Journal of the Korea Institute of Building Construction (한국건축시공학회지)

The Korean Institute of Building Construction (한국건축시공학회)
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Analysis of Risk Factors for the Importance in Vietnam's Public-Private Partnership Project Using SOM(Self-organizing map)

SOM(Self-organizing map)을 활용한 베트남 민관협력사업 리스크 요인 중요도 분석

  • Received : 2020.03.12
  • Accepted : 2020.08.05
  • Published : 2020.08.20
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Abstract

The economic growth rate and the urban population of the Vietnam are steadily increasing. As a result, the size of the Vietnam's construction market for infrastructure development is expected to increase. However, Vietnam is adopting PPP(Public-Private Partnership) to solve this problem because the government lacks the financial and administrative capacity for infrastructure development. PPP is a business that lasts more than 10 years, so risk management is very important because it can be a long term damage in case of business failure. This study proposes a self-organization map (SOM) for analyzing the impact of risk factors and determining the priority of them. SOM is a visualization analysis method that analyzes the inherent correlation through the color pattern of each factor.

베트남의 경제 성장률과 도시인구는 꾸준히 증가함에 따라 베트남의 인프라 개발 건설 시장 규모는 더욱 커질 전망이다. 그러나 인프라 개발을 위한 베트남 정부는 재정 및 행정 능력의 한계로 이러한 문제를 해결하기 위한 방안으로 PPP를 채택하고 있다. PPP는 10년 이상 지속되는 장기 사업으로 사업 실패 시 장기적 큰 피해가 될 수 있어 위험관리가 매우 중요하다. 본 연구에서는 리스크 관리에 대한 리스크 요인의 영향과 관리정도 분석에 SOM분석을 제안한다. SOM분석 방법은 시각화 분석으로, 각 리스크 요인의 색상 패턴을 통해 상관 분석이 가능하다. 본 연구는 SOM을 활용하여 베트남 PPP 사업의 위험요인의 우선순위를 결정하고자 한다.

Keywords

References

  1. Rathbo M, Chan D, Redrup O. Understanding infrastructure opportunities in ASEAN: Infrastructure Series Report 1. Singapore PwC; 2017. 52 p.
  2. Zen F, Regan M. ASEAN public private partnership guidelines. Jakarta: Economic Research Institute for ASEAN and East Asia; 2014. 84 p.
  3. Jeong DY, Hong SJ, Kang SY, Kim YT. An analysis of the legal environment of PPP in South-East Asia: Focused on Vietnam and Indonesia. GRI Review. 2017 Apr;19(1):91-111.
  4. Lee MS, Kim NH, Lee YM, Park MS, Ming BH, Kim YM, Jang HY. A study on the reinforcement of global public-private cooperation network. Cheonan; Koreatec; 2017. 141 p.
  5. Zen F. Public-private partnership development in southeast asia: Indonesia, Malaysia, Philippines, Thailand. ADB Economics Working Paper Series. 2018. 255 p.
  6. KARIM NAA. Risk allocation in public private partnership (PPP) project: a review on risk factors. International Journal of Sustainable Construction Engineering and Technology. 2011 Dec;2(2):8-16.
  7. Nam Gung J, Lee SH. An analysis on the importance and method of mitigation about main risk factors in overseas ppp business: Focused on healthcare PPP business. Journal of the Architectural Institute of Korea Structure & Construction. 2012 Oct;28(10):141-8. https://doi.org/10.5659/JAIK_SC.2012.28.10.141
  8. Hwang BG, Zhao X, Gay MJS. Public private partnership projects in Singapore: Factors, critical risks and preferred risk allocation from the perspective of contractors. International Journal of Project Management. 2013 Apr;31(3):424-33. https://doi.org/10.1016/j.ijproman.2012.08.003
  9. Chan APC, Yeung JFY, Yu CCP, Wang SQ, Ke Y. Empirical study of risk assessment and allocation of public-private partnership projects in China. Journal of management in engineering. 2011 Jul;27(3):136-48. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000049
  10. Lee JS, Ahn BJ, Kim JJ. Evaluating and suggesting key risk factors according to risk hierarchy of occurrence field in the overseas development projects. Korean Journal of Construction Engineering and Management. 2012 Mar;13(2):70-9. https://doi.org/10.6106/KJCEM.2012.13.2.070
  11. Han SH, Kim DY. Risk-based profit prediction model for international construction projects. Journal of The Korean Society of Civil Engineers. 2006 Jul;26(4D):635-47.
  12. Lee JH. Recent Market Trends and Issues in Infrastructure Construction in Vietnam [Internet]. Korea: KOTRA; [updated 2018 March 06; cited 2019 Dec 10]. Available from: https://news.kotra.or.kr/user/globalAllBbs/kotranews/album/2/globalBbsDataAllView.do?dataIdx=165007&searchNationCd=101084
  13. Kohonen T. Self-Organizing Maps. Germany: Springer; 1995. 371 p.
  14. Jung S, Sobanjo JO, Munoz GJ. Visualization and Assessment of the Aging Infrastructure Using Self-Organizing Map. 19th Analy sis and Computation Specialty Conference. 2010 May 12-15; Florida, USA. American Society of Civil Engineers: Structures Congress; 2010. p. 377-86. https://doi.org/10.1061/41131(370)33
  15. Santos M, Monteiro AMV, Medeiros JS. Visualization of geospatial data by component planes and U-Matrix. VI Brazilian Symposium on Geoinformatics. 2004 Nov 22-24; Sao Paulo, Brazil: Geoinfo; 2004. p. 74-89.