EFFECT OF INVENTORY CONTROL SYSTEMS ON SUPPLY CHAIN PERFORMANCE AT KITUI FLOUR MILLS, MOMBASA COUNTY
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Abstract
The purpose of the study was to determine the effect of inventory control systems on supply chain performance in Kitui Flour Mills in Mombasa County. The study sought to find out the effects of Just in Time (JIT), ABC Analysis, Economic Order Quantity (EOQ), and First in, First Out (FIFO) methods on supply chain performance in Kitui Flour Mills in Mombasa County. The study employed a descriptive research design to comprehensively understand the behavioral patterns and processes related to inventory control. The target population consisted of 200 respondents from various departments, including finance, procurement, information technology, logistics, operations, and stores in the firm. A stratified random sampling technique was used to ensure the selection of a representative sample of 133 respondents. Primary data was collected using a structured questionnaire, while secondary data was gathered from existing sources. Data analysis was done through use of percentages, mean, standard deviation, and multiple linear regression using the Statistical Package for Social Science (SPSS). Ethical considerations included ensuring informed consent, participant anonymity, privacy, and adherence to ethical standards. The study findings revealed significant positive relationships between all four inventory control systems and supply chain performance. All four independent variables have positive B coefficients (JIT: 0.539, EOQ: 0.469, FIFO: 0.281, ABC Analysis: 0.159). This indicates a positive relationship between each inventory control system implementation score and the predicted performance. JIT has the highest positive relationship (0.539) between JIT implementation and supply chain performance. After JIT, EOQ had the second-highest positive coefficient (0.469) suggesting a positive association between EOQ implementation and performance. Higher EOQ implementation scores are linked to improved performance. The positive FIFO (0.281) coefficient indicates a positive relationship between FIFO implementation and performance. The mean score for various aspects of ABC analysis implementation ranged from 3.00 to 3.72, highlighting its perceived effectiveness in inventory management. Based on the results, the study recommends that organizations consider adopting JIT principles to reduce lead times, lower inventory holding costs, and improve responsiveness to demand fluctuations. Companies can also optimize order quantities through EOQ models and can minimize total inventory costs while ensuring adequate stock levels. Adhering to FIFO principles can help reduce wastage and improve inventory accuracy, potentially leading to better inventory turnover. Lastly, ABC Analysis can contribute to overall supply chain optimization by enhancing inventory control through classification.
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