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Affirmative action funds and the growth of small and medium enterprises (smes) in Nairobi county
(KCA University, 2025) Abdi, Ismail A.
Across the globe, small and medium-sized enterprises (SMEs) serve as vital engines for economic advancement and social development, particularly within emerging economies. However, despite their significance, these enterprises often face challenges such as limited access to capital, insufficient managerial capabilities, and restrictive policy environments. This study explores the impact of affirmative action funds on the growth of SMEs in Nairobi County, focusing on the roles of the uwezo fund, youth enterprise development fund, and women enterprise fund. This study was anchored on growth theory and complimented by human capital and social capital theory. This study employed a cross-sectional survey design. Using Yamane’s formula, a sample of 376 SMEs was selected from a population of 6,176. Primary data was conducted through questionnaires. Data was coded and processed using SPSS. Descriptive statistics and inferential methods were adopted to analyze the data. Inferential statistics such as regression and correlation analysis were used to assess the influence of affirmative action funds on the growth of SMEs in Nairobi County. The study established that all three affirmative action funds, Uwezo Fund, Youth Enterprise Development Fund, and Women Enterprise Fund, positively influenced SME growth in Nairobi County. Uwezo Fund enhanced financial discipline and credit access through group lending, while YEDF improved managerial capacity and strategic planning via training and support services. WEF emerged as the most impactful, enabling women-led enterprises to invest in inventory and expand operations through affordable, tailored financing. Based on these findings, the study recommends strengthening fund outreach, simplifying access procedures, and integrating post-financing support such as mentorship and market linkages. Policy reforms should institutionalize these funds within national SME frameworks, promote inter-agency coordination, and embed gender-responsive strategies to ensure inclusive, sustainable enterprise development across Kenya.
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Moderating Effect of Corporate Governance on The Relationship Between Financial Risk Exposure and Profitability of Microfinance Banks in Kenya
(KCA University, 2025) Kamwilwa, Gladys K.
This study sought to investigate the moderating role of corporate governance on the linkage between exposure of banks to financial risks and the profitability of Kenyan microfinance banks. In particular, it aimed to evaluate the influence of credit risk exposure, liquidity risk exposure, and operational risk exposure on their profitability with corporate governance as a moderator variable in this relationship. The study was guided by the modern portfolio theory, theory of financial intermediation, liquidity preference theory, and agency theory. Utilizing an explanatory research design, the study targeted 14 registered microfinance banks with the Central Bank of Kenya as of December 2023, utilizing a census sampling method. Secondary data for the context of 2019-2023 were sourced from Central Bank publications, as well as financial statements of respective individual microfinance banks. The analysis of the findings employed panel data procedures with the help of Stata 18 as well as SPSS version 26, utilizing means, standard deviations, as well as multiple regression analysis. The study established that credit risk exposure (β=0.105, p<0.05), liquidity risk exposure (β=0.121, p<0.05), as well as operational risk exposure (β=0.019, p<0.05) had a significant positive influence on profitability. Moreover, it established that though corporate governance had a negative coefficient (β=-0.221, p<0.05) indicating its significance, after the inclusion of the interaction term with corporate governance as a moderating factor under the third scenario, both corporate governance as well as the interaction remained insignificant (p<0.05). The study concluded that exposure of banks to risks had a remarkable impact on their profitability, with partial modulation by corporate governance. The study recommends that credit risk managers of microfinance banks must formulate strong credit risk handling strategies with the intent of reducing non-performing loans, hence improving their profitability. Also, marketing managers have to invest in advertising and organizing activities for promoting mobilization of deposits, enhancing liquidity. Lastly, managers have to streamline operating costs while maximizing revenues for enhancing profitability, and owners of microfinance institutions have to have strong corporate governance mechanisms, such as enhancing board independence.
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Strategic factors affecting uptake of capital market’s public equity finance option amongst smes in Kenya: perceptions
(KCA University, 2025) Kayasi, Edwin E.
