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Empirical analysis of microfinance institutions support systems on performance of dairy farmers in Kakamega County, Kenya
(Mount Kenya University, 2021-10-08) Onyango, Sangoro Oscar; Prof. George Gongera
Efforts by the National Government and County Government of Kakamega have been directed
toward improving dairy performance in the County. The county government has partnered with
some MFIs to support dairy farming in the county in attempt to optimise milk supply and thus
achieve dietary diversity, which is one of the 2030 Agenda For sustainable development (SDGs),
as the county as well as the entire world rely on milk and dairy products from other counties.
However, little attention has been directed toward the relationship between MFI support systems
and the performance of smallholder dairy farmers in Kakamega. This study sought to find out an
empirical study on microfinance institution's support systems' influence on the performance of
dairy farmers in Kakamega County. The study's specific goals were to look into the impact of MFI
technical support systems on dairy farmers' performance in Kakamega County, assess the influence
of the MFI credit system on the performance of dairy farmers in Kakamega County, establish the
influence of MFI micro insurance support systems on the performance of dairy farmers in
Kakamega County, establish the influence of MFI saving systems on the performance of dairy
farmers in Kakamega County and determine the influence of government policy on the relationship
between microfinance institution support systems and the performance of dairy farmers in
Kakamega County. The following three theories guided the research:knowledge-based theory,
prospect theory, credit rationing theory and expected utility theory. The researcher identified
Kakamega County as the target region of study because it has low milk production despite huge
due potential in dairy farming. The study target population was1310 dairy farmers spread in 12
sub-counties as obtained from 17 Microfinance institutions in the county. The study sample size
was 297 .Primary data was collected using questionnaires and an interview guide. Secondary data
was obtained using document analysis. A pilot study was conducted. The findings were presented
using tables, models, and charts. The Micro Finance Institutions' processes have a considerable
impact on the performance of dairy producers in Kakamega, according to the data. Microfinance
technical systems have played a key role in dairy farming performance because they improve the
quality and quantity of dairy products by upgrading production technology. Micro Finance
Institutions' credit systems had a positive contribution to the dairy performance. MFIs micro insurance systems had a significant contribution to dairy farming through prompt compensation.
MFI saving had a significant positive contribution to dairy farming performance. Government
policies had substantial regulating variables on the association among dairy farming performance
besides Micro Finance Institutions saving as well as technical systems. The study recommended
that the Micro Finance Institutions need to collaborate with other organization and institution both
government and non-government to ensure that farmers receive technical systems which will
support dairy farmers.
Relationship of turnaround strategies on organizational performance of KCB Bank and Uchumi Supermarket
(Mount Kenya University, 2021) Kimemia , Gathiru Martin; Dr. A.H. Mwakamah Khamah
This was a study on relationship of turnaround strategies on organizational performance of enterprises in Kenya: A case of KCB Bank and Uchumi supermarket. Specific objectives crafted for the study were: to investigate the the way human, finance, coporate planning and marketing turnaround strategies relate to organizational performance in KCB Bank and Uchumi Supermarket. The study was significant because it compared vital nexus between turnaround strategies and organizational performance in KCB bank and Uchumi supermarket. The study was carried out using open ended, closed ended questionnaires and interviews. The theories underpinning the study were resource based view, dynamic capabilities theory, open systems theory, and competitive theory. Empirical studies were carried out per objective. The target population was 450 and 660 Uchumi and KCB staff respectively.The sample sizecalculated using Nassiuma’s (2009) formula was 82 and 87 Uchumi and KCB staff respectively making a total of 169 respondents). Causal research design was used. The validity of the questionnaire was examined using the face and content validity while the reliability was examined using the Cronbach alpha coefficient. Data was analysedusing descriptive statistics (means, frequency distribution and standard deviations) and inferential statistics (linear correlation and multiple linear regressions). There were significant relationship between corporate planning and organizational performance in KCB bank and Uchumi Supermarket since F (1, 139) = 5.356,p=0.022<0.05, no significant relationship between finance strategies and organizational performance in KCB bank and Uchumi Supermarket since F (1, 139) =0.019, p=0.892>0.05, no major relationship between HR strategies and organizational performance based in KCB and Uchumi supermarket since F (1, 139) =0.290, p=0.591>0.05, no significant relationship between marketing strategies and organizational performance in KCB bank and Uchumi Supermarket since F (1, 139) =0.760, p=0.385>0.05.Key recommendation were for FMCG retail outlets (uchumi supermarket) to implement turnaround strategies starting with marketing followed by finance, human resource and finally corporate planning turnaround strategies. However, to finance retail outlet (KCB Bank) corporate planning is a priority focus followed by human resource then marketing and finally finance strategies.
