Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography (한국측량학회지)

Korean Society of Surveying, Geodesy, Photogrammetry and Cartography (한국측량학회)
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Analyzing Growth Factors of Alley Markets Using Time-Series Clustering and Logistic Regression

시계열 군집분석과 로지스틱 회귀분석을 이용한 골목상권 성장요인 연구

  • Received : 2019.11.21
  • Accepted : 2019.12.27
  • Published : 2019.12.31
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Abstract

Recently, growing social interest in alley markets, which have shown rapid growth like Gyeonglidan-gil street in Seoul, has led to the need for an analysis of growth factors. This paper aims at exploring growing alley markets through time-series clustering using DTW (Dynamic Time Warping) and examining the growth factors through logistic regression. According to cluster analysis, the number of growing markets of the Northeast, the Southwest, and the Southeast were much more than the Northwest but the proportion in region of the Northwest, the Northeast, and the Southwest were much more than the Southeast. Logistic regression results show that people in 20s and 30s have a lower impact on sales than those in 50s, but have a greater impact on growth of alley market. Alley markets located in high-income areas often reached their growth limits, indicating a tendency to stagnate or decline. The proximity of a subway station effected positive on sales but negative on growth. This research is an advanced study in that the causes of sales growth of alley markets is examined, which has not been examined in the preceding study.

최근 들어 경리단길처럼 빠른 성장세를 보이는 골목상권에 대한 사회적 관심이 높아지면서 골목상권 성장요인에 대한 분석의 필요성이 커지고 있다. 이 연구에서는 서울시의 골목상권 매출액 자료에 동적타임워핑(DTW)을 적용한 시계열 군집분석을 통해 성장 골목상권을 찾아내고 로지스틱 회귀분석을 통해 골목상권의 성장에 영향을 미치는 요인들을 분석하였다. 군집분석 결과, 성장상권은 서남권과 동북권, 동남권에 많이 분포하는 것으로 나타났지만 성장상권의 권역 내 비중은 서북권, 동북권, 서남권이 높게 나타난 반면 동남권은 낮게 나타났다. 로지스틱 회귀분석 결과, 20~30대가 매출액에 미치는 영향은 50대에 비해 낮지만 성장에 미치는 영향은 더 큰 것으로 나타났다. 또한, 소득이 높은 지역에 위치한 골목상권들은 성장 한계에 도달한 경우가 많아 정체 또는 쇠퇴하는 경향이 나타났다. 지하철에 가까운 골목상권일 경우 매출액은 더 많지만 성장성은 오히려 떨어지는 것으로 나타났다. 본 연구는 기존연구에서 다루어지지 않던 골목상권의 성장요인을 처음으로 분석했다는 점에서 의의를 둘 수 있다.

Keywords

References

  1. Kang, H.M. and Lee, S.K. (2017), Classifying alley markets through cluster analysis using dynamic time warping and analyzing possibility of opening new stores, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 35, No. 5, pp. 329-338. https://doi.org/10.7848/ksgpc.2017.35.5.329
  2. Kang, H.M. and Lee, S.K. (2018), An analysis of the effects of customer characteristics on sales of alley market area using geographically weighted regression, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 36, No. 6, pp. 611-620. https://doi.org/10.7848/KSGPC.2018.36.6.611
  3. Kim, G.Y. (2004), A quality evaluation system of a handwriting string by global and local features, Journal of Internet Computing and Services, Vol. 5, No. 6, pp. 121-128.
  4. Kim, K., Sohn, D., and Lee, D. (2014), An analysis of the relationships between pedestrian traffic density and the physical environmental factors of commercial streets, Journal of the Urban Design Institute of Korea Urban Design, Vol. 15, No. 5, pp. 161-171.
  5. Lee, I.S. and Bae, J.H. (2013), Transition of building uses in the culture-based vitalization of commercial streets-a case study of Garosu-gil, Seoul, Journal of the Urban Design Institute of Korea Urban Design, Vol. 14, No. 5, pp. 127-140.
  6. Lee, S.H. (2010), A Study on Activation Factors of Garosu-gil in Sinsa-dong as a Commercial Street, Master's thesis, University of Seoul, Seoul, Korea.
  7. Lee, S. and Oh, K. (2011), Finding the optimal frequency for trade and development of system trading strategies in futures market using dynamic time warping, Journal of the Korean Data & Information Science Society, Vol. 22, No. 2, pp. 255-267.
  8. Park, M.R., Park, K.H., and Ahn, J.S. (2011), A study on the regional classification method using dynamic time warping, The Geographical Journal of Korea, Vol. 45, No. 3, pp. 387-395.
  9. Song, M.K. and Chang, H. (2010), Characterization of Cities in Seoul Metropolitan Area by Cluster Analysis, Journal of The Korean Society for Geospatial Information System, Vol. 18, No. 1, pp. 83-88.
  10. Song, C.W., Nam, K.W., and Lee, C.W. (2012), Driving pattern recognition system using smartphone sensor stream, Journal of the Korea Industrial Information Systems Research, Vol. 17, No. 3, pp. 35-42. https://doi.org/10.9723/jksiis.2012.17.3.035
  11. Yeom, J.H. and Yang, S.W. (2014), Empirical analysis of the vitalization step of commercial street in Samcheongdong-gil, Seoul through the restaurant change, Journal of the Urban Design Institute of Korea Urban Design, Vol. 15, No. 6, pp. 111-122.