<![CDATA[Road infrastructure projects are vulnerable to schedule disruption arising from interacting managerial, resource, technical, financial, and external conditions. However, conventional delay studies often identify or rank individual factors without estimating their structural contribution. This study develops and tests an integrated model of seven risk dimensions affecting road infrastructure project delay using Structural Equation Modeling. An explanatory design was implemented through a cross-sectional survey of 260 professionals involved in road infrastructure projects. The measurement model was assessed using indicator loadings, Cronbach’s alpha, composite reliability, average variance extracted, and the Heterotrait–Monotrait criterion, while the structural model was evaluated through path coefficients, collinearity diagnostics, bootstrapping, and explanatory power. The measurement results demonstrated reliability, convergent validity, and discriminant validity across all constructs, with all 42 indicators retained. The structural model showed that Project Management Risk was the strongest predictor of Project Delay (β = 0.458, p < 0.001), followed by External Risk (β = 0.227, p = 0.0006), Human Resource Risk (β = 0.152), Financial Risk (β = 0.143), and Material Risk (β = 0.139). Technical/Design Risk and Equipment Risk did not demonstrate significant effects. Collectively, the seven risk dimensions explained 69.5% of the variance in Project Delay, with Project Management Risk contributing 43.6% of explained variance. The findings establish that road-project delays are principally associated with management and external conditions, supporting risk mitigation strategies that prioritize governance, coordination, monitoring, decision-making, and contingency planning.]]>
Copyrights © 2026
