An analytical network process model for risks prioritisation in megaprojects.

Boateng, Prince; Chen, Zhen; Ogunlana, Stephen O.

Abstract

Megaprojects are complex and expensive projects that often involve social, technical, economic, environmental and political (STEEP) challenges to project management. Despite these challenges, project owners and financiers continue to invest large sums of money in megaprojects that run high risks of being over schedule and over budget. While some degree of cost and schedule risks are considered during project planning, the challenge of modelling risks interactions and impacts on project performance still remains. To tackle this technical problem, this research adopted the Analytical Network Process and combined it with a new Risk Priority Index as an innovative approach to model risks analytically based on data collected from the Edinburgh Tram Network project at the construction phase. The approach provides an interactive way for developers to prioritise risks across the project supply network and to initiate timely mitigation strategies against significant cost and time consequences of STEEP risks on megaproject performance.

Citation

BOATENG, P., CHEN, Z. and OGUNLANA, S.O. 2015. An analytical network process model for risks prioritisation in megaprojects. International journal of project management [online], 33(8), pages 1795-1811. Available from: https://doi.org/10.1016/j.ijproman.2015.08.007

• Journal Article Type: Article
• Acceptance Date: Aug 25, 2015
• Online Publication Date: Sep 29, 2015
• Publication Date: Nov 30, 2015
• Deposit Date: Feb 29, 2016
• Publicly Available Date: Sep 30, 2018
• Journal: International journal of project management
• Print ISSN: 0263-7863
• Electronic ISSN: 1873-4634
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 33
• Issue: 8
• Pages: 1795-1811
• DOI: https://doi.org/10.1016/j.ijproman.2015.08.007
• Keywords: Risk assessment; Analytical Network Process; Megaproject; Decision making
• Public URL: http://hdl.handle.net/10059/1393
• Contract Date: Feb 29, 2016