Thesis:

Assessment of supply chain performance on procurement Management in Baringo county, Kenya

Procurement practices play a vital role in enhancing the efficiency and performance of both public and private organizations globally. In Kenya, county governments continue to experience financial losses due to inefficiencies in procurement processes. Additionally, the reliance on traditional procurement methods has contributed to persistent inadequacies in procurement management. This study aimed to examine the impact of supply chain performance on procurement management, focusing on Baringo County. The specific objectives were to determine the effect of supplier management on procurement management, assess the influence of transport logistics, and evaluate the role of storage logistics in procurement management within the county. The research was guided by the Social Network Theory, Game Theory, and the Stochastic Inventory Model. A descriptive research design was employed, targeting 67 county officers directly involved in procurement activities. A census approach was used to include all 67 officers in the study. Data was collected using structured questionnaires and analyzed using the Statistical Package for Social Sciences (SPSS) version 22. Correlation analysis was conducted to establish the relationship between supply chain performance and procurement management. Descriptive statistics, including frequencies, percentages, means, and standard deviations, were used to summarize the data. The findings were presented in frequency tables and graphs for ease of interpretation. The study established that supplier management, transport logistics, and storage logistics significantly contribute to improving procurement management in Baringo County, as demonstrated by both descriptive and inferential statistical analyses. Supplier management showed a Pearson correlation of 0.518 and a regression coefficient of 0.433, indicating its significant contribution to cost savings and operational improvements. Transport logistics exhibited an even stronger correlation of 0.563 and a regression coefficient of 0.220, underscoring the importance of timely deliveries and efficient fleet management. Storage logistics, with a correlation of 0.449 and a regression coefficient of 0.432, was found to be crucial in ensuring adequate inventory control and reducing inefficiencies. The study’s R-squared value of 0.463 indicates that these three variables together explain 46.3% of the variation in procurement management. Conclusion of the study is that procurement management in Baringo County is heavily influenced by supplier management, transport logistics, and storage logistics Based on these findings, it is recommended that Baringo County focus on strengthening supplier relationships, adopting modern transport and storage technologies, and investing in ongoing training for procurement personnel to enhance performance and efficiency.