Abstract: This study aimed to assess the effect of project risk management practices on the performance of Indongozi SACCO Nyamasheke Karambi Branch. Data was collected using structured questionnaires for quantitative insights and semi-structured interviews for qualitative perspectives, complemented by secondary data from SACCO reports and documents. Using descriptive statistics to summarize trends and inferential statistics, specifically regression analysis, to test hypotheses the collected data was analyzed using SPSS version 27. The regression results indicate that all components of project risk management have a statistically significant positive effect on performance at Indongozi SACCO Nyamasheke Karambi Branch. Specifically, project risk identification (B = 0.214, t = 2.649, p = 0.008), project risk analysis (B = 0.505, t = 7.081, p = 0.000), project risk response planning (B = 0.311, t = 4.325, p = 0.000), and project risk monitoring andcontrol (B = 0.329, t = 4.736, p = 0.000). Among these, project risk analysis has the strongest effect, followed by risk response planning, risk monitoring and control, and risk identification. In conclusion, Since the p-value is less than 0.05, all null hypotheses were rejected confirming that project risk management practices have significant effects on performance of Indongozi SACCO Nyamasheke Karambi Branch. It is recommended that Indongozi SACCO Nyamasheke Karambi Branch further strengthens and standardizes these practices to enhance project efficiency and sustainability. Future studies should explore other influencing factors such as leadership, technology use, and financial management to broaden understanding of SACCO performance.

Abstract: The purpose of this study was to examine how risk management strategies affected the timeliness and quality of the Zaria Court building project in Kigali, Rwanda. Stratified random sampling with Slovin’s method yielded a sample size of 128 from a population of 188 project workers. Interviews and structured questionnaires were used to gather data, which was then analyzed using theme analysis for qualitative replies and SPSS for quantitative data. All four risk management techniques had a favorable and statistically significant influence on the final product. R² = 0.703, p < 0.001 in the regression analysis demonstrated that the model accounted for 70.3% of the variation in project performance. To be more precise, project performance was significantly impacted by project risk identification (β = 0.301, t = 2.89, p = 0.032). The strategy for managing risks was also shown to be significant (β = 0.215, t = 1.73, p < 0.001), as was the control and monitoring of risks (β = 0.361, t = 1.89, p = 0.007). Furthermore, project performance was greatly affected by contingency planning (β = 0.321, t = 1.91, p < 0.001). The research concludes that effective risk management measures are crucial for infrastructure projects to be completed successfully. From these findings, project stakeholders should establish ongoing training programs to improve their risk identification and monitoring abilities, set aside enough funds for dynamic risk management planning, improve communication channels to disseminate risk information quickly, and update and test backup plans frequently using simulations and stakeholder input.

Abstract: This study aimed to assess the effect of project risk management on performance of Rwanda Urban Development Project (RUDP) in Rwanda. A descriptive and correlational research design was applied, and data analysis was conducted using SPSS to examine the relationship between project risk management practices and project performance. The R-value of 0.862 signifies a strong relationship between the independent variables and project performance, as values above 0.7 indicate a strong effect. The R-Square value of 0.742 indicates that 74.2% of the variations in project performance are explained through project risk identification, risk analysis, response planning, monitoring and control. A unit increase in project risk identification results in a 0.249 increase in project performance (β = 0.249, t = 4.195, p = 0.000), confirming its significance. A unit increase in project risk analysis leads to a 0.217 increase in project performance (β = 0.217, t = 2.771, p = 0.006), reinforcing its role in reducing project uncertainties. Project risk response planning contributes positively, with a unit increase leading to a 0.272 rise in project performance (β = 0.272, t = 3.151, p = 0.002), demonstrating its importance. Likewise, project risk monitoring and control positively impacts project performance. With a unit increase resulting in a 0.204 increase (β = 0.204, t = 3.029, p = 0.003). The study recommended that project managers establish a detailed scope definition framework and ensure strict adherence to guidelines throughout execution to prevent scope creep and maintain project focus.