• Title/Summary/Keyword: 상권

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Modeling for Consumer Behavioral Pattern in Commercial Supremacy (유통업체 상권내 소비행동패턴 해석)

  • Song, Yeo-Hyeon;Lee, Jung-Hee;Wang, Il-Woung;Kim, Dong-Ho
    • Proceedings of the KAIS Fall Conference
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    • 2010.05b
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    • pp.634-636
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    • 2010
  • 소비자의 행동이론은 경영학의 주된 관심사이다. 소비자의 소비 행동패턴 이론은 소비자의 합리적 소비에 근거한 선호도로써, 선택의 문제를 주요한 연구대상으로 삼고 있다. 하지만 본 모델링은 소비자의 선택을 선호의 문제로 취급하는 기호에 의존하기 보다는, 상권의 측정가능한 크기에 의존하는 수동적 의미의 소비패턴을 산정하게 된다. 단순한 몇 가지 가정을 기반으로 하여 상권이 미치는 영향력을 상권의 거리와 상권의 크기로만 한정할 경우, 최적 경로에 따른 합리적인 소비함수 모델링을 만들 수있다. 상권의 거리 및 상권의 크기로 상권의 범위를 제한 할 경우, 물리학 분야인 전기자기학 중에서 쿨롱의 법칙으로부터 유도된 전기장의 개념을 도입하여 상권의 의미를 재해석할 수 있다. 향후 본 모델링에 대한 소비자 행동패턴의 실질적인 검증 및 추가 도입변수 및 에러항을 도입한 일반적인 모델링으로 발전시킬 수 있고, 그 또한 추가 연구주제가 될 수 있다.

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Classifying and Characterizing the Types of Gentrified Commercial Districts Based on Sense of Place Using Big Data: Focusing on 14 Districts in Seoul (빅데이터를 활용한 젠트리피케이션 상권의 장소성 분류와 특성 분석 -서울시 14개 주요상권을 중심으로-)

  • Young-Jae Kim;In Kwon Park
    • Journal of the Korean Regional Science Association
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    • v.39 no.1
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    • pp.3-20
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    • 2023
  • This study aims to categorize the 14 major gentrified commercial areas of Seoul and analyze their characteristics based on their sense of place. To achieve this, we conducted hierarchical cluster analysis using text data collected from Naver Blog. We divided the districts into two dimensions: "experience" and "feature" and analyzed their characteristics using LDA (Latent Dirichlet Allocation) of the text data and statistical data collected from Seoul Open Data Square. As a result, we classified the commercial districts of Seoul into 5 categories: 'theater district,' 'traditional cultural district,' 'female-beauty district,' 'exclusive restaurant and medical district,' and 'trend-leading district.' The findings of this study are expected to provide valuable insights for policy-makers to develop more efficient and suitable commercial policies.

Analysis of Growth-Decline Type and Factors Influencing Growth Commercial Area Using Sales Data in Alley Commercial Area - Before and After COVID-19 - (골목상권 매출액 데이터를 활용한 성장-쇠퇴 유형화와 성장상권 영향요인 분석 - 코로나19 전후를 대상으로 -)

