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Determinants Of Effectiveness Of Public Sector Audit In Kenya
Get PDFThe purpose of this study was to investigate the determinants of effectiveness of public sector
audit (PSA) in Kenya with a key focus on the national government and its entities. The
dependent variable of the study was the effectiveness of public sector audits (EPSA). Four
independent variables were identified including institutional corporate governance (ICG),
professional and technical competence (PC), resources availability (R), and internal control
process (ICP). The research used a descriptive research design and adopted a content analysis
methodology to analyze secondary data obtained from annual audit reports of the Office of
the Auditor General (OAG). The study used one-year cross-sectional data for the financial
year 2021/2022. The population of the study comprised of 109 financial statements of the
national government and 326 accounts of MDAs, donor funds, revenue statements, and other
three funds of the national government. The sampling technique used was 15% of the
population which amounted to a review of 43 statements. The non-disclosures or disclosures
for the variables and their indicators were coded as a "0" or "1" based on the specificity of the
detail. The disclosed details were recorded in a coding sheet. STATA version 16 software
was used to analyze the significance of the determinants of EPSA. The study findings showed
that all independent variables had positive coefficients and were statistically significant to
EPSA. Professional and technical competence was found to have the highest coefficient (PC),
followed by institutional corporate governance (ICG), Internal control process (ICP), and
Resource availability (R) which had a negative correlation. The major findings of the
regression were that ICP can be improved by ensuring sufficient training of the staff, to
further improve competence levels and help employees identify system weaknesses. Further
research can be conducted by adding a fifth variable of independence of the OAG which was
found by other researchers to be influenced by political matters. The research adopted
qualitative methodology; further research can be conducted using similar variables but use
primary data
Effects of Digital Payments on Financial Performance of Commercial Banks in Kenya
No full textCommercial banks in Kenya, reported a significant decline in financial performance in the year ending 2017 in comparison to the previous year. This profitability decline was attributed to a higher decrease in income compared to the marginal expenses. One of the key challenges that impacted the sector’s financial performance came from the interest rate caps enacted by the Banking (Amendment) Act of 2016. In order to remain competitive, profitable and achieve operational efficiency, banks have been collaborating with Fintech firms to offer Fintech services to the bank clientele; with Tier One banks being at the forefront of these collaborations. This study’s main goal was to determine effect of digital payments on the financial performance of tier one commercial banks in Kenya. The study sought to attain the following specific objective: to establish how digital payments affect the financial performance of tier one commercial banks in Kenya. The theories it focused on were: the diffusion of innovation theory, regulation innovation theory and disruptive innovation theory. A descriptive research design was applied in the study. The population target for this study was the tier one commercial banks in Kenya. The study used secondary data from the banks publications and financial statements as well as Central Bank of Kenya (CBK) annual reports published in the period from 2016 to 2019 when Fintech disruptions became more notable in Kenya. The data collected was analysed using descriptive statistics, correlation analysis and linear regression analysis using a fixed effect panel data regression analysis. STATA was applied as the data analysis tool. The results were presented in tables and graphs. The correlation analysis results showed that digital payments fintech services had a positive relationship with return on assets as the measure of financial performance of tier one commercial banks. The study concluded that digital personal finance management services showed a significant effect on the financial performance of tier one commercial banks in Kenya. The study recommends that commercial banks should partner with fintech companies so as to share knowledge and gain better expertis
Determinants Of Loan Funds’ Performance Of In Laikipia County, Kenya
Get PDFIn this study, the performance of loan funds within Laikipia County, Kenya is
investigated with particular attention given to the Laikipia County Enterprise Fund (LCEF)
and the Laikipia County Revolving Cooperative Fund (LCRCF). The determinants of these
fund's efficiency from a beneficiary perspective - in particular Small and Medium-sized
Enterprises (SMEs) and cooperatives - are analyzed. This study sought to investigate these
impediments focusing on both the supply and demand side. Three primary areas were
evaluated: beneficiary traits, loan fund administration methods, and loan operation
procedures processes. On the supply, Loan repayment rate, loan portfolio quality, loan fund
sustainability and loan fund growth are used as indicators to operationalize the performance
of the loan funds. The research seeks to understand the effect of beneficiary characteristics on
