Risk Management in Road Construction Projects: A Fuzzy ANP Approach for Prioritizing Critical Factors

Abstract

Road construction projects are inherently associated with numerous risks and uncertainties that can significantly impact project objectives including cost, time, and quality. This paper presents a comprehensive risk assessment framework for road construction projects using fuzzy Analytic Network Process (ANP) methodology. A case study of road construction projects in Tonkabon city, Iran, is conducted to identify, evaluate, and prioritize risk factors affecting project performance. Through literature review and expert consultation, five main risk categories and ten sub-criteria were identified. The fuzzy ANP method was employed to handle the inherent uncertainty in expert judgments and capture interdependencies among risk factors. Results indicate that employer-related risks (weight: 0.27) rank first, followed by accident-related risks (0.23), machinery-related risks (0.18), contractor-related risks (0.16), and consultant-related risks (0.14). Among sub-criteria, lack of access to skilled and expert personnel emerged as the most critical risk factor (weight: 0.12). The findings provide valuable insights for project managers and stakeholders in developing proactive risk mitigation strategies for road construction projects. The proposed methodology offers a systematic approach for risk prioritization that can be adapted to various infrastructure project contexts.