DOI QR코드

DOI QR Code

Tourism policy establishment plan using geographic information system and big data analysis system -Focusing on major tourist attractions in Incheon Metropolitan City-

지리정보시스템과 빅데이터 분석 시스템을 활용한 관광 정책수립 방안 -인천광역시 주요 관광지 중심으로-

  • Min, Kyoungjun (Big Data Convergence Department, Korea University Graduate School of Computer and Information Technology) ;
  • Lim, Heuiseok (Department of Computer Science and Engineering, Korea University)
  • 민경준 (고려대학교 컴퓨터정보통신대학원 빅데이터융합학과) ;
  • 임희석 (고려대학교 컴퓨터학과)
  • Received : 2021.04.26
  • Accepted : 2021.08.20
  • Published : 2021.08.28

Abstract

This study aims to analyze tourist inflow trends and consumption patterns using a geographic information system and big data analysis system. Songdo Central Park and Chinatown were selected among the major tourist destinations in Incheon, and floating population analysis and card sales analysis were conducted for one month in June 2017. The number of tourists visiting Songdo Central Park from metropolitan cities across the country was highest in the order of Incheon Metropolitan City, Gyeonggi-do, and Seoul Metropolitan City, and the proportion of foreign tourists was the highest in China. The number of card consumption used by Chinatown tourists was 12.4% higher for men than for women, and the amount of card consumption was also higher for men by 18%. This study has implications for proposing a strategic plan for tourism policy by analyzing the inflow trend and consumption pattern of tourists and deriving major issues in the establishment of tourism policy. Based on this study, it is expected that it can be helpful in improving the construction of tourism infrastructure in the future.

본 연구는 지리정보시스템과 빅데이터 분석 시스템을 활용하여 관광객 유입동향 및 소비패턴 분석에 목적을 둔 연구이다. 인천광역시 주요 관광지 중 송도센트럴파크와 차이나타운을 선정하여 2017년 6월 1개월 동안 유동인구 분석, 카드매출 분석을 진행하였다. 전국 광역시도로부터 송도센트럴파크에 방문한 관광객은 인천광역시, 경기도, 서울특별시 순으로 높게 나타났으며, 외국인 관광객 비중은 중국이 가장 높았다. 차이나타운 관광객의 카드 소비 이용건수는 남성이 여성보다 12.4% 높게 나타났고 카드소비 금액도 남성이 18% 높게 나타났다. 본 연구는 관광객들의 유입동향 및 소비패턴을 분석하여 관광정책 수립의 주요 쟁점들을 도출함으로써 관광정책의 전략적 방안을 제안하는데 시사점이 있다. 본 연구를 바탕으로 향후 관광 인프라 구축 개선에 도움이 될 수 있다고 기대된다.

Keywords

References

  1. S. J. Lee, S. H. Ahn & H. A. Y. (2021) KRIHS POLICY BRIEF No.811. Diagnosis of the current status and causes of the decline of tourist destinations and the direction of the regeneration policy : KRIHS
  2. D. W. Ha. (2017). KIET Industrial Economy October 2017. http://www.kiet.re.kr
  3. Y. Noh. (2007). A study on the architecture of tourism information system using web-based GIS. Financial knowledge research, 5(1). 159-177, ISSN 1738-0715
  4. Tourism Research Division. (2020). Impact of COVID-19 on tourism industry and countermeasures
  5. National Travel Survey. https://know.tour.go.kr/
  6. Korea Culture and Tourism Institute. https://www.kcti.re.kr/web/user/main.do
  7. B. K. Jang. (2020). tourism policy : Baeksan publisher
  8. H. S. Kim. (2006). A study on the change direction of tourism industry policy:Korea Culture and Tourism Policy Institute
  9. W. S. Shim, S. M. Choi & C. S. Shim. (2018). Identifying Major Issues of Tourism Analysis Using Big Data: Focused on Mobile and Credit Card Data.Journal of Tourism Studies, 30(3), 3-22. DOI : 10.21581/jts.2018.08.30.3.3
  10. K Chang. (2008). Introduction to Geographic Information Systems : McGraw Hill
  11. Korea National Spatial Data Infrastructure Portal. http://www.nsdi.go.kr/
  12. S. H. Jeon & K. T. Do. (2013). Design and Implementation of Web GIS Server Using Node.js. Spatial Information Research, 21(3), 45-53. DOI : 10.12672/KSIS.2012.20.6.045
  13. H. J. Kim (2001). Development of Kwangju Tourism Information System on the Basis of GIS. Journal of the Korean GIS Society, 9(2), 277-290.
  14. J. Y. Heo, J. H. Seo, Y. B. Kim & M. K. Park (2003). Construction Method of a Cyber Tourism System using Geographic Information System. 175-183.
  15. E. H. An & J. K. An. (2021). A Study on the Revitalization of Local Tourism in Yongin City Based on Tourism Bigdata Analytics: Focusing on Geographic InformationSystem Analytics Combining Mobile Communication and Credit Card Data. Journal of the Korea Convergence Society, 12(4), 207-216, DOI: 10.15207/JKCS.2021.12.4.207.
  16. GeoServer Website. http://geoserver.org/
  17. OpenLayers Website. https://openlayers.org/