loan fund performance. This quantitative research project involved the development a
questionnaire to gather data from fund management and administration, Laikipia County
SMEs. Descriptive statistics, correlation analysis, and regression model was used to establish
the most influential factors on loan fund performance. The questionnaire's reliability and
ethical considerations related to data collection and analysis was also assessed provided
evidence-based insights that can inform decisions, enhance management and drive targeted
policy recommendations for Laikipia County's Enterprise Fund and Cooperative Revolving
Fund. These funds are essential in providing financial assistance for SMEs and cooperatives,
thereby stimulating economic growth and empowerment in the region. The study findings
showed that beneficiary characteristics have significant influence on performance of loan
funds in Laikipia County. Moreover, loan management practices positively and significantly
influenced loan funds performance. Likewise, loan operation procedures significantly
affected performance of loan funds. A conclusion was made that loan service provider at the
county need to understand beneficiary demographic characteristics based on education, borrower’s
experience and kind of business operated. In addition, loan management practices such as
approvals, disbursements and default policies are integral in achieving optimal loan
performance. The study concluded that loan operation procedures significantly and positively
affected performance of loan funds. The study recommends that to review their vetting and
screening process so that credit worth people are allocated financing through credit have
credit worthiness attributes. The use of technology will make the loan management practices
efficient and effective since many data can be pooled and worked within a shorter period of
time. It is recommended that loan operation procedures are tailored to meet customer
expectations especially on simplification of the processes. The study suggests use of
secondary data in measuring performance of loan
A Hybrid Model For Predicting E-learning Course Dropout Rate For Post Graduate Students
Get PDFIn universities all around Kenya, e-learning has grown in popularity, especially for postgraduate
programs. Students now find it simpler to access education from any location at any time thanks
to the use of technology in the delivery of courses and academic resources. However, dropout rates
continue to be a serious issue despite the many advantages of online learning. For a variety of
reasons, including a lack of desire, insufficient assistance, and trouble understanding the course
materials, students withdraw from online courses. Dropouts drive up educational institutions'
average cost per student because it typically costs more to retain a possible dropout than to enroll
a new student. The rise of online learning is hampered by the prevalence of school dropouts, which
waste the student's initial time and financial investment. Low graduation rates that follow high
dropout rates will surely damage the standing of educational institutions in the community and
eventually result in a downward loop of declining government support. To lower the dropout rate,
online educational institutions can employ this technology to quickly spot probable dropouts and
put retention measures in place before the dropout behavior takes place. The study's objective was
to create a hybrid machine learning prediction model for postgraduate E-learning students who
drop out utilizing the Support Vector Machine and Random Forest algorithms to improve
prediction accuracy. The researcher employed a descriptive survey and an experimental study
approach. The research methodology will be appropriate because the researcher trained the
Dropout Prediction Detection model using a machine learning technique. In 2024, 61.7% of
students are expected to graduate. With the aid of the data, the researcher was better able to
determine whether students had spent more time studying than was anticipated. 62.5% of the
respondent's price posed the most challenge to finishing the investigation, however 37.5% of the
fee posed no issue. In order to prepare students for postgraduate study, 68.3% strongly agreed that
undergraduates should be taught research techniques, and 29.2% also agreed. A 100% accuracy
rate for forecasting student dropout was demonstrated by the hybrid model. By using machine
learning to predict student attrition, educational institutions have a ground-breaking chance to
effectively address this pervasive problem. The study also recommended that the students choose
a study strategy that would best fit their schedules in order to prevent unneeded stress from juggling
numerous tasks at once. Deep learning models can be strengthened by techniques like Synthetic
Minority Over-sampling Technique to handle the unbalanced datasets typical in dropout prediction
problem
Yield-scaled and area-scaled greenhouse gas emissions from common soil fertility management practices under smallholder maize fields in Kenya
