Application of Fuzzy Set Theory to Evaluate Large Scale Transport Infrastructure Risk Assessment and Application of Best Practices for Risk Management

Abstract

This study explores the factors that pose risks to the efficiency with which capital is utilized in large-scale transport infrastructure investments and suggests for risk management best practices that may be applied in relation to each. The literature review categorizes risks into nine major categories. Four practices that enhance capital usage efficiency are selected: namely, value engineering, asset portfolio management, life cycle costing, and quality assurance. Fuzzy set theory is applied to analyze and evaluate risks and the effect of adopting best practices in relation to them. By linking each risk to a best practice, potential enhancements to capital usage efficiency in infrastructure investment projects are observed. Survey responses of 83 engineers involved in land transport infrastructure projects in Sri Lanka form the dataset of this study. Results demonstrate that quality assurance reduces the planning fallacy and political influence, while value engineering reduces risks associated with technical know-how and change order. The study concludes that risks in large scale transport infrastructure investments may be managed through efficiency-enhancing practices to reduce.