  • Jiwan Park;Leebom Jeon;Seungil Lee
    • Journal of the Korean Regional Science Association
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    • v.39 no.1
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    • pp.53-66
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    • 2023
  • Due to COVID-19, the external activities of urban residents have greatly shrunk, causing a lot of damage to the commercial district, such as a decrease in population and sales. The downturn in commercial districts means the collapse of the infrastructure of the national economy, and can have serious side effects on the local economy and individual lives. Therefore, it is necessary to look at the alley commercial area, which is closely related to the national local economy, and pay attention to the damage and stagnation of the alley commercial area where small business owners are concentrated. The purpose of this study is to classify alley commercial districts into growth commercial districts and decline commercial districts by using commercial sales time series data and DTW time series group analysis for the pre- and post-COVID-19 period. The main findings of the study are as follows. First, using the time series data on commercial sales before and after COVID-19, the alley commercial districts were divided into growth commercial districts and decline commercial districts, and it was confirmed that the distribution of growth commercial districts and decline commercial districts was regionally different. Therefore, it is necessary to actively manage commercial districts in areas where many declining commercial districts are distributed, and it is required to prepare policies for each region in consideration of the spatial distribution of declining commercial districts. Second, during the COVID-19 period, face-to-face essential industries, density of guest facilities, and population density negatively affected the sustainability of commercial districts, which is the opposite of previous studies. This is the result of empirically confirming the specificity of the COVID-19 period and the negative effects of the integrated economy, and can be used as basic data for effective commercial district management and policy preparation in the event of a national disaster in the future. Third, the characteristics of the background of the commercial district had a significant effect on the sustainability of the commercial district, and the negative effect of the attracting facilities inducing population concentration in the background area was found. This suggests that it is necessary to consider the characteristics of the background as well as the inside of the commercial district when establishing policies to revitalize the commercial district and support small business owners in a national disaster situation.

A Study on Policy Suggestions of Commercial District Revitalization through the Interaction between Local Commercial Districts and Customer Component : The Way of Revitalizing Commercial Districts in Cheonan City (지역상권과 고객구성의 상호작용을 통한 상권활성화에 관한 정책제안 - 천안상권 활성화 방안을 중심으로 -)

  • Kim, Hyun-Gyo;Kim, Cheol-Ho;Lee, Dong-Il
    • The Korean Journal of Franchise Management
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    • v.3 no.1
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    • pp.73-91
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    • 2012
  • This study is in the purpose for the revitalization of traditional market as comparing to the relevancy between the central characteristics of a floating population going around for buying something or eating food and lots of small-sized businesses comprising of the commercial districts. The several traditional markets such as Cheonan station, Dujeong-dong, Sinbu-dong in Cheon-An city has been investigated repeatedly almost every two or three years by the Small Enterprise development Agency(SEDA) since 2001. By analyzing the raw data of those commercial districts made by SEDA, we can calculate the number of firms andthe ratio of business type of each commercial districts. In this research, the type of each business is classified into four groups such as restaurant, service, retail and the rest. Moreover, the central character of the floating population is derived from the raw data, which means the customer information about sex, age structure or the most populous time zones. From these characteristics, one commercial districts has his own specific features distinguishing from the others. The most important differences of past researches are firstly the dynamic viewpoint rather than a static one. Secondly it suggests that the relation between the central characteristics of districts and the floating population would exist. Lastly, it suggests that the interaction between both of them have a significant effect on the growth or decline of the districts and the rates of business type, other adjacent commercial districts as well. Eventually, this study provides several meaningful points for the revitalization of commercial districts to government or stakeholder such as management organization, business owners and new starter etc.

Seoul Local Brand Alley Commercial Area Recommendation System Design Using Machine Learning (머신러닝 기반 서울시 로컬브랜드 골목상권 추천시스템 설계)

  • Jiyeon, Kim;Hyoseon, Jang;Minseo, Park
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.1
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    • pp.101-109
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    • 2023
  • According to data released by the Covid 19 Self-Employed Emergency Response Committee, 95.6% of small business sales due to Covid 19 have decreased over the past two years, and the damage has further increased due to social distancing for quarantine. However, as all social distancing guidelines have rebeen lifted, and the commercial district has been revitalized, the Seoul Metropolitan Government is pushing for a project to foster local brand commercial districts so that small business owners or prospective founders who have closed their businesses due to the prolonged COVID-19. Therefore, this study propose the model that recommends alley commercial districts suitable for founders among the five alley commercial districts selected for the project to foster local brand commercial districts in Seoul. The Seoul Metropolitan Government's local brand alley commercial recommendation system recommends major population age groups and major industries in the commercial district by combining the population perspective model using Xgboost and the commercial district characteristic model using Decision Tree.