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

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.

Keywords

infrastructure mega-projects / public-private partnership / Hong Kong-Zhuhai-Macao Bridge / Hong Kong / fuzzy

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Acknowledgments

This paper forms part of a Ph.D research project entitled “A best practice framework for PPP implementation for infrastructure development in Ghana” from which other papers have been produced with different objective/scope but sharing the same background and methodology. The research project described is fully supported by the Hong Kong Ph.D Fellowship Scheme from the Research Grants Council (RGC) of the Hong Kong Special Administrative Region and The Hong Kong Polytechnic University, Hong Kong. Authors wish to express their sincere gratitude to all PPP practitioners and researchers in Hong Kong who participated in this research study.

RIGHTS & PERMISSIONS

2018 The Author(s) 2018. Published by Higher Education Press. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0)