Risk Management Strategies and Performance of National Government Constituency Development Funds Projects in Ruiru Constituency, Kenya

Risk management is critical to the successful implementation of development projects. This study investigated the influence of risk management strategies on the performance of National Government Constituency Development Fund (NG-CDF) projects in Ruiru Constituency, Kiambu County, Kenya. The research adopted a descriptive survey design, targeting 564 respondents involved in 94 NG-CDF projects. Using stratified random sampling, 234 participants were selected, and data were collected through structured questionnaires. The study focused on four key risk management strategies: risk acceptance, risk transference, risk avoidance, and risk reduction. Descriptive and inferential statistics, including regression analysis, were employed using SPSS. The findings indicated a high response rate of 77.35%. Descriptive statistics showed moderate to strong agreement on the use of risk strategies, with mean scores ranging between 3.18 and 3.71 across variables. Inferential analysis revealed that risk management strategies had a statistically significant impact on project performance. The regression model showed a strong correlation (R = 0.965) and high explanatory power (R² = 0.931), indicating that 93.1% of the variance in project performance was explained by the four risk strategies. ANOVA results confirmed the model’s significance (F = 591.782, p < 0.001). Among the predictors, risk avoidance (β = 0.741, p < 0.001) and risk reduction (β = 0.173, p = 0.012) had significant positive effects. However, risk acceptance and transference were statistically insignificant (p > 0.05). The study concluded that effective application of risk avoidance and reduction strategies is crucial in enhancing the performance of NG-CDF projects. It recommended institutionalizing structured risk management frameworks and capacity-building initiatives. These findings provided valuable insights for policymakers and project implementers seeking to optimize project outcomes in resource-constrained environments