Now showing 1 - 5 of 6
- ItemValue of application of insights from Big Data Analytics on transformation of agriculture: case of farmers subscribed to Mkulima Techie Kenya(Strathmore University, 2021) Okumu, MillicentThe application of big data analytics in agriculture is a revolution that has the potential to transform agriculture from being process driven to being data driven. Transformation of agriculture is defined as a process that involves gradual shifts in the production, from a traditional concept to a modern one resulting in change from a subsistence oriented monoculture system to a diversified and market oriented production system. The objectives of the study were to demonstrate the application of Big Data Analytics, determine the effect of usage of insights from Big Data Analytics and to determine the barriers in application of Big Data Analytics within a smallholder farmer setting. The study applied a mixed methods approach to investigate the value big data analytics has on transformation of agriculture. Data was collected using structured questionnaires from 282 respondents and key informant interviews. The inferential analysis tools applied included correlation analysis and logistic regression analysis. From this study, the findings reveal that there was a significant association between insights from big data analytics and value derived which facilitated transformation of agriculture in terms of income and yield for farmers. For the practitioners, researchers and policy makers in the agricultural industry this study provide guidelines to mitigate challenges in implementation and contributing to the broader discussion on the opportunities provided by a data driven agricultural industry. The limitations also help uncover future research courses in order to achieve better knowledge.
- ItemThe Effect of adoption of agricultural sustainable intensification practices on the Mwea rice farmers’ yields and income in Mwea Irrigation Scheme(Strathmore University, 2021) Ndung’u, Joseph MainaThe purpose of this study was to investigate the effect of adopting agricultural sustainable intensification practices with relation to rice farmers’ yields and income with the aim of increasing rice yields and profitability and ultimately reducing rice imports in Kenya. The study was quantitative and analysed using descriptive statistical methods, the data collected was mainly quantitative since it was mostly numerical and discrete. The study was a cross-sectional one and survey research strategy was used. The study used stratified sampling method (i.e. adopters’ vs non-adopters) and examined a sample of 400 small scale rice farmers out of the 3,200 active farmers derived from the irrigation scheme. The study used both primary and secondary data and the primary data was collected using questionnaires to guide the interviews on the respondents. Simultaneously the secondary data was mainly from journals, periodicals, textbooks and reports by relevant institutions. The data was analysed statistically by use of OLS model with the STATA software and results were presented descriptively as mean, mode, median, percentages and frequencies presented in graphs, tables, charts, percentages and cross tabs.
- ItemAssessing psycho-social, socioeconomic and institutional characteristics that influence adoption of climate smart agriculture in Taita Taveta County, Kenya.(Strathmore University, 2021) Godino, Mwasaru MwaghaniaAdoption of Climate Smart Agriculture practices remains key policy agenda in Kenya especially in the wake of climate change and increased food insecurity. This research adopted an integrative approach in examining how psycho-social, socioeconomic and institutional characteristics influence adoption of Climate Smart Agriculture (CSA) in Taita Taveta County, Kenya. The study applied the Theory of Planned Behaviour theoretical framework with Multivariate Probit Modelling and Structural Equation Modeling in assessing small holder farmer’s adoption decisions making process to CSA. The study showed there is no significant difference between, socioeconomic, institutional characteristics and adoption of Climate Smart Agriculture practices. Socioeconomic characteristics such as farm income; farmer group membership were found to increase the probability of adoption of CSA. While Institutional characteristics such as extension service, input subsidies and national government support also increase the likelihood of adoption rate among small holder farmers. The result further showed that farmer’s perceived behavioral control and personal attitudes significantly influence, the farmer intention to adopt a number of CSA practices within the household. These results mean that efforts to promotes adoption of Climate Smart Agriculture practices should concentrate on empowering farmers through support and resources mobilization to increase farm income, access to quality extension service, institutional support and general improvement of farmer’s awareness and knowledge to change their perception and attitude towards adoption of climate smart agriculture.
