Incorporating stakeholder perception into risk assessment model: an empirical study of highway construction projects

PurposeLarge infrastructure projects encounter diverse risks, yet existing risk assessment (RA) models often overlook key stakeholder perspectives. This study addresses the gap by combining insights from both public and private sector stakeholders into an innovative RA model.Design/methodology/approachThe study examined Vietnam's Mekong Delta highway projects through two targeted surveys to capture stakeholder perceptions of risk factors. Statistical analysis and the fuzzy synthetic evaluation (FSE) methods were utilized to identify critical risk factors (CRFs), primary risk groups (PRGs), and overall risk levels (ORLs) from stakeholder perspectives. Subsequently, seven professional experts re-evaluated the CRFs, validated the proposed RA model, and confirmed its applicability for upcoming projects.FindingsThe study identified twenty-two CRFs and grouped them into five PRGs. Land acquisition and compensation issues and material price fluctuations are the two most prominent CRFs, while commercial and natural environment risks are the most significant risk components. Notably, the private sector stakeholders perceive higher risk levels than the public sector counterparts across almost identified risk categories and indexes.Practical implicationsThe study contributes to improving RM practices and project RA outcomes in highway construction by developing this stakeholder-driven RA model. It also provides ready-to-use risk registers and actionable strategies, facilitating stakeholders with practical tools for effective RM. Key recommendations for highway projects include (1) flexible land acquisition policies and streamlined compensation processes, (2) price adjustment mechanisms in contracts, and early stakeholder engagement to address regulatory and environmental concerns proactively.Originality/valueThis study introduces a novel, stakeholder-driven RA model, addressing the gap between theoretical frameworks and real-world applications. It offers a structured and data-driven approach to risk identification and prioritization, applicable not only to highway projects in Vietnam's Mekong Delta but also to similar infrastructure projects worldwide. The findings contribute to advancing risk management (RM) theory while delivering practical tools for policymakers, project managers, and investors to strengthen decision-making and project resilience.