Abstract
Despite the widespread recognition of change orders as critical impediments to project success, there remains limited empirical evidence employing advanced statistical techniques such as Partial Least Squares Structural Equation Modeling (PLS-SEM) to systematically evaluate the complex interrelationships among change-order causes, their propagation mechanisms, and their multidimensional impacts on construction project outcomes in Kano State. This study, therefore, evaluates the causes of change orders and their impacts on construction projects in Kano State, providing evidence-based insights to improve project performance by reducing unnecessary variations and enhancing change management practices. A quantitative research approach was adopted for data collection, while data analysis was conducted using SPSS and Structural Equation Modeling (SEM). The results revealed that client-related factors (β = 0.556, p < 0.001) and consultant-related factors (β = 0.326, p = 0.005) are the most influential drivers of change orders. Contractor-related factors (β = 0.297, p = 0.004) also showed a significant effect, indicating that contractor financial capacity and early involvement meaningfully shaped change-order outcomes. External factors, however, are statistically insignificant (β = 0.067, p = 0.495), suggesting that internal project dynamics remain the primary causes of change orders. The findings further indicate that client-related, consultant-related, contractor-related, and external factors collectively provide a robust explanation of the magnitude and nature of change-order impacts on construction project outcomes. The developed model accounts for 61.6% of the variance in change-order impacts, demonstrating strong explanatory power within the construction management context. Cost effects of change orders exhibit the strongest direct influence on overall impact (f² = 0.789), confirming that financial consequences dominate stakeholder perceptions of change-order severity, with cost overruns serving as the primary mechanism through which change orders negatively affect project success. External factors demonstrate negligible effects (f² = 0.005), further confirming their minimal contribution to change-order outcomes. The Q² values, ranging from 0.287 to 0.404 across all constructs, validate the model’s predictive relevance and its ability to reliably forecast out-of-sample observations. The findings provide evidence-based guidance for construction practitioners, project owners, and policymakers in Kano State to implement more effective change management frameworks, reduce the frequency and cost impact of change orders, and improve overall project performance.

Key words: Change orders, Construction projects, Kano State, Variation causes, Project performance, Change management