• Proceedings of the Korean Information Science Society Conference
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• 2000.10c
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• pp.464-466
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• 2000

인터넷의 발전에 따라 전자상거래의 기술적인 중요성이 한층 높아지고 있다. 최근 부동산 전문 쇼핑몰이 증가하고 있는 추세이다. 그러나 기존 부동산 쇼핑몰은 단순한 검색 수준의 게시판 형태로 결과를 보여주고 있는 문제점이 있다. 본 논문은 기존의 부동산 쇼핑몰들이 갖고 있는 지능화 자동화의 부족과 가격 중심의 거래라는 문제점을 극복하기 위해 부동산 거래과정에 참여하는 당사자들이 제시한 요구조건과 우선 순위를 절충할 수 있는 기능을 가진 알고리즘과 지능화와 자동화를 가진 에이전트를 이용해 부동산 거래를 위한 우선 순위 기반 에이전트 시스템을 제안하고, 이 알고리즘을 이용한 시스템을 연구하였다.

• Land and Housing Review
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• v.14 no.3
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• pp.55-75
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• 2023

Based on prior studies on real estate policy, tax policy, and financial policy, this study examined how tax policy and financial policy affected real estate prices using monthly data from January 2014 to December 2021. We performed a VAR model using unit root tests, cointegration tests, as well as conducted impulse response analysis and variance decomposition analysis. The results are as follows. First, the tax regulation index and the financial regulation index had no discernible impact on housing prices. Specifically, a one-sided stabilizing regulatory policy was ineffective and, instead, led to unintended side effects, such as price increases resulting from reduced transaction volume. Secondly, mortgage rates had a negative impact on the housing sale price index. In other words, an increase in interest rates might led to a decrease in housing prices. Thirdly, an increase in the transfer difference, which involves capital gains tax, has a positive effect on housing prices. This led to rising housing prices because the transfer taxes were shifted to buyers, causing them to hesitate to make purchases due to the increased tax burden. Fourthly, both acquisition taxes and mortgage loans had relatively little impact on housing prices.

• Korea Real Estate Review
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• v.28 no.1
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• pp.65-77
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• 2018

This paper analyzes the redemption risk of renters by estimating the LTV and CoLTV with finance market big data (individual credit information) and housing market big data (actual housing transaction data). The analysis showed that when using LTV, the redemption risk was higher in the case of the monthly renter than of the chonsei renter. On the other hand, when using CoLTV, the chonsei renter had a higher redemption risk than the monthly renter. This implies that there is a need to activate a guarantee system, such as risk management using the CoLTV index and the chonsei deposit return guarantee because it is possible for renters to experience losses on their chonsei deposits due to the higher redemption risk. Another implication is that the risk manager should consider the individual characteristics of renters because of the different effects of the redemption risk stemming from the characteristics of the rental contract and the personal characteristics of the renters. CoLTV was just a concept until this study calculated it using housing big data and actual housing transaction information. It helps identify the redemption risk through the characteristics of renters and their contracts.

• International Journal of Advanced Culture Technology
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• v.8 no.4
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• pp.271-278
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• 2020

Modern financial services go beyond the stage of internet banking, and new concepts of financial transactions such as Internet of Things, mobile banking, electronic payments, and fintech have emerged. As a result, banks are less influential in financial transactions, and changes are being demanded. In the present era, the basic business of banks has decreased, and it is transforming into a space where both consumer finance work and reside. The bank office stands for the brand image of the bank, and it is represented by trust with customers in the basic business of financial transactions, and the rise in real estate value is a natural social phenomenon due to the nature of the location and location of real estate owned by the bank. The business method and space of the bank office that meets the new paradigm of the modern society is an inefficient space only for the convenience and rest of consumers, but it must be used as a variety of spaces suitable for the region to increase the functional value of the bank office. Through this study, as a convenience space for consumers, various service facilities should be introduced to understand the characteristics of the region as a convenience space for consumers, and various service facilities should be introduced to meet the needs of consumers, and the bank office should be improved as a complex service space for local residents.

• Knowledge Management Research
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• v.22 no.2
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• pp.289-300
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• 2021

Proptech, which has applied information technology to the real estate market, is leading real estate transaction innovation by presenting various value creation models. This study categorizes and understands values that are created and shared in proptech-based businesses, and develops evaluation data that reflects the relative importance of individual value areas. To this end, the dimension of value creation of proptech was hierarchically constructed, and the degree of relative value creation of the sub-industries of the proptech industry was evaluated. In order to grasp the relative importance of the proposed indicators, AHP analysis was conducted for industry and academic experts. In the first stage, intangible values, relational values, and advanced values were presented. It was derived as weights between indicators through two-way comparison. This study aims to improve and develop the value-creation capability of the entire Korean proptech ecosystem in the future by evaluating the value-created competence of each sector of the proptech industry.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.717-729
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• 2020

As the environmental pollution problem in modern society is rapidly changing with industrialization, the environmental pollution problem has a direct or indirect effect on various fields. In particular, heavy industry pollutants can be a significant variable in site selection and realestate value. Therefore, this study is based on transaction data of 13apartment complexes in Maanshan City, a representative steel city in China, and uses the Hedonic Price Model to study the effect on real estate prices, mainly on heavy industry pollution during environmental pollution. The conclusion shows that the farther away from the source of pollution, the higher values are.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.81-94
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• 2022

