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http://dx.doi.org/10.5345/JKIBC.2020.20.4.347

Analysis of Risk Factors for the Importance in Vietnam's Public-Private Partnership Project Using SOM(Self-organizing map)  

Yun, Geehyei (School of Architecture, Yeungnam University)
Kim, Seungho (Graduate School, Yeungnam University College)
Kim, Sangyong (School of Architecture, Yeungnam University)
Publication Information
Journal of the Korea Institute of Building Construction / v.20, no.4, 2020 , pp. 347-355 More about this Journal
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.
Keywords
public-private partnership project; risk management; self-organizing maps; priority;
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Times Cited By KSCI : 1  (Citation Analysis)
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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   DOI
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   DOI
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   DOI
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   DOI
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 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.
15 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