• Korea Real Estate Review
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• v.28 no.1
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• pp.91-104
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• 2018

In this study, the occurrence and degree of herding behavior as a market participant behavior in a housing market were analyzed. For the analysis method, the actual sales price was applied in the CSAD (Cross-sectional Absolute Deviation) model, which has been used the most of late for herding behavior analysis. For the analysis contents, these were subdivided into region, elapsed year, size, and market condition to analyze the regionality and the internal and external factors. For the study results, first, there was no herding behavior in the entire region of Seoul. By region, herding behavior occurred in the downtown, southeast, and northwest regions, which coincided with the results of the precedent study (Ngene et al., 2017). Second, in the market analysis by elapsed year, herding behavior was captured in dilapidated dwellings. By size, herding behavior was observed in small-scale ($60m^2$ or less) apartments and in $85m^2$ or higher and less than $102m^2$ national housing units. Third, during the time of the global financial crisis, herding behavior was not observed in all the regions, whereas when the market situations were in a boom cycle, it was observed in the northwest region. These results suggest that there is a difference from the stock market, where in a period of recession, herding behavior occurs intensively with the expanding fear of incurring losses. This study is significant in that it analyzed the market participant behaviors in the behavioral economic aspects to better understand the abnormal phenomenon in a housing market, and in that it additionally provides a psychological factor - market participant behavior - in market analysis.

• 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.

• Journal of the Korean association of regional geographers
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• v.23 no.1
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• pp.106-117
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• 2017

Recently, urban regeneration is being actively promoted in Korea and among those Jeonju Hanok Village is the major project which is the most consistently promoted. For this, visitors of Jeonju Hanok Village are skyrocketing. However, due to this condition, various problems are occurring, especially about commercialization. In this regard, this study is to suggest management of the Jeonju Hanok Village and new orientation in the policy, by analyzing physical, economic, and social status due to urban regeneration for Jeonju Hanok Village which has lost its identity and been commercialized. For this, the study analyzed changes in land usage and real transaction price, SNS data. Firstly, in the physical analysis, the study realized that there is commercialization going around the main streets of Jeonju Hanok Village. Due to the rapid commercialization, living spaces for locals are replaced to commercial spaces for tourists, and the emigration of locals is caused by economic/environmental damages with the degradation of housing environments. Secondly, in the economic analysis, there was no gap in real transactions among streets in 2010 but has shown a valid gap in 2016. The traffic of tourists is heavy and the real transaction prices of streets that are adjacent to major tourist sights rose the most. Rising real transaction prices are a positive phenomenon in the aspect of the city regeneration but it is concerned that they can be perceived as investment subjects. Thirdly, in the social analysis, tourists are using commercial aspects more than historical or cultural sites, and have lots of interest on those. However, because there are also lots of opinions about the commercialization of Hanok Village, we think the plans which can establish the identity of Hanok Village should be prepared. The study has its meaning on analyzing reality based on the land usage, real transaction, SNS data and suggesting political implications.