Investigating knowledge transfer for entrepreneurship in Kenya's agricultural sector
Ngugi, William Wanyoike
MetadataShow full item record
Agriculture remains the backbone of Kenya's economy. About 80% of the population depends directly or indirectly on agriculture for both food and employment. Despite this, the small scale farmers have largely remained stagnant in productivity and tended to focus on subsistence farming. This study investigated the knowledge transfer predictors for entrepreneurship in Kenya's Agricultural Sector. The objectives were, to first determine the knowledge and skills gap in the agricultural sector in Kenya, to determine the relationship between these knowledge gaps and successful knowledge transfer (productivity) in the agricultural sector in Kenya and to find out the moderating effect of hindrances on the relationship between knowledge gaps and successful knowledge transfer in the agricultural sector in Kenya. The knowledge predictors identified have shown that with an effective knowledge transfer from various existing agricultural and research institutions as well as learning institutions, it is possible for the farmers to not only increase their production, but it is also possible to turn their farming activities into commercial enterprises, small, medium and large farming enterprises. The initial stage of the study used exploratory design followed by descriptive design. Data was collected through self – administered questionnaires. The questionnaires were structured to minimize variability. The sample set was clustered and convenience sampling applied resulting in a sample size of 60 respondents (30 small-scale farmers and 30 large scale farmers from Laikipia, Kiambu and Nakuru counties, purposively sampled). The data was analyzed using descriptive statistics and inferential statistics in particular regression analysis. The study established that a relationship exist between knowledge gaps and knowledge transfer. Five predictors of knowledge transfer were identified. The most significant predictors of knowledge transfer according to their impact factor were: skills transfer from the large scale farmers to small scale farmers, access to research centers (KARl) and extension service providers like Syngeta EA, Osho chemicals, Amiran, Bayer EA, Twiga Chemicals, Kenya Seeds Company and others, access to information on agriculture relayed via TV and radio, education of the farmers and the courses pursued at college level. The study concludes that effective knowledge transfer is tenable through such mediums like the government agricultural officers, mass media and agricultural learning institutions which will turn the farming activities of small-scale farmers to commercial enterprises. Since implementing the predictors of knowledge transfer would entail a financial cost, a key recommendation to other academicians is to determine the return on investment in knowledge transfer, by putting into practice the theoretical aspects identified.