• 한국벤처창업학회:학술대회논문집
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• 2018.04a
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• pp.67-74
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• 2018

소상공인 창업자들이 자금조달의 대부분을 은행 대출에 의존하고 있는 가운데 소규모 자금 조달을 필요로 하는 이들을 위해 핀테크 기반의 새로운 금융서비스를 통해 소상공인 창업자의 금융 공급을 확산할 필요가 있다. 이러한 환경 변화 패러다임에서 본 연구는 빅데이터와 핀테크 솔루션의 활용이 소상공인의 매출과 금융지원에 미치는 영향을 살펴보기 위해 실제로 공공과 민간의 상권빅데이터자료를 수집하여 분석을 수행하였다. 이를 통해 소상공인에 대한 금융혜택 증대를 위한 사업장의 매출증대 등 소상공인 창업자의 사업성 평가에 필요한 주요변수들을 상권빅데이터를 실증적으로 분석하여 효과성을 검증하는 것이 본 연구의 목적이다. 특히 자금의 대부분을 정책자금을 통해 조달하는 소상공인들이 일반 은행에서도 중소기업 대출의 하나로 비중 있게 이루어질 수 있도록 기존에 활용되지 못한 빅데이터 변수들을 탐색하여 소상공인의 경쟁력 향상을 위한 효율적인 금융지원이 가능함을 확인하고자 하였다. 본 연구에서는 소상공인 창업자의 대출 등 금융지원 확대를 위한 사업성 평가에 상권빅데이터의 활용 가능성이 있는지를 중심으로 문헌적 연구방법 연구와 실증적 분석을 병행하였다. 본 연구는 핀테크와 빅데이터의 활용이 향후 소상공인 자금 조달의 발전 방향이 어떻게 되어야하는지를 모색해야하며, 소상공인을 포함하는 중소기업 신용평가방식의 발전 방향을 구체적으로 모색되어야 할 시점임을 의미하고 있다.

• The Journal of Bigdata
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• v.5 no.2
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• pp.171-186
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• 2020

The proportion of micro-enterprises and self-employed in Korea is excessively high compared to that of major developed countries, and frequent start-ups and business closures are repeated, causing enormous damage to the national economy. In order to solve this problem, various studies are underway for micro-enterprises, and the government provides commercial district information analysis services using big data for micro-enterprises. Among the commercial district information analysis services, the commercial district information analysis of our village store operated by the Seoul Metropolitan Government is continuously improving its service to provide the big data analysis service related to micro-enterprises. Since the service was built by integrating big data provided by various organizations, however, there are limitations in data reliability, data analysis, and service composition. In order to overcome these limitations, this paper proposes a location-based survey system that can be analyzed in conjunction with big data-based commercial district services. The proposed questionnaire survey system established the basis for expending the big data commercial district analysis service by linking the survey information and commercial district information.

• Annual Conference of KIPS
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• 2015.10a
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• pp.1244-1247
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• 2015

본 논문에서는 소상공인의 창업 성공을 지원하는 점포 평가 분석 사례를 소개하여 기업의 빅데이터 도입 및 활용을 촉진하고자 한다. 본 사례에서는 카드사 거래 정보, 가맹점 정보, 부동산 가격 정보, 부동산 통계 정보, 감정평가 정보, 조사업무관련 정보 및 인허가 개폐업 정보를 활용해 36만개의 GIS 블록과 GEO 컨텐츠를 생산하여 빅데이터 분석을 실시하였다. 체계적인 분석을 위해 상권 평가 지수, 업종 평가 지수, 입지 평가 지수, 임대료 추정, 매출 추정, 적정면적 추정 등의 상권, 업종, 입지에 대한 지표를 개발하였다. 이를 통해 상가와 상권에 대한 분석 자료를 제공하여 과밀창업의 예방과 신중한 창업의 유도를 통해 창업실패로 유발 될 수 있는 경제적 비용의 감소 효과를 이룰 것으로 판단된다.

• The Journal of Bigdata
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• v.5 no.2
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• pp.29-42
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• 2020

In Korea, micro-enterprises are in charge of an important part of the common people's economy, but face difficulties such as excessive competition, deteriorating profitability, and concentration of life-oriented industries. In order to solve this problem, the government is providing commercial district analysis services for micro-enterprises. However, the data provided by various organizations is not standardized, and there is a limit to the composition of the service with limited data. In this paper, we propose a method of solving the data consistency problem and linking and analyzing between questionnaire information and commercial district information to expand the data analysis service. The proposed linking methods are three methods: linking the commercial area information and questionnaire information in the same area based on the type of business and area, linking the survey information centered on individual micro-enterprise, and linking a small area of questionnaire information with a large area of commercial district information. The linked commercial district information and questionnaire information can be used in various ways or expanded analysis services. This proposed a method to overcome the limitations of existing commercial district analysis services with questionnaire information and lay the foundation for expanding the commercial district analysis services necessary for micro-enterprises.

