A new hybrid fuzzy cybernetic analytic network process model to identify shared risks in PPP projects

Abstract

A proper risk management strategy is essential in property management. For controlling and reducing risks on Public-Private Partnership (PPP) project, risk allocation is a major component of PPP risk management. Identifying appropriate shared risks and optimal risk allocation in a structured way is a complex process. The aim of this study is to develop a quantitative approach for equitable risk allocation with attention to identifying dependencies between risk allocation criteria and barriers. The paper presents an approach in the form of a hybrid Fuzzy method and Cybernetic Analytic Network Process (CANP) model for identifying shared risks. The approach involves the use of Fuzzy sets to convert linguistic principles and experiential expert knowledge into systematic quantitative analysis and the CANP to solve the problem of dependency and feedback between criteria and barriers as well as selection of shared risks. A case study is presented to demonstrate the use of the model in selecting shared risks. The study involves development of 10 criteria and 8 barriers. Finally, of 40 significant risks, 14 risks are successfully allocated between the public and private sector in Iranian PPP projects.