Effect of working capital management on financial performance of manufacturing firms in Kenya
Nyabenge, Vincent Oyoko
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The main purpose of this research was to establish the effect of working capital management on financial performance of manufacturing firms in Kenya. In addition, this study sought to determine the effect of specific working capital components on profitability of manufacturing firms in Kenya. This study employed panel data methodology and a population constituting nine manufacturing firms in Kenya was examined. The data for the study was derived mainly from secondary data sources including Capital Markets Authority library and Nairobi Securities Exchange library. The results from regression analysis indicated that only 26% of variations on financial performance of manufacturing firms could be attributed to working capital management and the remaining portion being influenced by other factors outside the scope of this study. This study further revealed that working capital variables accounts collection period, inventory conversion period and average payables period were inversely related to financial performance as was measured by Return on Assets. This implies that effective working capital management policies may be implemented to improve financial performance of manufacturing firms. This study utilized a number of regression models with each model regressing each working capital variable against the Return on Asset. An overall regression equation that constituted all the relevant working capital variables subject to a set of control variables was used to study the variations in return on assets. The various regression models produced different results each time the regression was conducted with individual working capital variables. Results for this study was obtained using SPSS tool. Multiple correlation analysis was performed with each of the unique models to examine the significance of relationship amongst the various independent variables and the dependent variable. With all the variables incorporated in one model, multiple correlation co-efficient was observed to be 63%. The raw data obtained from financial reports of the firms under study were analyzed using Ms Excel spreadsheets after which regression analysis was performed with the aid of SPSS.