• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.281-293
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• 2020

Recently, large and small fires have been happening more often in Korea. Fire is one of the most frequent disasters along with traffic accidents in korean cities, and this frequency is closely related to the land use and the type of facilities. Therefore, in this study, the significance of fires was analyzed by considering land use, facility types, human and social factors and using 10 years of fire data in Jinju city. Based on this, OLS (Ordinary Least Square) regression analysis, SLM (Spatial Lag Model) and SEM (Spatial Error Model) using space weights, were compared and analyzed considering the location of the fire and each factor, then a statistical model with high suitability was presented. As a result, LISA analysis of spatial distribution patterns of fires in Jinju city was conducted, and it was proved that the frequency of fires was high in the order as follow, central commercial area, industrial area and residential area. Multiple regression analysis was performed by integrating demographic, social, and physical variables. Therefore, the three models were compared and analyzed by applying spatial weighting to the derived factors. As a result of the significance test, the spatial error model was analyzed to be the most significant. The facilities that have the highest correlation with fire occurrence were second type neighborhood facilities, followed by detached house, first type neighborhood facilities, number of households, and sales facilities. The results of this study are expected to be used as significant data to identify factors and manage fire safety in urban areas. Also, through the analysis of the standard deviation ellipsoid, the distribution characteristics of each facility in the residential area, industrial area, and central commercial area among the use areas were analyzed. In, the second type neighborhood facility with the highest fire risk was concentrated in the center. The results of these studies are expected to be used as useful data for identifying factors and managing fire safety in urban areas.

• Journal of the Korean Geographical Society
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• v.49 no.5
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• pp.690-704
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• 2014

Single family houses are the traditional & typical type of house in human history. But there had been little attention to single family houses in Korea so that there was little studies on single family houses. This study aimed to analyse price determinants of single family houses in Seoul, using Quantile Regression Analysis(QRA). Because single family houses has large levels of price, quantile regression analysis is more proper than Ordinary Least Square(OLS). The Results of analysis showed that, land coverage ratio, zoning, passed years, basement floor, hight of land, shape of land were important factors to single family houses price. The scale of effect of land coverage ratio to single family houses price was different to price levels of single family houses. And basement floor affected more negative effects to middle price, location and zoning had positive effects to high price single family houses. The degree of influence of determinants of single family houses price was deferent by region, KangBuk and KangNam. In KangNam, land coverage ratio and accessibilities were more important in low price single family houses, green zone and more far way is affected positive effects on single family houses price. In Kangbuk, land coverage ratio affects similar effects on single family houses price.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.1
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• pp.67-79
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• 2013

For the sake of the Transit-Oriented Development that has been prominent recently, an analysis of the spatial structures of transit centers, above all, should be carried out at a local level. This study, thus, analyzes the spatial structures of subway influence areas by applying a Geographically Weighted Regression (GWR) model to individual parcels. As a result of the validity analysis of the model, it has turned out that the subway influence areas have different characteristics respectively, and there is spatial heterogeneity even in the same single area. Also, the result of the comparison among models has proved that the GWR model is more adequate than the Ordinary Least Square (OLS) model and $R^2$ has been also increased in the GWR model. Then, the results have been mapped by means of the GIS, which have made it possible to understand the spatial structures at a local level. If the Transit-Oriented Development is fulfilled in consideration of the spatial structural characteristics of the subway influence areas drawn respectively from the model analysis, it will be helpful in adopting effective policies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.310-318
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• 2016

This study examined the correlation between microscopic factors and pedestrian volume in an urban environment, focusing on the microscopic factors that stimulate the pedestrian volume, such as density, diversity, network structure, accessibility, and the form of lots and buildings. In particular, factors already known to boost the pedestrian volume include density, diversity and accessibility, which are three variables strongly related to the concept of the 3Ds (Density, Diversity, Design) proposed by Cervero and Kockelman (1997) and the additional 2Ds (Distance to Transit, Destination Accessibility) suggested by Ewing et al. (2008). The analysis in this study was based on the 2010 survey of the floating population in Seoul, particularly on the data from Jongro-gu and Jung-gu in Gangbuk area. Data were established by analyzing the microscopic factors within a 500m radius around each of the 1,028 spots from which the pedestrian volume in Jongro-gu and Jung-gu was measured. The analysis showed that density, diversity and accessibility, three factors that were already known to be effective in increasing pedestrian volume, also have the same effect in Jongro-gu and Jung-gu.

• Journal of Korea Trade
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• v.27 no.5
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• pp.113-136
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• 2023

Purpose - Global production chains and their impacts on economic growth have drawn extensive attention from researchers. Close relationships among global production chains, export and economic growth have been illuminated, as evidenced by the fast and stable economic growth of East Asian economies. These economies perform various roles within global production chains using offshoring, in which the impact of import on domestic gross output is as strong as that of export. The impact of import on economic growth would depend on whether imported inputs substitute or complement domestic inputs production, which is likely to vary according to individual countries' functions within global production chains. The economic growth of concerned countries would also be diverse. However, little attention has been paid to the impact brought by imports compared to its significance. Design/methodology - The principal methodology used in this paper is structural decomposition analysis (SDA), widely chosen to elucidate the impact of various factors on domestic gross output using input-output tables. This paper extracts trade data of six Asian economies from the World Input-Output Database (WIOD) 2016 release that covers 43 countries for the period 2000-2014. The extracted data is then categorised into 37 sectors. First, this paper calculates the Feenstra-Hanson Offshoring Index (OSI) of each country. It then applies SDA to measure the changes in each economy's gross output, export, import input coefficients, and domestic input coefficients. Finally, after taking the first difference from pooled time-series data, it estimates the correlations between imported input coefficients and OSI using the ordinary least square (OLS) method. Findings - The main findings of this paper can be summarised as follows. Firstly, all six countries have increasingly engaged in global production chains, as evidenced by the growing size of OSI. Secondly, there are negative correlations in five countries except Japan, with sectoral differences. Thirdly, changes in import input coefficients are not negative in all six countries, indicating that offshoring does not necessarily substitute for domestic inputs production but does complement it and, therefore, fosters their economic growth. This is observed in China, Indonesia, Korea and Taiwan. Offshoring has led to an increase in the use of imported inputs, which has, in turn, stimulated domestic inputs production in these countries. Originality/value - While existing studies focus on the role of export in evaluating the impact of participating global production chains, this paper explicitly examines the unexplored impact of import on domestic gross output by considering both the substitution and the complementary effect, using the WIOD. The findings of this paper suggest that Asian economies have achieved fast and stable economic growth not only through successful export management but also through effective import management within global production chains. This paper recommends that the Korean government and enterprises carefully choose offshoring strategies to minimise disruption to domestic production chains or foster them.