Improving the accessibility of digital content via Mobile technology: a case study of Mount Kenya University
(Mount Kenya University, 2022-08-01) Githinji,Ann; Prof. Gregory Wanyembi
Globally, Higher Education Institutions (HEI) have embraced the use of mobile technology in the delivery of instructional resources which has promised multiple benefits in digital or blended learning, HEIs are facing the challenge of high internet tariffs. The current study sought to improve the accessibility of digital content via mobile technology within limited Internet connectivity contexts. The case study was Mount Kenya University in Kenya. In the university, training had been done for both students and educators on how to access digital content but still, both students and educators have been experiencing challenges in getting cost-effective, high quality education, and the accessibility of reading materials. The accessibility of digital content was a problem because of internet connectivity and bulky content. This research contributes to improving the accessibility of digital content via mobile technology by coming up with a mobile-based model. Objectives were to establish the factors that influence mobile technology, Challenges, and their effects on the learners, develop a mobile-based model, and then validate the model. The study was guided by the Technology Acceptance Model (TAM). TAM demonstrates the prediction of the usability and acceptance of new technology. The study used a quantitative research approach within which a descriptive survey research design was adopted. The target population was 15123 individuals comprising of 15,000 students and 123 were educators/ ICT staff who accessed digital content in the academic year 2018/2019. In sampling methods, this research used a case study of Mount Kenya University; students, staff, and educators as population. In this study, Slovin’s formula was used to get the sample population of 390 out of the target population of 15,123 members. Simple random sampling was the procedure used. The findings showed that there is a statistically significant relationship between internet connectivity, type of mobile technology, user literacy, data caching, and eLearning policy had a significant effect on the accessibility of digital content. The variables were statistically significant. The adjusted R squared was 0.862 indicating that 86.2 percent of the total variation of accessibility of digital content can be explained by Internet connectivity, e-learning policy, type of mobile technology, data caching, and user literacy. The study then went ahead to develop a mobile-based e-learning model. The mobile-based model used a WIFI router device which is not internet supported as an alternative to a wired internet connection where students and educators access digital content from the mobile sub-server which was not connected to the internet through their mobile technology The findings showed that the use of mobile-based e-learning (m-learning) in universities will greatly improve access to digital content and hence e-learning. The study recommends the use of m-learning as it will provide alternative means of optimizing Internet connectivity. This research makes a contribution to m-learning to universities, policymakers involved in testing, designing, and implementation, and scholars.
Text mining model for retrieval of explicit knowledge at Kenya coastal development project, Mombasa
(Mount Kenya University, 2022-09-06) Onkundi,Ednah Nyakerario; Raymond Wafula Omgus PdD
The study investigated the prospects of applying a Text Mining model in the retrieval of explicit knowledge at the Kenya Coastal Development Project (KCDP). The study’s main objective was to establish how a Text Mining model could be used in explicit knowledge retrieval at KCDP. The study identified text-mining techniques that could be used to develop a text-mining model, evaluate the model to be able to retrieve explicit knowledge at KCDP. The study targeted staff of the agencies that constituted the KCDP project which included,
Kenya Marine and Fisheries Research Institute (KMFRI), Kenya Wildlife Service (KWS), State Department of Fisheries (SDF), Coastal Development Project (CDA), Department of Physical Planning, Kenya Forest Service (KFS) and National Environment Management Authority (NEMA). The study used the exploratory and experimental research design to be able to understand the research problem, answer the research objectives and questions. The total population of staff in the project was one hundred and fifty (150), out of which fiftytwo (52) were sampled. Purposive sampling was used to select samples from the representative groups that comprised the target population. Two methods of data collection were used namely; questionnaires and focus group discussion. The questionnaire was applied to members of staff in four major departments namely the top management, research and administration, knowledge management and finally the ICT department. The focus group discussion was applied to a special group in the knowledge management section. Content analysis was used to analyze the focus group discussions. Questionnaires were analyzed using the Statistical Package for the Social Sciences (SPSS) version 25 software. The use of questionnaires and focus groups were used to establish the current situation at the KCDP in terms of knowledge management systems in place and whether text mining could be used to retrieve explicit knowledge at KCDP. Text were collected from websites of organizations