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논문 기본 정보

자료유형
학술저널
저자정보
김선정 (The University of Seoul) 남진 (The University of Seoul)
저널정보
대한국토·도시계획학회 국토계획 國土計劃 第57卷 第5號(通卷 第265號)
발행연도
2022.10
수록면
157 - 173 (17page)
DOI
10.17208/jkpa.2022.10.57.5.157

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This study was conducted to empirically analyze the impact of the size of cooperative activities in Seoul on apartment housing prices, referring to the importance of interactions taking place at Seoul National University. To this end, the interaction index that can determine the size of the city’s cooperative activities was calculated using the DIT (non-directional Dominance Index), one of the interaction indicators developed by Limtanakool (2009), and the network hierarchy that occurs disproportionately in the metropolitan area was investigated. In addition, through multiple regression analysis, it was investigated whether the interaction index affects housing prices. Looking at the urban network class identified through this interaction index, Seoul has the highest control in the Seoul metropolitan area, followed by Gyeonggi-do and Incheon. Areas with high control are identified as major employment centers or areas with specific functions, so they have high potential and geographic accessibility. In addition, based on the correlation analysis, regions with high control can be interpreted as regions where two-way mutual supplementation occurs due to high quantitative flows in both inflow and outflow. In addition, based on the network city theory, it was confirmed that even a small scale could have great exponential value at the population level. As a result of the multiple regression analysis, it was found that the interaction index (Eup, Myeon, and Dong) greatly influenced housing prices. According to analysts, apartment prices also rose as the interaction index rose. As the urban network-based interaction index is a major factor influencing housing prices, expanding housing supply considering areas with strong complementary flow through the interaction index calculated in this study may be more important in stabilizing housing prices.

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Abstract
Ⅰ. 서론
Ⅱ. 이론 및 선행연구 고찰
Ⅲ. 서울대도시권 네트워크 현황분석
Ⅳ. 상호작용 지수가 주택가격에 미치는 영향분석
Ⅴ. 결론 및 시사점
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