Fuzzy integral-based risk-assessment approach for public-private partnership infrastructure projects

Adequate assessment of risk is essential to assist the stakeholders in planning for efficient risk allocation and mitigation and to ensure success in business and projects. However, it is problematic due to the difficulty in quantification of certain risks, existence of interactions, and multiattribute structure of the project risk assessment task. This paper reports research in which relevant risks were identified for power and transport infrastructure public-private partnership (PPP) projects, which are globally the most active infrastructure sectors for private investment. It further proposes, demonstrates, and validates a novel multiattribute risk assessment model that supports both sectoral and project risk analysis to assist stakeholders in risk management decision making. A 45-factor risk register, established based on literature review and PPP experts' interviews, was administered to solicit industry-wide perceptions for risk assessment. Application of fuzzy set theory to risk analysis revealed 22 critical risk factors (CRFs) that were categorized into seven critical risk groups (CRGs) of correlated factors using factor analysis. Risk factors that achieved a linguistic assessment of high impact reflect issues related to institutional capacity and the local economy. Further analysis based on fuzzy measure and nonadditive fuzzy integral combined with arithmetic mean helped to obtain an overall risk index (ORI) which indicated a moderate risk outlook for both power and transport infrastructure sectors. Whereas public sector maturity was assessed as a high impact CRG in the power sector, project planning and implementation, project finance, and project revenue were additionally rated as high impact CRGs in the transport infrastructure sector. Demonstration of the developed methodology for a build-operate-transfer (BOT) motorway case study project showed that the private sector stakeholders viewed the project at high risk with all the CRGs evaluated as high impact except the political stability CRG, which was assessed as moderately risky. Test results show that the methodology performed satisfactorily in approximating experts holistic project risk assessments. The developed framework can be used to assess a country's condition or overall project risk at the initial project stage with little input of time and resources, thus facilitating an efficient and robust risk assessment. Application of fuzzy measure based nonadditive fuzzy integral combined with arithmetic mean for sectoral and project risk assessment, and comparison of sectoral risk analysis from a developing country perspective are some of the key features of this study.