| dc.description.abstract | Performance of public hospitals is becoming a major concern to Kenyans. Forte five percent of Kenya's population are living below the poverty level and access to basic quality health care is a luxury to them, opting for public hospitals. This has put pressure on availability of drugs in the pharmacies. Public hospitals are currently facing the problem of balancing between overstocking and understocking of drugs. The main objective of this study was to determine the effect of inventory management practices on operational performance of public hospitals in Siaya County, Kenya, with supply chain performance as the moderating variable. The study was guided by the following specific objectives: to establish the effect of inventory categorization on operational performance; to determine the effect of demand forecasting on operational performance; and to establish the effect of Just-in-Time on operational performance of public hospitals in Siaya County. This study was anchored on Resource Based View Theory, Network Perspective Theory and Competitive Advantage Theory. The study adopted cross-sectional survey design with a target population of 106 employees. The study used a sample size of 84 employees based on Yamane formula. The study adopted stratified proportionate and simple random sampling in selecting the 84 respondents across the six hospitals. This study used structured questionnaires and interview guides to collect primary data. Reliability was tested using split half analysis while validity was tested using expert judgement at an index of 0.70 Cronbach's Alpha coefficient. Descriptive statistics were analyzed using frequency percentage, mean and standard deviation. Inferential statistics were analyzed using regression and correlation analysis. The hypotheses were tested using Pearson Chi¬Square test of independence at a significance level of 0.05. Statistical Package for the Social Science (SPSS) version 24 was used to aid in analyzing the data. The study found that inventory management practices have statistically significant effect on operational performances (f=I 0.854; R2 = 0.667; p:S0.003 at 8 :S 0.05). The study concludes that inventory management practices have statistically significant effect on operational performances of public hospitals in Siaya County. However, the individual attributes of inventory management practices have differential contribution on operational performance. The trend indicates that demand forecasting contributes more (/J=0.536; p:S0.030), followed by inventory categorization (/J=0.465; p:S0.040) then and lastly Just¬in-time practices (/J=0.417; p:S0.030) respectively in the improvement of operational efficiency of public hospitals in Siaya County. The study also concludes that there is a statistically significant moderating effect of supply chain performance on the relationship between inventory management practices and operational performances of public hospitals in Siaya County from (F=I0.854; R2 = 0.667; p:S0.003 at 8 :S 0.05) to (F=12631; R2 = 0.801; p :S 0.002 at 8 :S 0.05). However, the individual attributes of inventory management practices have differential contribution on operational performance. The trend indicates that demand forecasting contributes more (/J=0.586; p:S0.003), followed by inventory categorization (/J=0.497; p:S0.004) then and lastly Just-in-time practices (/J=0.463; p:S0.004) respectively in the improvement of operational efficiency of public hospitals in Siaya County. The government regulation to use Integrated Financial Management Information System (IFMIS) in vendor sourcing, supplier selection, procurement and payments has tried to streamline the inventory management in public hospitals removing heavy bottlenecks in the acquisition of medical inventory thus a niche in efficient service delivery, This is not always true though since in some situations, the IFMIS platform often hangs or is shut by some ill intended personnel in the control rooms. The study recommends that inventory Managers should categorize inventory with accurate demand forecasts that are ordered on a Just-in-Time basis. | en_US |