Effect of Knowledge Management on Performance of Small and Medium Enterprises in Kisumu City, Kenya,

Abstract

Knowledge management is a relatively new discipline in management; it is practiced in businesses including Small and Medium Enterprises (SMEs). Globally SMEs suffer a high failure rate of more than 50% in the first five years of coming into existence, in Africa 70% and in Kenya 60% of SMEs fail within their first three years of operation. Past studies have outlined various reasons for business failure, but no known studies have examined the effect of knowledge management on performance of SMEs in Kisumu City. The study area was chosen because of the 34% failure rate of SMEs in Kisumu City. The purpose of this study was to establish the effect of knowledge management infrastructure, processes, and role of knowledge management in performance of SMEs in Kisumu City, the specific objectives were to identify whether knowledge management infrastructure was in place in SMEs, to examine if knowledge management processes were used in SMEs, and to establish the role of knowledge management in contributing to performance of SMEs in Kisumu City. The independent variable was knowledge management with Knowledge Management Infrastructure (KMI) and Knowledge Management Processes (KMP) as its dimensions while the dependent variable was Organization Performance (OP) with profitability and sales growth as its dimensions. The researcher used cross sectional survey design suited for obtaining data at a defined time to conduct a survey in a sample population of 324 from a target population of 2047 SMEs chosen using simple random sampling technique. A questionnaire was administered to key informants of the SMEs. Reliability was tested using the test-retest technique; a Cronbach's alpha coefficient of 0.82 was calculated, suggesting a high internal consistency. Validity was tested using the predictive method; a Pearson's correlation coefficient of 0.79 was obtained which showed evidence of validity. Descriptive statistics was used, the mean for KMI was 3.46, standard deviation (SD) of 0.82 and 24% variability meaning that majority of responses in the variable KMI were neutral, the mean for KMP was 3.52, SD of 0.72 and 20% variability meaning that majority of responses in the variable KMP were in agreement, the mean for the OP was 3.33, SD of 0.74 and 22% variability in the responses meant that most responses were neutral. Inferential statistics was done using Spearman's rank correlation, the results show that there was positive p (Rho) value of 0.67 between KMI and KMP; a positive p value of 0.33 between KMI and OP; and a positive p value of 0.37 between KMP and OP, all showing a moderate association. The study concluded that KMI was underdeveloped, KMP were underused, and knowledge management contribution to organisation performance was minimal in SMEs in Kisumu City. The researcher recommends that SME owners improve knowledge management infrastructure by acquiring low cost ICT tools; that SME owners and employees acquire and continuously update their skills on the use of ICT tools and processes; that SMEs include knowledge management as a function in their management activities. The study may be significant in providing new insights on knowledge management practices in SMEs in Kisumu and contribute to the little knowledge management literature there is in SMEs in general.