• Spatial Information Research
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• v.10 no.2
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• pp.215-232
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• 2002

Variables representing neighborhood quality should be included in hedonic price models to control lfor the influences of negative or positive externalities from the quality of neighborhood on urban housing prices. This study proposes a GIS-based method to effectively measure the neighborhood quality variable when data on the neighborhood quality are aggregated by census sub area. This study also tests the superiority of the proposed neighborhood quality variable created by intensive use of GIS operations to a neighborhood variable not based on GIS operations in explaining the housing price variations by using Seoul＇s apartment sales data. The results from this study show that the neighborhood quality variable based on GIS-based operations shows better performance in explaining the urban housing price variations in Seoul＇s housing market. The implication from the results is that the potentials of GIS-based spatial operations in creating neighborhood quality variables should be well acknowledged by the researchers in the area of urban housing market study and GIS-based spatial operations should be more actively applied to generate better neighborhood quality variables for hedonic price models.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.100-103
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• 2016

This Study is focused on hedonic model study for retargeting advertising Based air inteface using useful information. many research related to the existing Internet of things, relatively not many study for effective advertising model based air inteface. So, this study is designed more information, fun, interactive advertising model based air inteface. therefore, result of this study show that implication to produce advertising based air inteface provides a practical guide.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.3
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• pp.67-81
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• 2006

The present study suggests an analytical method to overcome the spatial problems that traditional hedonic methods have. The concept of overlapping neighborhoods is introduced in order to solve the problems of global parameter estimate methods that treat the whole city by the gross. Moreover, a 3rd party program for the tight coupling of GIS and statistics is developed in order to explore hedonic methods efficiently. By using these, this study analyses the spatial variation of location variables that affect the real estate price. The results show that the influences of urban centers do not reach to the whole city, but only to the catchment areas of them. And the coefficients of location variables are different depending on the space. The tight coupling of GIS and statistics offers a powerful tool in analysing the real estate price efficiently.

• Journal of the Korean Geographical Society
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• v.49 no.6
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• pp.917-934
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• 2014

Geographically weighted regression(GWR) model has been widely used to estimate spatially heterogeneous real estate prices. The GWR model, however, has some limitations of the selection of different price determinants over space and the restricted number of observations for local estimation. Alternatively, the geographically weighted LASSO(GWL) model has been recently introduced and received a growing interest. In this paper, we attempt to explore various local price determinants for the real estate by utilizing the GWL and its applicability to forecasting the real estate price. To do this, we developed the three hedonic models of OLS, GWR, and GWL focusing on the sales price of apartments in Seoul and compared those models in terms of model fit, prediction, and multicollinearity. As a result, local models appeared to be better than the global OLS on the whole, and in particular, the GWL appeared to be more explanatory and predictable than other models. Moreover, the GWL enabled to provide spatially different sets of price determinants which no multicollinearity exists. The GWL helps select the significant sets of independent variables from a high dimensional dataset, and hence will be a useful technique for large and complex spatial big data.

• Spatial Information Research
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• v.16 no.4
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• pp.489-497
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• 2008

Currently, GIS has been widely used in the hedonic analyses of urban apartment housing markets in Korea. In those analyses, the apartment complexes are typically represented as the points or the polygons on the GIS maps and the location variables of the analyses are measured based on the points or the polygons. In this study, the relative performance of the point based approach and the polygon based approach in a GIS based hedonic analysis was compared using the apartment housing market data from the north eastern part of the city of Seoul and Davidson and MacKinnon Test. The results from this study indicate two things. First, two approaches can produce substantially different results in a hedonic price model estimation. Second, the polygon based approach produces a hedonic price model which explains the price variations better than the point based approach. These findings suggest that Korean researchers who are interested in improving quality of hedonic price model estimations and use GIS to measure the location variables for hedonic price models should consider using the polygon based approach with the point based approach. This is because the polygon based approach can produce the location variables with the shortest straight line distances and can explain the housing price variations well.

