• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.95-118
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• 2017

Recent centrally the downtown area, the transaction between the row housing and multiplex housing is activated and platform services such as Zigbang and Dabang are growing. The row housing and multiplex housing is a blind spot for real estate information. Because there is a social problem, due to the change in market size and information asymmetry due to changes in demand. Also, the 5 or 25 districts used by the Seoul Metropolitan Government or the Korean Appraisal Board(hereafter, KAB) were established within the administrative boundaries and used in existing real estate studies. This is not a district classification for real estate researches because it is zoned urban planning. Based on the existing study, this study found that the city needs to reset the Seoul Metropolitan Government's spatial structure in estimating future housing prices. So, This study attempted to classify the area without spatial heterogeneity by the reflected the property price characteristics of row housing and Multiplex housing. In other words, There has been a problem that an inefficient side has arisen due to the simple division by the existing administrative district. Therefore, this study aims to cluster Seoul as a new area for more efficient real estate analysis. This study was applied to the hedonic model based on the real transactions price data of row housing and multiplex housing. And the K-Means Clustering algorithm was used to cluster the spatial structure of Seoul. In this study, data onto real transactions price of the Seoul Row housing and Multiplex Housing from January 2014 to December 2016, and the official land value of 2016 was used and it provided by Ministry of Land, Infrastructure and Transport(hereafter, MOLIT). Data preprocessing was followed by the following processing procedures: Removal of underground transaction, Price standardization per area, Removal of Real transaction case(above 5 and below -5). In this study, we analyzed data from 132,707 cases to 126,759 data through data preprocessing. The data analysis tool used the R program. After data preprocessing, data model was constructed. Priority, the K-means Clustering was performed. In addition, a regression analysis was conducted using Hedonic model and it was conducted a cosine similarity analysis. Based on the constructed data model, we clustered on the basis of the longitude and latitude of Seoul and conducted comparative analysis of existing area. The results of this study indicated that the goodness of fit of the model was above 75 % and the variables used for the Hedonic model were significant. In other words, 5 or 25 districts that is the area of the existing administrative area are divided into 16 districts. So, this study derived a clustering method of row housing and multiplex housing in Seoul using K-Means Clustering algorithm and hedonic model by the reflected the property price characteristics. Moreover, they presented academic and practical implications and presented the limitations of this study and the direction of future research. Academic implication has clustered by reflecting the property price characteristics in order to improve the problems of the areas used in the Seoul Metropolitan Government, KAB, and Existing Real Estate Research. Another academic implications are that apartments were the main study of existing real estate research, and has proposed a method of classifying area in Seoul using public information(i.e., real-data of MOLIT) of government 3.0. Practical implication is that it can be used as a basic data for real estate related research on row housing and multiplex housing. Another practical implications are that is expected the activation of row housing and multiplex housing research and, that is expected to increase the accuracy of the model of the actual transaction. The future research direction of this study involves conducting various analyses to overcome the limitations of the threshold and indicates the need for deeper research.

• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.2
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• pp.70-77
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• 2009

The purpose of this study is to evaluate the economic value of an urban landscape. The site of this study was Independence Park in Seoul. Before measuring economic valuation, an amount of view analysis was performed to learn the visual characteristics of the landscape. As a result, the green space ratio of the park is approximately 64%. This study estimates the intrinsic value of an urban landscape that might be included in housing prices using a hedonic price model. The hedonic price model is a statistical analysis that is often used to estimate intrinsic values of certain attributes of a product. The Box-Cox model was adopted as an analysis tool while the housing price for $3.3m^2$ was used as a dependent variable and housing and landscape features as independent variables. Results show that the value of the landscape of the Independence Park is approximately 2.2% of the housing market price. The Landscape variables of the park is the second most significant of the 8 variables. This shows that residents perceived the view of the urban landscape as one of the most significant factors in their living environment. The study also indicates that urban landscapes play important roles in improving quality of life and in influencing housing prices. The implication of the study can be said to be the potential of the urban landscape as a significant urban infrastructure. These results can be used to help make policy decisions to preserve and/or develop urban landscapes.

• 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.

• Journal of the Korean Geographical Society
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• v.48 no.2
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• pp.272-287
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• 2013

This paper describes the importance of selecting explanatory variables(e.g. land price determinants) in hedonic pricing models employed in predicting real estate price, and explores dynamics of the land price determinants over time. The City of Junju was chosen as the study area, and repeated measured price data of standard lots over 17 years were analyzed. We applied a three-level modeling approach to this data in consideration of its nested data structure and longitudinal characteristics. Main land price determinants we focused on are primarily based on items included in the standard comparison table of land price, which is an official hedonic pricing model used by Government to estimate land price for tax levy. Our result shows that the land price fluctuation over 17 years was not uniform over the whole study area with each neighborhood revealing different price trend, and as such warrants longitudinal model components. In addition, some of determinants previously recognized as important were proved insignificant. It was also found that significant determinants at a particular time point lost its power gradually over time and vice versa. It is expected that more accurate prediction of price would be possible when taken account for this dynamics of price determinants over time in applying hedonic pricing model method.