- ItemFactors affecting the development of dairy cooperatives in Kenya: a case study of Kiambu County(Strathmore University, 2021) Mugwe, Peter GithinjiCooperatives societies are part and parcel of an increasing number of people in formal and informal employment the world over. The study sought to establish factors affecting the development of Dairy Cooperatives in Kiambu County, Kenya. The objectives of the study were to: find out the effect of adoption of technology on the development of Dairy Cooperatives; evaluate the effect of financial access on the development of cooperatives; find out how managerial skills affects the development of Dairy Cooperatives in Kiambu County and; determine how the participation of members affect the development of Dairy Cooperatives in Kiambu County. Grounded on the Social Capital and Resource-Based Theory, this study adopted the descriptive research design. In this study, the target population was 59,635 registered Dairy Cooperative members while the sample size was 398 respondents who were picked via stratified random sampling. Data collection involved questionnaires that contained 5-point scale Likert-type statements. Descriptive and inferential statistics were carried out. In this case, tests such as central tendency (mean), frequencies, percentages, standard deviation in addition to Pearson and regression analysis were utilized. The findings show that the factors under investigation have significant influences on development of dairy cooperatives. This is evidenced by positive and statistically significant relationship between technology adoption, managerial skills & leadership; access to finance; member's participation to the development of dairy cooperatives. These findings show that technology adoption showed the strongest relationship with development of dairy cooperatives. This was followed by member’s participation, access to finance, and managerial skills and leadership in that order. These findings are corroborated by results from multivariate regression analysis that shows that all the IVs statistically significantly predict the DV. These findings lead to the conclusions that the kind of managerial skills and leadership in dairy cooperatives affected their development. Access to finance also affected the level to which cooperatives funded their development activities. Affordable financing and increased member subscriptions affected the success of Cooperatives projects. Increasing members’ participation would also increase their buy in of the development projects of the dairy cooperatives; augmenting their sustainability. This would go on to enhance their development. The study recommends the need for Dairy Cooperatives to have robust management teams staffed with highly competent and experienced managers. The integrity of the firms should be established and regularly assessed to avoid corruption and mismanagement of the finances. Training was also necessary so as to enhance the capacity of managers and employees. This could be done in-house or sponsored in institutions of learning. There was also need to carry out thorough research before starting development projects so as to understand their riskiness and establish the requisite strategies to ensure their success. Partnerships with SMEs was also recommended since it could avail low-cost credit. Member participation should also be strengthened and embedded in all management processes of the Dairy Cooperatives so as to enhance their support of projects. Regular monitoring and evaluation was recommended so as to come up with strategies for correcting deviations from predetermined development objectives.
- ItemThe Effect of farmer chacteristics on entrepreneurial behavior of beekeepers in Kibwezi West Sub County, Makueni County(Strathmore University, 2021) Strong, Margaret MbesaAgriculture plays a major role in the Kenyan economy through its significant contribution to the GDP, a foreign currency earner, supplier of raw materials to the processing and manufacturing sector as well as contributing to the food security in the country. In addition, the sector supports rural livelihoods through farm entrepreneurship and farm-generated employment thereby alleviating poverty levels in the rural population. Beekeeping is an important form of farming especially in the ASAL regions of the country where there are frequent occurrences of crop failure. The beekeeping subsector in Kenya is unable to satisfy the growing demand of honey in local, regional and global markets, producing 25 per cent of the national potential. The study sought to focus on beekeeping farmers and investigated their entrepreneurial behaviour, in that despite the huge market opportunity to commercialize their farm enterprises, the farmers operate at a subsistence level. The study aimed at establishing the effect of farmer characteristics on entrepreneurial behavior among bee farmers in Kibwezi West sub-county, Kenya. The study’s specific objective was to evaluate the effect of socio economics, psychological factors, group participation, and beekeeping management practices, on entrepreneurial behaviour of beekeeping farmers in Kibwezi West Sub County, Makueni County. The study was guided by the human capital entrepreneurship theory and the McClelland’s human motivation theory. The study applied descriptive research design. The study utilized purposive sampling technique to select 272 beekeepers from a target population of 816 beekeepers in Kibwezi West subcounty. Data was collected using a pretested questionnaire. The study realized a response rate of 83 per cent. The primary data collected was analyzed by applying descriptive and inferential statistical analysis utilizing SPSS statistical software. Data was presented using tables. Regression results indicated that age, education, number of beehives, psychological factors, and extension participation, had a positive and significant effect on entrepreneurial behaviour. Psychological factors and extension participation had high significant influence on entrepreneurial behaviour whereas age, education and number of beehives had a marginal effect. The beekeeping farmers were found to have moderate entrepreneurial behaviour. The study therefore recommends that entrepreneurship development programs targeting beekeepers should prioritize the enhancement of psychological motivation levels of beekeepers namely economic motivation and market orientation, through training and market linkages. In addition, more opportunities for extension participation should be provided, specifically through peer learning via farm visits and practical demonstration of beekeeping management practices – these factors were associated with higher farmer extension participation.