Working Capital Management and Profitability of Textile and Apparel Firms in Kenya

Abstract

Abstract The textile and apparel industry in Kenya contributes 7% to the country’s export earnings. However, it faces profitability challenges due to increasing competition both locally and internationally. This study examined the impact of working capital management on the profitability of textile and apparel companies in Kenya, as local firms struggle to offer competitively priced products, resulting in declining profits. Specifically, the study assessed the effect of accounts receivable management, accounts payable management, cash management, and inventory management on profitability. The study was anchored on the Cash Conversion Cycle, Accounts Receivable Aging Analysis Model, Payables Deferral Period Model, Miller-Orr Model, and Economic Order Quantity Model. A correlational research design was adopted, targeting 75 finance managers in firms registered under the Kenya Association of Manufacturers. Given the small population, a census approach was applied. Data was collected using structured questionnaires, with a pilot conducted in Nairobi County. Cronbach's alpha for all variables was 0.801, confirming reliability. Data collection was done using the drop-and pick-later method and Google Forms across selected counties. The findings indicated that the overall mean score for accounts receivable management was 3.8466 with a standard deviation of 0.9882, suggesting that most textile and apparel firms in Kenya have fairly robust accounts receivable management practices. In addition, there was a moderate positive and significant correlation between accounts receivable management and profitability (r = 0.475, p = 0.000). The β value was 0.371, meaning that a unit change in accounts receivable management results in a 0.371 increase in profitability. For accounts payable management, the mean was 3.8624 with a standard deviation of 1.0215. There was a significant positive relationship with profitability (r=0.609, p=0.000) and a β value of 0.337. For cash management, the mean was 4.1772 with a standard deviation of 0.9537, showing a strong positive correlation (r = 0.817, p = 0.000) and a β value of 0.661. For inventory management, the mean was 4.0238 and the standard deviation was 1.0403, with a significant correlation (r = 0.723, p = 0.000) and a β value of 0.249. The model had an R² of 0.754. The study concluded that effective management of these components enhances financial performance. It recommends improving receivables monitoring, negotiating favorable supplier terms, adopting inventory control systems, and implementing cash flow forecasting.