No full textAgricultural land-use activities are the leading sources of GHG (greenhouse gas) emissions in Kenya. However, few studies have examined GHG emissions resulting from different soil fertility management practices in small-scale African agricultural systems. The objective of the study was to quantify on-farm GHG emissions under different maize cropping practices in Tharaka-Nithi County, Kenya. The static chamber technique following a randomized rotational commencement pattern between farms and plots during GHG sampling events was used. Annual grain yield was determined from net plots and reported at 12.5 % moisture content. During analysis, analysis of variance (ANOVA) followed by LSD (Least Significant Difference) tests were used to assess treatment effects on grain yield, nitrogen use efficiency, area-scaled, and yield-scaled GHG emissions using GenStat and R procedures (‘agricolae’ package). The results showed that maize yield was not statistically different between fertilizer and fertilizer+manure treatments. The highest GNU (Grain nitrogen uptake) values were recorded in the fertilizer treatment, followed by fertilizer + manure, sole manure, and the control, which recorded the least GNU. The greatest GHG sinks were observed in sole manure, followed by fertilizer+manure, fertilizer, while the control treatment recorded the least GHG sinks. Additionally, the highest grain yields were obtained in the fertilizer treatment, followed by fertilizer+manure, and sole manure, while the control recorded the least yield. The study concluded that organic manure integration contributed significantly to improved soil fertility and GHG sequestration benefits without compromising maize yields
A Framework for Enhancing Computer Network Dependability in Universities
No full textComputer networks bring along many benefits in present-day society. The full benefits of computer networking are yet to be realised because of non-resilience issues. Universities are one of the sectors that have been a forefront user of computer networks and are yet to tap into its full benefits. This paper examines computer networks and develops a framework for computer network resilience in achieving computer network dependability in the context of universities. The paper adopted a survey research design targeting universities where Kibabii University was purposively sampled as the case study. The target population comprised (6246) undergraduate, (248) masters and (42) PhD students and (430) Kibabii staff. Random and purposive sampling were used where appropriate. The study used content analysis, questionnaires, interviews for data collection and a focus group for the framework validation process. Data collection tools were given to (3) experts to validate where they scored a validity value of (78.3%). Inferential and descriptive statistics were used to analyse the data. A KMO value of (0.803) justified the use of factor analysis on the collected data. Network, connectivity and human characteristics with factor loadings of (0.1898), (0.4359) and (0.3243) were the main constructs of the framework. The researchers expect that focusing on connectivity, human behavior, and network characteristics guarantees network end users a worthwhile experience, help computer hardware and software vendors fine-tune their solutions and guide governments and universities to plan and invest in enlightened environments when investing in computer networks, especially in universities
Investing for More than Just Money: The Non-Utilitarian Benefits of Investments
No full textPurpose: This article aimed to identify the psychological, social, environmental and ethical benefits of investments.
Methodology: A total of 82 articles that were initially picked for this study, 30 articles were however selected and critically scrutinized to yield this review article.
Findings: The review findings reveal that investments can have a significant impact on investors' well-being and highlight the importance of considering these benefits in investment decision-making processes.
Unique contribution to theory, practice and policy: One limitation of the existing studies is that they are often based on self-reported data, which may be subject to bias or social desirability effects. This research describes new paradigms to the additional benefits of investments, in addition to the famous monetary gains such as the psychological, social, environmental and ethical benefits. Understanding these trade-offs can help investors make more informed decisions about their investment strategies
Financial Structure and Market Performance of Non-financial Firms Listed at the Nairobi Securities Exchange
Get PDFThe determination of the optimum financial structure of a firm plays a critical role in ascertaining the appropriate amount of funds to be borrowed and the ideal combination of debt and equity for the purpose of financing business operations. The optimal financial structure for a corporation is possessing a robust financial base that enables the organization to capitalize on development prospects while upholding financial equilibrium. Nevertheless, the process of making finance choices is complex and might differ across businesses. The primary study aim was to assess the impact of financial structure on the market performance of non-financial companies listed at NSE. The primary aims of this study were to evaluate the impact of long-term debt on the market performance of non-financial companies listed on the NSE, analyze the effect of short-term debt on market performance, investigate the influence of share capital on market performance, and assess the impact of retained earnings on market performance of firms listed on the NSE. The research study used a descriptive research approach and relied on secondary data. The research used the utilization of secondary data, namely panel data. The temporal range of the investigation spanned from 2018 to 2022. The research included many statistical tests, including Multicollinearity, Heteroscedasticity, Normality