Influence of Resosurce Allocation on Performance of Kigali Infrastructure Project

The study entitled effect of risk management on supply chain performance, a case study of Sulfo Rwanda Industries Ltd conducted for assessing four specific objectives such as: to assess the effect of risk identification on supply chain performance in Sulfo Rwanda Industries Ltd, to assess the effect of risk monitoring on supply chain performance in Sulfo Rwanda Industries Ltd, to assess the effect of risk control on supply chain performance in Sulfo Rwanda Industries Ltd, and to assess the effect of risk register on supply chain performance in Sulfo Rwanda Industries Ltd. This study guided by Decision theory and Transaction Cost Theory. The study also correlative design as intends to assess the effect in the context of correlation between risk management and supply chain performance. The study also qualitative design as intends to use qualitative data which collected from respondents using open questions (see the questionnaire). The study once again quantitative designed as intends to use quantitative data which obtained from the closed questions which addressed to the respondents. All primary data collected from Sulfo Rwanda Industries Ltd employees and management. This study has taken 581 staff of Sulfo Rwanda Industries Ltd of different branches in Kigali main headquarters, Rubavu and Kamembe Branch. A total of 237 people is found in the research, based on the sample size calculated using the Solvin formula presented. Data analysis used both descriptive and inferential statistics with a support of Statistical Package for Social Sciences (SPSS). The value of R (0.834) indicates a strong positive correlation between the combined predictors (risk Register, risk identification, risk monitoring, and risk control) and the dependent variable (Supply chain performance). The coefficient of determination (R Square) is 0.695, which means that approximately 69.5% of the variability in the dependent variable (Supply chain performance) can be explained by the combined influence of the four predictors. Risk identification has a coefficient of 0.269, indicating that a one-unit increase risk identification corresponds to a 0.269 increase in supply chain performance. Similarly, risk monitoring has a coefficient of 0.418, indicating that a one-unit increase in risk monitoring corresponds to a 0.418 increase in supply chain performance. Risk control has a coefficient of 0.018, indicating that a one-unit increase in risk control corresponds to a 0.018 increase in supply chain performance. Also, risk Register has a coefficient of 0.211, indicating that a one-unit increase in risk register corresponds to a 0.211 increase in supply chain performance all predictor variables have significant p-values, with risk identification (p<0.05), risk monitoring (p<0.05), Risk control (p<0.05) and risk Register (p<0.05) demonstrating statistical significance. Sulfo Rwanda is advised to prioritize the development of an inclusive risk identification process involving all stakeholders, establish a robust risk monitoring system with defined KPIs and proactive techniques, formulate a comprehensive risk control strategy with clear responsibilities, and maintain an organized and current risk register linked to mitigation actions, leveraging technology for improved supply chain performance.