Abstract: The general objective of this study was to assess the effect of logistics management practices on supply chain performance at Solektra Rwanda, located in Kigali, Rwanda. Data was collected using questionnaires, interviews, and documentation methods. Data analysis was conducted using statistical tools including descriptive statistics such as mean and standard deviation, as well as inferential statistics such as correlation and regression analysis. Statistical analysis was performed using SPSS software to examine the relationship between logistics management practices and supply chain performance. The results indicate model summary for the effect of logistics management practices on supply chainperformance at Solektra Rwanda. The R value of 0.936 shows a very strong positive relationship between the combined predictors and supply chain performance. The R Square value of 0.877 means that transportation management, inventory management, warehousing management, and information flow management explained 87.7% of the variation in supply chain performance. The study concluded that logistics management practices significantly improve supply chain performance at Solektra Rwanda by strengthening delivery reliability, stock availability, warehouse efficiency, and information coordination. The study recommended that Solektra Rwanda should reinforce route optimization, stock visibility, warehouse layout organization, and real-time logistics information sharing to improve supply chain performance.

Abstract: The general objective of this study was to assess the effect of logistics management practices on performance of
pharmaceutical industry in Rwanda. Descriptive research design used to analysis information on a variety of issues, and correlational research design examined the links that exist between variables under study. Data analysis was performed through SPSS version 25. The study presents the model summary for regression analysis. The R value of 0.896 indicates a strong positive correlation between predictor variables and dependent variable, suggesting that all combined management practices are closely related to the performance of Rwanda Medical Supply Ltd. The R-square value of 0.803 implies that approximately 80.3% of variance in pharmaceutical industry performance is explained by the combined effects of the three management practices. Information flow management has a coefficient of 0.424, indicating a strong positive effect on performance of Rwanda Medical Supply Ltd., which is statistically significant (p = 0.000 < 0.005). Warehouse management shows a coefficient of 0.182, also significant (p = 0.016< 0.005), reflecting a positive effect on performance of Rwanda Medical Supply Ltd. Transport management has a coefficient of 0.353, indicating a substantial and significant effect on the performance of Rwanda Medical Supply Ltd. (p = 0.000 < 0.005). All correlations are statistically significant at the 0.05 level. Rwanda Medical Supply Ltd. should implement advanced information management systems, such as integrated supply chain management software, to streamline communication and data exchange between departments and stakeholders.