Risk allocation in public-private partnership projects : an innovative model with an intelligent approach
Jin, Xiaohua and Doloi, Hemanta 2007, Risk allocation in public-private partnership projects : an innovative model with an intelligent approach, in COBRA 2007 : Proceedings of the Construction and Building Research Conference of the Royal Institution of Chartered Surveyors, Royal Institution of Chartered Surveyors (RICS), [Georgia Tech, Atlanta], pp. 1-13.
Attached Files
(Some files may be inaccessible until you login with your Deakin Research Online credentials)
Name
Description
MIMEType
Size
Downloads
Title
Risk allocation in public-private partnership projects : an innovative model with an intelligent approach
Both the increasing private participation in public projects and the critical importance of appropriate risk allocation to the success of Public-private partnership (PPP) projects justify specific research on how to establish effective risk allocation strategies in PPP projects. Partner’s risk management capability is currently the main concern to risk allocation in PPP projects. Following the transaction cost economics, it is argued that factors such as partner’s commitment and risk management structure should be considered simultaneously in order to develop effective risk allocation strategies. Based on the holistic capability-commitment governance-driven view, this paper proposed a model for generating an optimal risk allocation strategy in PPP projects. The model is demonstrated and described. An artificial intelligent technique integrated with fuzzy logic for model testing and validation is then introduced and justified. The innovative model is expected to provide a logical and complete understanding of the risk allocation strategy selection process, and to provide stakeholders with a richer framework than previously existing ones to guide their decision-making on risk allocation strategies.
ISBN
9781842193570
Language
eng
Field of Research
120201 Building Construction Management and Project Planning