the research objectives and provide the comprehensive perceptions on the revitalization project. The results show that public participants in revitalized project have generated considerable value enhancements to social-cultural, environmental, political and economic aspect. This study provides valuable insights that the public participation can make positive contribution to sustainability in the city. The findings indicate that no any single system is flawless therefore seeking both public opinions and professional advices are also important as a comprehensive approach to achieve higher sustainability of the building.

• Information Systems Review
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• v.18 no.3
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• pp.97-110
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• 2016

Real estate brokerage app service is an emerging online-to-offline (O2O) business model. This study analyze the relationship between the satisfaction and reuse of real estate app services through a survey of experienced users of the application. The results show that "ease of use" and "usefulness" of the online app service positively affect customer satisfaction and eventually affects reuse. Moreover, ease of use and usefulness of the offline brokerage introduced by the application positively affects customer satisfaction and eventually affects reuse too. One meaningful finding is the stronger impact of usefulness on customer satisfaction than that of ease of use in both online and offline situations. This finding implies that the value of usefulness is bigger than that of ease of use because of users who purposely use the application to find relevant real estates. The effect of online customer satisfaction on reuse is slightly higher than that of offline. This finding suggests that need to develop a strategy for online applications that focuses on enhancing the usefulness of real estate brokerage app services in the O2O market.