• Environmental and Resource Economics Review
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• v.11 no.4
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• pp.707-722
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• 2002

본 연구는 헤도닉가격기법과 비교정태분석을 사용하여 휘발유가격에 대한 자동차의 연료효율성과 속성의 수요탄력성을 추정한 것이다. 탄력성을 추정하는 데에는 휘발유가격에 대한 장기간의 시계열자료 대신 분석의 기준년도인 2001년의 평균휘발유가격이 사용되었으며, 그리고 2001년에 한국에서 새로 출시된 110개 자동차 모델에 대한 자료가 이용되었다. 분석의 대상이 되는 자동차의 속성으로는 디자인, 실내공간의 넓이, 엔진 배기량, 장착가능한 편의장치, 그리고 연비 등을 포함시켰다. 휘발유가격에 대한 연료효율성의 장기적인 수요탄력성은 0.366으로 추정되었다. 그 외 속성들의 수요탄력성도 비탄력적인 것으로 도출되었다. 따라서, 휘발유가격은 자동차의 속성들과 연료효율성의 소비에 큰 영향을 미치지 않는 것으로 해석할 수 있다.

• Journal of the Korean Geographical Society
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• v.39 no.6 s.105
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• pp.907-921
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• 2004

Lots of characteristics such as dwelling, neighborhood, and accessibility characteristics affect to the housevalue. Many researches have been done to identify values of each characteristic using hedonic technique. However, there is a limit to identify interaction of each characteristic and variation of each characteristic among the accessibility context. This paper has implemented the Expansion Method research paradigm to model the housevalue determination process in the city of Seoul. The findings of this paper have revealed the presence of contextual variations in the housevalue determination process. The initial model for housevalue reveals that as $F_1$ increases (i.e., larger the number of rooms/bathrooms, larger parking space) and/or $F_2$ increases (i.e., higher owner occupied housing units, higher apartment housing units) and/or $F_3$ increases, (i.e., higher the ratio of higher than college graduated households, 8 school zone, older housing units) the estimated housevalue increases. However, the above relationships drift across their respective contexts. The houses which have negative $F_1$ value, the housevalue does not fluctuate according to the distance to the city center or subcenters. However, the houses which have positive $F_1$ value, the closer to the subcenters or shorter to the river, the higher the estimated housevalues. On the other hand, in areas far from the subcenters, the estimated housevalues does not fluctuate much according to the corresponding $F_2$ level. In areas close to the subcenters, the estimated housevalues vary tremendously according to the $F_2$ value. In the residual analysis, it is revealed that large apartment which are located in Kangnam, IchongDong, MokDong are underestimated. This paper has contributed to our understanding of the housevalue determination process by providing an alternative conceptualization to the traditional approach.

• Land and Housing Review
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• v.14 no.3
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• pp.37-53
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• 2023

This study conducted an empirical analysis of how different types of living retail businesses affected housing prices during the COVID-19 pandemic, with a particular focus on both global and local time series effects. The main findings are three folds: First, from a global perspective, the study discovered that the presence of living retail businesses had a significant impact on prices of nearby apartment, varying according to their type. Secondly, the impact of COVID-19 on the retail industry varied depending on the type of business. Thirdly, when viewed from a local standpoint, the impact of the retail business sector on apartment prices due to COVID-19 pandemic was substantial, varying across regions and business types. This implies that external shocks like COVID-19 have the potential to alter the role and perception of living retail businesses. In light of this, the study has put forth policy implications aimed at mitigating the adverse effects of living retail businesses and enhancing residential quality.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.3
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• pp.101-115
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• 2009

The prompt recovery of housing market in Korea became the national task, for which tools that can analyze the influence that changing situation of housing market and new policy may have on the housing market needs to be developed. Thus, this research intends to develop Multi-Agent Housing Market Model and simulation system in Jinju City as a study area. Analyzing the local housing market of Jinju City, then multi-agent model of housing market that consolidates 3 sub-models, house choice model, hedonic model of house price and location choice model is developed. Moreover in order to develop simulation system the model is programmed in the virtual space of which the size is $150{\times}100$ cell including physical shape of city such as road, urban facilities, land use, etc. With the system, simulations are performed to confirm the impact of urban development on the pattern of residential location. As a result, it is found that the residential location can not be easily induced when only road, commercial and convenient facilities are supplied. However, it is also found that since supplying green results in very many residences, arrangement of infrastructure and environmental factor should be considered at the same time for urban development. As conclusion, it is confirmed that the model and simulation system developed in this research smoothly works to be utilized for the analysis of diverse policy experiment and housing market.