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A Study on Policy Priorities for Implementing Big Data Analytics in the Social Security Sector : Adopting AHP Methodology

AHP분석을 활용한 사회보장부문 빅 데이터 활용가능 영역 탐색 연구

  • Ham, Young-Jin (Dept. of Research and Development, Korea Health and Welfare Information Service) ;
  • Ahn, Chang-Won (ETRI(Electronics and Telecommunications Research Institute)) ;
  • Kim, Ki-Ho (ETRI(Electronics and Telecommunications Research Institute)) ;
  • Park, Gyu-Beom (Dept. of Research and Development, Korea Health and Welfare Information Service) ;
  • Kim, Kyoung-June (Dept. of Research and Development, Korea Health and Welfare Information Service) ;
  • Lee, Dae-Young (Dept. of Research and Development, Korea Health and Welfare Information Service) ;
  • Park, Sun-Mi (Dept. of Research and Development, Korea Health and Welfare Information Service)
  • Received : 2014.06.20
  • Accepted : 2014.08.20
  • Published : 2014.08.28

Abstract

The primary purpose of this paper is to find out what issues are important in the Social Security sector, and then, through AHP methodology, this study analyzes what kind of big data methodologies and projects can be implemented to solves these issues. To the aim, this paper first confirmed 8 big data projects from reviewing all issues in the Social Security sector such as administrative works and social policies. After the result of pairwise comparison, policy validity is most important factors rather then effectiveness and practicability. With regard to the priorities among sub-big data projects, the project about preventing improper recipients has come out the most important project in terms of validity, effectiveness and practicability. And the results showed that the project about outreaching and reducing a blind spot on the welfare sector is weighed as a significant project. The results of this paper, in particular 8 sub-big data projects, will be useful to anyone who is interested in using big data and its methodologies for the social welfare sector.

본 논문의 목적은 사회보장분야에서 어떠한 이슈가 중요시 되고 있으며, 어떠한 이슈에 빅 데이터 분석기술이 적용가능한지를 전문가 AHP방법을 통해 살펴보는데 있다. 이를 위해 사회보장분야에서 중요시 되고 있는 이슈분석 수행하였으며, 이를 토대로 8개 주요 과제를 도출하였다. 평가기준의 쌍대비교 결과, 정책적 타당성이 사업의 효과성과 실현가능성 보다 중요한 의미를 갖는 지표로 도출되었다. 그리고 세부과제 우순순위 절대평가 결과를 살펴보면, 사회보장분야 부적정 급여 방지와 사각지대 조기 발굴은 빅 데이터 분석을 통해 복지행정의 합리성 증진과 대국민 권리구제를 강화한다는 측면에서 매우 의미 있는 과제로 도출되었다. 본 연구는 사회보장분야에서 빅 데이터 활용 가능여부를 분석하였다는 점에서 의의가 있으며, 향후 빅 데이터 관련 세부과제의 체계적인 추진을 위한 기반연구로 기능할 수 있을 것이다.

Keywords

References

  1. B. D. Jung, The Analysis of Priorities of Roads Investment Using Analytic Hierarchy Process, Journal of Korean Society of Transportation , Vol. 20, No.5, pp.45-54, 2002.
  2. C. W. Ahn, et al., A study on exploring the implementation of Big data in the social security sector, Korea Health Industry Development Institute, 2013.
  3. H. M Chun The Impact of the Une SNS and Big data to Enable Social Commerce, Korea Logistics Review, Vol.23 No.5, pp.405-431, 2013
  4. K. H. Kwak, Big Data and Personal Information Protection, Ilkam Law Review, Vol 27 No 0, pp.125-153, 2014
  5. K. K. Ko, H. Y. Ha, Meta Analysis of the Utilization of Analytic Hierarchy Process for Policy Studies in Korea, Korean Policy Studies Review, Vol. 17, No. 1, pp.287-313, 2008.
  6. National Information Society Agency, New Value Creation Engine, New Possibility and Strategy of Big Data, IT & Future Strategy, Vol. 18, 2011.
  7. Saaty, T. L., The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation (2nd edition), Pittsburgh, PA:RWS Publication, 1990.
  8. Saaty, T. L., Fundamentals of Decision Making and Priority Theory with the Analytic Hierarchy Process, Pittsburgh, PA:RWS Publication, 1994.
  9. S. H. Kim, J. K Choi, The Weights Analysis of Evaluation Areas and Items for the Informatization Program by means of the AHP, Journal of the Korean operations research and management science society, Vol. 32, No. 2, pp.123-140, 2007.
  10. S. H. Lee, D. W. Lee, Current Status of Big Data Utilization, The Journal of digital policy & management Vol. 11 No. 2, pp.229-233, 2013
  11. Slaughter, R., A New Framework for Environment -al Scanning, Foresight : the Journal of Futures Sudies, Strategic Thinking and Policy, Vol. 1, No. 5, pp.387-397, 1999.
  12. S. C. Kim, H. J. Eo, Priority Aggregation for AHP Based on Experts Opinions, Journal of the Korean operations research and management science society, Vol. 19, No. 3, 41-51, 1994.
  13. T. S. Kim, J. S. Kim, Social Security Theory(2nd Edition), Chungmok, 2006.
  14. Anderson Cancer Center: www-03.ibm.com/ innovation/us/ watson/pdf/MD_Anderson_Case_Study.pdf
  15. Expert Choice Homepage: expertchoice.com/.
  16. Google Crisis Response: www.google.org/crisis response
  17. Google Flu Trend: www.google.org/flutrends
  18. Great Britain HSC: www.bis.gov.uk/foresight
  19. Pillbox: pillbox.nlm.nih.gov
  20. Public Data Portal: www.data.go.kr/.
  21. Seoul Open Data Square: data.seoul.go.kr/.
  22. Singapore Immigration & Checkpoints Authority: www.sas.com/offices/asiapacific/korea/success/ica.html
  23. Singapore RAHS: app.rahs.gov.sg/public/www/home.aspx
  24. Syracuse: www.syrgov.net
  25. Toulouse: www.toulouse.fr/web/project-urbain/
  26. University of Western Ontario Healthcare: www.slideshare.net/davidpittman1/big-data-inhealthcare-realtime-health-monitoring-and-interve ntion
  27. Where does my money go: www.whrerdoesmymoneygo.org