서울시 골목상권 유형화와 창·폐업 영향요인 분석 : 시계열 유동인구 빅데이터와 Dynamic Time Warping 시계열 군집분석을 활용하여

초록

The cycle of growth, stagnation, and decline of commercial districts resembles that of a living, breathing organism. People are motivated to visit commercial districts due to the competitiveness of the entire commercial district, which affects the typology of weekday and weekend commercial districts. This study aims to analyze the influencing factors of alley commercial districts’ vitality through the typology of commercial districts and to provide policy implications for alley commercial district revitalization by verifying the relationship between business openings and closings. For the analysis, we utilized floating population big data and dynamic time warping time series cluster analysis. Additionally, we conducted logistic regression analysis to identify influencing factors affecting business openings and closings. The analysis results that the number of apartments, business type diversity index, density of businesses, and number of hinterland gathering facilities exhibit positive relationships for determining weekend commercial districts. By contrast, the number of franchises, number of office workers, individual land price, existence of subway station, and the location adjacent to major commercial district exhibit negative relationships. Furthermore, multiple linear regression analysis was performed to explore the relationship between business openings and closings and influencing factors. The significance of this study is that different types of alley commercial districts in Seoul are identified and that influencing factors affecting business openings and closings in each alley commercial district are indicated. This study suggests that different revitalization policies should be applied depending on the alley commercial districts.

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