• Environmental and Resource Economics Review
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• v.28 no.1
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• pp.61-93
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• 2019

This study is to apply Hedonic Price Method in analyzing residents' preferences for three types of urban green space (UGS, rivers, urban parks, and forests) near the apartment complexes in Seoul. Based on hedonic price function estimation results, residents in Seoul preferred for the urban amenity that was provided by the view and accessibility (in terms of both within 10 minutes and distance) of rivers and urban parks near the apartment complexes, but not forests. The annual benefits calculated using the shadow prices are about 550~600 thousand won for the urban park views and about 800 thousand won for the accessibility, which is 2-3 times higher than river views and accessibility. On the other hand, forest views and accessibility did not have significant effects on apartment prices, except the view of Bukhan mountain for the residents of Gangbuk area. Based on the empirical results, Seoul residents' preferences for urban parks would have important implications for the urban park sunset program that will be initiated from July 2020.

• Journal of Korea Entertainment Industry Association
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• v.14 no.4
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• pp.91-104
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• 2020

In this study, the value of the medical resort was divided into hedonic value, hospitality value, safety and personal information protection value, and profitability value by exploring and typifying the successful cases and related services of the medical resort in order to provide the direction of development and policy implications of the medical resort for the medical tourism industry. For those who have used the medical resort, I wanted to verify the impact of the value of medical resort on perception of medical resort and its intention to use it. As a result of this study, it was found that hedonic value and hospitality value of medical resort have a strong influence on usefulness perception and well-being perception of medical resort, that safety and personal information protection value of medical resort was only affected by usefulness perception, and profit value of medical resort was only affected by well-being perception. In addition, the usefulness perception and well-being perception of medical resorts were shown to have an impact on the intention of using medical resorts, especially in the case of well-being perception of medical resorts. The above findings are meaningful in that they expanded the medical resort-related research area for the medical tourism industry and provided useful implications for the development of medical resorts that meet the convenience and needs of medical tourists.

• The Journal of Society for e-Business Studies
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• v.17 no.1
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• pp.1-21
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• 2012

Conventional studies on technology acceptance have focused on information technology for utilitarian value and hence based on 'theory of reasoned action'. Correspondingly, the studies depend on perceived usefulness and perceived ease of use as rational decision making elements. However, in ubiquitous society, innovative technologies are applied to non-task area, as well as task-oriented area. Therefore, users are more influenced by affective factors than cognitive factors in causing their usage intention. In line with those discussions, we cannot make sure that the conventional technology acceptance model could fully explain the current u-service acceptance phenomenon. Hence, to overcome the limitations of the prior technology acceptance studies, we propose an amended TAM which includes one hedonic factor and two factors on ubiquitous computing technology : ubiquity and intelligence.

• Journal of Environmental Policy
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• v.9 no.4
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• pp.103-123
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• 2010

Many former industrial cities such as Cleveland, Ohio are trying to transform their identities from blue-collar manufacturing centers to white-collar professional hubs. As a result, the re-use of land previously occupied by industrial firms has been on the rise as an important sustainable land-use strategy in the United States. Ohio's Cuyahoga County offers a Brownfield Redevelopment Fund to overcome the environmental barriers inherent in re-use in order to obtain full use of underutilized properties in the county. This study estimates externality effects of brownfield redevelopment projects (BRPs) on nearby housing sales prices in Cuyahoga County. Typical hedonic regression models that employ "difference-in-difference" techniques are used to compare proximal housing sale prices before and after the completion of BRPs.

• Korea Real Estate Review
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• v.24 no.1
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• pp.7-14
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• 2014

This study, as the temporal and spatial data for the real price apartment in Seoul from January 2006 to June 2013, empirically compared and analyzed the estimation result of apartment price using OLS by hedonic price model for the problem of space-time correlation, temporal autoregressive model (TAR) considering temporal effect, spatial autoregressive model (SAR) spatial effect and spatiotemporal autoregressive model (STAR) spatiotemporal effect. As a result, the adjusted R-square of STAR model was increased by 10% compared that of OLS model while the root mean squares error (RMSE) was decreased by 18%. Considering temporal and spatial effect, it is observed that the estimation of apartment price is more correct than the existing model. As the result of analyzing STAR model, the apartment price is affected as follows; area for apartment(-), years of apartment(-), dummy of low-rise(-), individual heating (-), city gas(-), dummy of reconstruction(+), stairs(+), size of complex(+). The results of other analysis method were the same. When estimating the price of real estate using STAR model, the government officials can improve policy efficiency and make reasonable investment based on the objective information by grasping trend of real estate market accurately.

• Korea Real Estate Review
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• v.27 no.4
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• pp.63-76
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• 2017

The purpose of this study is to analyze the effect of the results of a nationwide academic evaluation of middle schools and high schools on apartment prices in Ulsan City by using a hedonic pricing model. The results of the middle school and high school achievement test, the College Scholastic Ability Test (CSAT) score for high school, the national united evaluation score, and the number of successful applicants to prestigious universities have a significant effect on the apartment price formation with a positive relationship. In addition, different kinds of academic evaluation score have asymmetric effects on apartment price determination. The results of the high school achievement evaluation are more important than the results of the middle school achievement evaluation in the apartment price determination. Among the achievement evaluation results, the ratio of the students with the higher education level is more important than the ratio of the students with the lower basic education level. Furthermore, the CSAT score for Natural Sciences is more important than the CSAT score for the Humanities course.