Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/79651
Title: A fuzzy model for assessing the risk exposure of procuring infrastructure mega-projects through public-private partnership : the case of Hong Kong-Zhuhai-Macao Bridge
Authors: Chan, APC 
Osei-Kyei, R 
Hu, Y
Yun, L
Keywords: Infrastructure mega-projects
Public-private partnership
Hong Kong-Zhuhai-Macao Bridge
Hong Kong
Fuzzy
Issue Date: 2018
Publisher: Higher Education Press
Source: Frontiers of engineering management, Mar. 2018, v. 5, no. 1, p. 64-77 How to cite?
Journal: Frontiers of engineering management 
Abstract: Considering the rapid urbanization growth rate particularly in developing countries, the number of infrastructure mega-projects over the past years has risen tremendously. Essentially, because infrastructure mega-projects require huge investment funds, better management skills, well qualified and experienced international expertise and technology innovation, they are mostly preferred to be procured using the PPP method compare to the use of the traditional bid-build system. In this regard, this paper aims to develop a fuzzy evaluation model for assessing the suitability of procuring infrastructure mega-projects through PPP by considering their risk exposure. The main body of Hong Kong-Zhuhai-Macao Bridge (HZMB) is used as a case project to demonstrate the practicality of the risk evaluation model. The risk evaluation model consists of four critical risk groupings, these include, construction and land risks, commercial risks, operational risks and political risks. Using the risk evaluation equation, a risk index of 4.53 out of 5.00 is computed for the selected project if it is procured through the PPP scheme. This outcome shows that the case project is not suitable for the PPP approach because its risk exposure is very high. The model developed will enable PPP practitioners to predict the likely risk exposure of procuring infrastructure mega-projects through the PPP scheme.
URI: http://hdl.handle.net/10397/79651
ISSN: 2095-7513
EISSN: 2096-0255
DOI: 10.15302/J-FEM-2018067
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