The uptake of public equity financing among Small and Medium Enterprises (SMEs) in Kenya remains significantly low despite the growing need for alternative capital sources to support business growth and sustainability. This study was motivated by the need to evaluate the strategic factors that influence the adoption of equity financing through capital markets by SMEs. Grounded on the Agency Theory, Resource based theory, and Pecking order Theory, the study specifically assessed the role of corporate governance, technology adoption, and information disclosure in accelerating SME uptake in equity markets. A descriptive and exploratory research design was employed. The study targeted 38 SMEs comprising firms listed at the Nairobi Securities Exchange (NSE) which were classified either in the Alternative Market Segment, or the Growth Enterprise Market Segment. SMEs that were near listing or had sought interest in listing were classified under Ibuka program. Primary data were collected using structured questionnaires, while secondary data were sourced through document reviews. A census approach was used, and responses were analyzed using descriptive statistics and binary logistic regression using SPSS. Diagnostic tests including reliability analysis (Cronbach’s alpha), multicollinearity (Variance Inflation Factor), and linearity in the logit were also conducted. Descriptive results showed that SMEs generally exhibited strong corporate governance structures, moderate to high levels of technological adoption, and reasonable compliance with information disclosure practices. However, inferential analysis revealed that none of the three strategic factors significantly predicted the uptake of public equity financing. This may be attributed to regulatory barriers, inefficient capital markets, and investor skepticism toward SME transparency. The study recommends that policymakers and regulators revise listing requirements and enhance market infrastructure to accommodate SMEs more effectively. Capacity-building initiatives should also be undertaken to improve SME readiness for equity financing. Future research should consider broader geographic coverage, adopt mixed methods, and explore additional strategic and institutional variables influencing equity financing adoption.
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Loan pricing techniques, regulatory environment on performance of tier one commercial banks in Kenya
(KCA University, 2025) Chemjor, Dickson K.
This study investigates the effect of loan pricing strategies, specifically cost plus pricing, risk-based pricing, and market-based pricing, on the performance of tier 1 commercial banks in Kenya. The study is motivated by inconsistent and inadequate loan pricing policies that have resulted in a rising number of non-performing loans (NPLs), diminishing profitability, and deteriorating asset quality throughout the industry. The objectives are to evaluate the effect of each pricing model on key performance indicators, including returns on assets (ROA), returns on equity (ROE), and non performing loan (NPL) rates. The target population encompassed all designated Tier 1 commercial banks in Kenya, from which a representative of 90 observations sample was obtained through a purposive sampling method. A collection of secondary data was obtained from audited financial statements and regulatory reports spanning 2015 to 2024. The study found that cost plus pricing (β = 0.053, p = 0.677), risk-based pricing (β = 0.043, p = 0.726), and market-based pricing (β = 0.098, p = 0.368) had weak, negative, and insignificant effects on Tier 1 banks’ performance, while the regulatory environment (β = 0.865, p = 0.376) showed a mild positive but insignificant influence. The conclusion indicates that while pricing models theoretically shape profitability, their practical impact is limited by regulatory rigidity, risk mispricing, and macroeconomic instability. It is recommended that banks adopt flexible, data driven pricing systems, strengthen credit risk evaluation, and enhance regulatory collaboration. Policymakers should encourage digital innovation and balanced oversight. Future studies should expand coverage to lower tier banks, include macroeconomic variables, and apply longitudinal or mixed method designs to better capture the evolving relationship between pricing strategies and bank performance.
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Predictive model to forecast desert locust outbreaks in Kenya using maximum entropy
(KCA University, 2025) Chepkwony, Noah K.
Desert locusts (Schistocerca gregaria) are one of the most destructive transboundary pests, posing significant threats to food security, livelihoods, and vegetation. In Kenya, a severe outbreak of desert locust outbreak occurred between December 2019 and June 2021, causing extensive damage to crop and vegetation, specially in the eastern and northeastern parts of the country. Using forecasted climate and environmental data as well as historical occurrence data, it is possible to Predict possibility of an outbreak which can facilitate relevant stakeholders to put in place necessary measures to mitigate the effects. This prediction can help enhance early warning systems by facilitating timely intervention towards mitigating risks efforts. This research study aimed at coming up with a predictive model for desert locust outbreaks in Kenya using the MaxEnt algorithm and historical presence data together with environmental variables such as precipitation, soil moisture, temperature, and vegetation indices to identify areas susceptible to infestations. The research used used Maxent algorithm and latest technologies of GIS and machine learning techniques to generate maps that classify areas in terms of risks levels (low, medium, high) based on climate data and historical locust occurrence data. The output will help enhance locust monitoring and forecasting, providing critical insights for policymakers, stakeholders, and farmers. The output includes a validated prediction model, maps, and recommendations for locust control strategies. The findings revealed that precipitation and soil moisture were the strongest predictors of habitat suitability, followed by temperature and vegetation indices. The MaxEnt model produced validated habitat suitability maps, classifying areas into low, medium, and high-risk zones. High-risk areas were concentrated in northeastern and eastern Kenya, aligning with regions historically affected by locust invasions. These results demonstrate that combining presence-only data with climatic and environmental predictors provides reliable forecasts of potential outbreak zones. The study concludes that the predictive model and generated risk maps can strengthen early warning systems, guide surveillance and control operations, and support policymakers, stakeholders, and farmers in mitigating the impact of desert locust outbreaks.