• Information Systems Review
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• v.20 no.2
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• pp.63-85
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• 2018

Emerging hotspot and trendy areas are formed into alleys and blocks with the help of viral effects among social network services (SNS) users called "Golmogleo." These users search for every corner of the alleys to share and promote their own favorite places through SNS. An analysis of hot places is limited if it is only based on macroeconomic indicators such as commercial area data published by national organizations, large-scale visiting facilities, and commuter figures. Careful analyses based on consumers' actual activities are needed. This study develops a "social big data analysis methodology" using Instagram data, which is one of the most popular SNSs suitable to identify recent consumer trends. We build a spatial analysis model using Local Moran's I. Results show that our model identifies new trend zones on the basis of posting data in Instagram, which are not included in the commercial information prepared by national organizations. The proposed analysis methodology enables better identification of the latest trend areas formulated by SNS user activities. It also provides practical information for start-ups, small business owners, and alley merchants for marketing purposes. This analytical methodology can be applied to future studies on social big data analysis.

• 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.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.3
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• pp.125-140
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• 2018

According to statistics, it is shown that domestic SMEs rely on bank loans for the majority of fund procurement. From financial information shortage (Thin file) that does not provide information necessary for credit evaluation from banks such as financial statements. In order to overcome these problems, recently, in alternative finance such as P2P, using differentiated information such as demographics, trading information and the like utilizing Fintech instead of existing financial information, small funds A new credit evaluation method has been expanding to provide SMEs with small amounts of money. In this paradigm of environmental change, in this research, credit evaluation which can expand fund supply to SMEs by utilizing big data based on trade area information such as sales fluctuation, location conditions etc. In this research, we try to find such a solution. By analyzing empirically the big data generated in the trade area, we verify the effectiveness as a credit evaluation factor and try to derive the main parameters necessary for the business performance evaluation of the founder of SMEs. In this research, for 17,116 material businesses in Seoul City that operate the service industry from 2009 to February 2018, we collect trade area information generated for each business location from Big Data specialized company NICE Zini Data Co., Ltd.. We collected and analyzed the data on the locations and commercial areas of the facilities that were difficult to obtain from SMEs and analyzed the data that affected the Corporate financial Distress. It is possible to refer to the variable of the existing unused big data and to confirm the possibility of utilizing it for efficient financial support for SMEs, This is to ensure that commercial lenders, even in general commercial banks, are made to be more prominent in one sector of the financing of SMEs. In this research, it is not the traditional financial information about raising fund of SMEs who have basically the problem of information asymmetry, but a trade area analysis variable is derived, and this variable is evaluated by credit evaluation There is differentiation of research in that it verified through analysis of big data from Trading-area whether or not there is an effect on.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.269-270
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• 2016

빅데이터 분석을 통한 여러 산업 군과 융합으로 시너지를 발생시키기 위해서, 다양한 유형의 데이터 수집을 통해 빅데이터를 구성하는 것이 첫 번째 단계이며 기상, 교통, 인터넷 활동, 상권 등의 다양한 출처로부터 데이터 연계를 수행하고 사물인터넷과 같은 실시간으로 발생하는 로그 성 데이터 수집을 고려한 실시간 처리 시스템을 설계 하였다. 이를 통해 서로 다른 유형의 데이터가 빅데이터로 수집 되면 여러 산업 군에서 요구되는 인사이트 기반의 빅데이터 분석을 통해 B2B 또는 B2C 서비스에 응용 될 수 있다.

• Annual Conference of KIPS
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• 2017.11a
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• pp.652-654
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• 2017

본 프로젝트의 목적은 소상공인들을 위한 상권 분석, 트렌드 분석, 창업 지원 정책 소개, 커뮤니티 등을 제공하는 빅 데이터 기반의 웹 서비스를 구축하는 것이다. 일반적인 창업 관련 사이트는 정형데이터를 DB(Data Base)에 저장 후 관리되는 시스템으로, 이는 사용자 개개인에 맞는 맞춤형 정보를 제공하기 힘들다. 따라서 본 논문에서는 실시간 검색어 수집 및 분석을 통해 소상공인들이 창업을 희망할 때, 사용자에 맞는 정보를 제공해주는 맞춤형 서비스 연구에 대한 내용이다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.784-792
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• 2018

In this study, we designed the area except the development market and the traditional market, where large scale shops were concentrated by realizing the real estate center of the alley commercial area. In addition, we have developed an area setting method for the alley area where reliability and rationality can be ensured by utilizing the actual data such as the business statistics, the survey data of the business, and the store business DB, which are managed by the local government or the state. The alley commercial areas were classified into five groups according to density. It is thought that users can distinguish the commercial areas from dense commercial areas to the commercial areas in order to utilize various commercial areas.