Journal Home Online First Current Issue Archive For Authors Journal Information 中文版

Frontiers of Engineering Management >> 2018, Volume 5, Issue 1 doi: 10.15302/J-FEM-2018067

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

. Department of Building and Real Estate, The Hong Kong Polytechnic University, Hong Kong, China.. Department of Construction Management and Real Estate, School of Economics and Management, Tongji University, Shanghai 200092, China

Accepted: 2018-01-31 Available online: 2018-03-21

Next Previous

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.

Related Research