test, Autocorrelation Test, and Hausman Test. The findings of the regression analysis showed that there exists a positive correlation between Long Term Debt, Short Term Debt, Retained Earnings and Share Capital, and the market performance of non-financial enterprises listed on the NSE. Furthermore, the observed statistical significance, as shown by the low p-values, implies that these linkages have a substantial impact on market performance. The research findings indicate that the market performance of firms listed on the NSE is positively influenced by short-term and long-term debt, share capital, and retained profits. The observed associations exhibited statistical significance, hence resulting in the rejection of the null hypotheses pertaining to each goal. The report proposes that non-financial enterprises listed on the NSE should consider using short-term debt as a strategy to enhance market performance, while concurrently exercising caution in controlling their debt levels. When considering long-term debt, it is advisable to adopt a prudent approach and seek guidance from professionals, given its relatively modest but nonetheless favorable influence. It is highly recommended to augment the share capital in order to bolster market attractiveness and attract a diverse spectrum of investors. Finally, it is recommended to accumulate larger retained profits as a means of communicating both financial stability and capacity for growth
The Role Of Internal Audit In Promoting Organizational Performance Of Commercial State Corporations In Kenya
Get PDFMany state enterprises in Kenya have recently suffered poor performance patterns, which has
jeopardized the sustainability of most of these vital institutions. Some state corporations have a
reputation for repeatedly producing poor results, relying excessively on the exchequer, and losing
their viability. The study's specific goals were to ascertain the extent to which audit quality affects
the organizational performance of commercial state corporations in Kenya, to investigate the
impact of audit independence on those organizations’ performance, and to ascertain the impact of
audit standards on those corporations' performance. At a 95% level of confidence, a similar number
of hypotheses were developed and tested. Three theories served as the study's foundation: the
agency theory, the contingency theory, and the auditor's theory of inspired confidence. In this
Cross-sectional study, descriptive, and correlational research designs were used. The study's target
population consisted of all commercial state corporations, The study used primary data giving a
total of 33 targeted respondents out of which 31 were filled and returned. The questionnaire was
used in data collection. Data were summarized using descriptive statistics, by use of frequencies
and percentages (%), while the causal relationship between the variables was determined using
inferential statistics, using correlation analysis (R-value) and regression analysis (beta coefficients,
R2 & p values). For ease of comprehension and interpretation, the collected data were analyzed
using SPSS version 20.0 and Excel and then presented as tables and figures. The results showed
that audit standards (β = 0.399, p=0.001), audit independence (β = 0.326, p=0.009), and audit
quality (β = 0.254, p=0.018) all significantly and positively affect the organizational performance
of commercial state firms in Kenya. Therefore, the study draws the conclusion that audit standards,
audit independence, and audit quality all significantly and favorably affect the organizational
performance of Kenyan commercial state firms. The study advises policymakers to pay great
attention to internal audit, particularly in monitoring and evaluating procedures to ensure quality
standards. For accountability and openness, the study advises routinely monitoring the audit
department. The results of the study suggest that risk analysis be encouraged at the level of
individual enterprises as well as across the whole range of functions and extensions of the
established organization. The researcher suggests that commercial state organizations might
improve the quality of their audits by creating and putting into practice methods to assess the
auditor's likelihood to find and disclose errors
Political Leadership and Regional Integration: A Case of the East African Community Common Market
No full textThe East African Community (EAC) is a regional integration initiative of East African countries, including
Uganda, the Democratic Republic of Congo, Tanzania, Kenya, South Sudan, Burundi, and Rwanda. The
EAC is struggling to achieve a fully functional common market. This research investigated political leader-
ship as an impediment to the region’s trade advancement using interpretative phenomenology. The researcher
interviewed selected individuals from the member state governments, regional trade bodies and private sec-
tor practitioners across the region. The findings posit that poor political leadership is a major challenge
affecting common market implementation. The research proposes relooking the EAC decision-making model,
reconciliation, sanction mechanism, political will and commitment, re-evaluating the principle of variable
geometry, financial solidarity, member states’ contributions, independence of EAC institutions, anti corruption
and EAC visioning as major solutions towards common market implementation. The study recommends
further research on how the solutions can be implemented for the benefit of the region