that took part in the KCDP project by using python libraries namely Python Request 2.22 and Beautiful Soup 3. The collected text was then summarized using text summarization algorithms used in the model like Luhnsummarizer, Lsansummarizer, Lexranksummarizer and Edmondsummarizer. After summarization topic, modelling was performed on the text collected using Latent Dirichlet Allocation (LDA) topic-modelling algorithm to create topics based on patterns in text. The model was then evaluated to establish its performance by measuring the four variables identified using precision and recall to measure accuracy, topic modelling to measure rate of similarity, and perplexity to measure evaluation of the model which gave a perplexity of -6.0455 from the text analyzed and modelled. It was concluded that text analysis could be used to analyze text and create explicit knowledge from both structured and unstructured data formats using the model. Future models should incorporate artificial intelligence into machine learning, so that semantics (i.e., English grammar) are deciphered and not only syntax of the language. The system should be willing to differentiate between “willing flesh” and “good meat”. The system should detect the intrinsic difference between the phrases “weak spirit” and “bad liquor”. This will help the system to avoid getting lost in translation via the use of synonyms and will incrementally rely on semantic, as facilitated by artificial intelligence.
A palm vein authentication implementation model For enhanced access of biometric systems: a case of Mount Kenya University Main Campus
(Mount Kenya University, 2023-06-20) Wambui,Boniface Mwangi; Dr. Joyce Gikandi
One of the crucial components that contributes to the efficacy and efficiency of information systems is system integrity. One security method used to increase system integrity is biometrics. The existing fingerprint system is prone to spoofing attacks, high FRR and FAR, tear and wear of the sensor scanner. The goal of this study was to look at the integrity issues that affect the security of biometric technologies in Kenyan higher education institutions, IT security factors, implementing a new model and validating it. The implemented contactless security model sought to solve the current security problems facing the current biometric system. The study's particular goals were to look into the IT security factors that influenced biometric system integrity, review the success and failures of present biometric systems in boosting learning institution integrity, and design and validate the model. The research was guided by the extended integrated system theory which consisted of contingency and management theory. Since the contactless model had been approved by security system specialists, the researcher used an experimental and descriptive research approach. The research subject was Mount Kenya University's faculty and employees. Stratified sampling provided a true depiction of the varied population. 300 randomly chosen employees from particular departments made up the study's target population, and 169 individuals were picked for the sample using simple random sampling. The Zetech University served as the site of the pilot study. In the study area, questionnaires were used to collect the data. The researchers employed an equation for multivariate regression. Analysis of Variance (ANOVA) was used to examine the model's fitness, with a 95 percent confidence level test of significance. From the findings a strong correlation coefficient of 0.792 was obtained on objective one. This showed that the model fitted well and their statistical relationship between the variables. The correlation coefficient between the variables was at 0.792, indicating that the constructed model was more efficient in terms of data integrity. One objective two the R2 of 73.4% indicated the data fitted the model well on the assessment the IT security metrics that influenced the integrity of biometric systems in higher learning institutions since it was greater than 50%. The experiment consisted of a control group having 15 participants. From the experiment the palm vein had an FRR of 93.33% while fingerprint had 60% which demonstrated superiority in authentication accuracy. On objective three a F value of 0.714 was produced regarding the integrity of the new security model. This value is lower than the table value at (1.70) degree of freedom (10,59), which showed that there was statistical significance. 87.5% of the experts concurred that the security system satisfied the requirement for a system that can improve the integrity of the data. The researcher added feature extraction component that represented infrastructure variable in the conceptual framework. The institution should consider changing its present fingerprint security system, which failed to verify legitimate users and was therefore inconsistent with data integrity. Learning institutions should implement the contactless system that does not require physical touch to verify people, which was more useful in the current COVID 19 epidemic, which has rendered the existing fingerprint security system useless. Organizations should consider implementing live detection systems or employ cancellable biometric systems that helps overcome spoofing attacks. More research needs to be carried out on palm vein template protection in deep learning since little research has been done in the field and also new decision authentication algorithms.
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