Real estate and artworks were considered challenging investment targets for individual investors because of their relatively high average transaction price despite their long investment history. Recently, the so-called fractional investment, generally known as investing in a share of the ownership right for real-life assets, etc., and most investors perceive that they actually own a piece (fraction) of the ownership right through their investments, is gaining popularity. Founded in 2016, Musicow started the first service that allows users to invest in copyright fees related to music distribution. Using the LSTM algorithm, one of the deep learning algorithms, this research predict the price of right to participate in copyright fees traded in Musicow. In addition to variables related to claims such as transfer price, transaction volume of claims, and copyright fees, comprehensive indicators indicating the market conditions for music copyright fees participation, exchange rates reflecting economic conditions, KTB interest rates, and Korea Composite Stock Index were also used as variables. As a result, it was confirmed that the LSTM algorithm accurately predicts the transaction price even in the case of fractional investment which has a relatively low transaction volume.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.59-76
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• 2023

Since the COVID-19 era, the rise in apartment prices has been unconventional. In this uncertain real estate market, price prediction research is very important. In this paper, a model is created to predict the actual transaction price of future apartments after building a vast data set of 870,000 from 2015 to 2020 through data collection and crawling on various real estate sites and collecting as many variables as possible. This study first solved the multicollinearity problem by removing and combining variables. After that, a total of five variable selection algorithms were used to extract meaningful independent variables, such as Forward Selection, Backward Elimination, Stepwise Selection, L1 Regulation, and Principal Component Analysis(PCA). In addition, a total of four machine learning and deep learning algorithms were used for deep neural network(DNN), XGBoost, CatBoost, and Linear Regression to learn the model after hyperparameter optimization and compare predictive power between models. In the additional experiment, the experiment was conducted while changing the number of nodes and layers of the DNN to find the most appropriate number of nodes and layers. In conclusion, as a model with the best performance, the actual transaction price of apartments in 2021 was predicted and compared with the actual data in 2021. Through this, I am confident that machine learning and deep learning will help investors make the right decisions when purchasing homes in various economic situations.

• The Journal of Industrial Distribution & Business
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• v.9 no.6
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• pp.77-85
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• 2018

Purpose - The purpose of this study is to subdivide trade transaction-centered structure in a logistics/distribution industry system to apply blockchain, to establish and resolve with which types of technology, and to provide policy direction of government institution and technology to apply blockchain in this kind of industry. Research design, data, and methodology - This study was conducted with previous researches centered on cases applied in various industry sectors on the basis of blockchain technology. Results - General fields of blockchain application include digital contents distribution, IoT platform, e-Commerce, real-estate transaction, decentralized app. development(storage), certification service, smart contract, P2P network infrastructure, publication/storage of public documents, smart voting, money exchange, payment/settlement, banking security platform, actual asset storage, stock transaction and crowd funding. Blockchain is being applied in various fields home and abroad and its application cases can be explained in the banking industry, public sector, e-Commerce, medical industry, distribution and supply chain management, copyright protection. As examined in the blockchain application cases, it is expected to establish blockchain that can secure safety through distributed ledger in trade transaction because blockchain is established and applied in various sectors of industries home and abroad. Parties concerned of trade transaction can secure visibility even in interrupted specific section when they provide it as a base for distributed ledger application in trade and establish trade transaction model by applying blockchain. In case of interrupted specific section by using distributed ledger, blockchain model of trade transaction needs to be formed to make it possible for parties concerned involved in trade transaction to secure visibility and real-time tracking. Additionally, management should be possible from the time of contract until payment, freight transfer to buyers through land, air and maritime transportation. Conclusions - In order to boost blockchain-based logistics/distribution industry, the government, institutionally, needs to back up adding legal plan of shipping, logistics and distribution, reviewing standardization of electronic switching system and coming up with blockchain-based industrial road maps. In addition, the government, technologically, has to support R&D for integration with other high technology, standardization of distribution industry's blockchain technology and manpower training to expand technology development.

• The Journal of Society for e-Business Studies
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• v.22 no.1
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• pp.51-64
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• 2017

After Bitcoin was proposed by Satoshi Nakamoto in 2009, studies have been carried out to apply the Block Chain technology in various environment, which was applied as a distributed transaction of Bitcoin. Smart contracts, voting and proof of ownership of digital contents are typical applications of Block Chain. They used the feature that it is impossible to modify or delete once recorded facts. They also applied to prove relevant facts and to provide data integrity. The applied cases are mainly made in an environment where the data should or could be open to the public, and they have been proposed as solutions to solve the problems occurred in relations. This fact has led to the attention that Block Chain can be applied as a good alternative in similar circumstances. In this study, real estate market service was selected to expand the application range of Block Chain. Although there are about 250 applications and web services in total, the satisfaction is not high due to false offerings. Thus we propose a countermeasure against the problem by applying the Block Chain to the real estate market service, and investigate the research direction of the Block Chain in the future market.