RISK MANAGEMENT PRACTICES AND SUPPLY CHAIN PERFORMANCE IN COUNTY GOVERNMENTS OF WESTERN KENYA

Abstract

Risk management has drawn attention to procurement entities globally due to continuous changes in the supply chain function. Poor risk management strategies may attract issues such as lack of risk decision-making, accountability, risk identification, risk assessment, mitigation, and monitoring. Many studies conducted on risk management practices on supply chain performance produced conflicting results, since some had positive. In contrast, others had a negative influence and, therefore, the need for conducting the current study. The purpose of the study was to establish the influence of risk management practices on the supply chain performance of County governments of western Kenya. The study specifically determined the influence of risk identification on supply chain performance, to establish the influence of risk assessment on supply chain performance, to examine the influence of risk mitigation on supply chain performance, and to assess the influence of risk monitoring on supply chain performance in County governments of western Kenya. The study was guided by the economic theory of agency, resource-based and institution theory. The study used a descriptive research design. The target population was 150 employees comprising procurement officers, logistics managers, and directors of audit service, quality assurance, and finance officers from Vihiga, Kakamega, Bungoma and Busia Counties. The study used a census sample strategy, focusing on all 150 employees. Primary data were gathered for the study utilizing closed-ended questionnaires. Secondary data was obtained by analyzing auditors' reports. Both descriptive and inferential statistics were used to analyze the data. Inferential statistics were examined using the Pearson product moment correlation and the linear regression model. The correlational results showed that risk assessment, identification and mitigation had a significant positive association since their p-values were less than 0.05. In contrast, risk monitoring had an insignificant positive association with supply chain performance. The regression model results of the study showed that risk identification had a coefficient of 0.191, and a p-value of 0.010, risk assessment had a coefficient of 0.214, with a p-value of 0.003 and risk mitigation had a coefficient value of 0.162, with a p-value of 0.011, meaning that risk identification, assessment and mitigation had a significant positive influence on supply chain performance. On the other hand, risk monitoring showed an insignificant positive influence on supply chain performance with a Beta coefficient of 0.131 and p- value of 0.246 which was greater than 0.05 significant level, meaning monitoring risks doesn’t influence the supply chain performance significantly. It was recommended that county governments should perform a thorough screening of suppliers, integrate their procurement processes, conduct a review of compliance to ensure compliance risks are reduced and risk management strategies be implemented