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Adoption Of Circular Economy Practices And Performance Of Agricultural Value Chains In Kenya
(KCAU, 2024) Karanja, Jackson Munyoroku
This research explored the adoption of circular economy practices within Agri-Value Chains in Kenya under varying external factors, a critical step towards enhancing sustainability, efficiency, and resilience in agriculture. The primary objectives were to assess the level of circular economy practices integration, identify barriers to its adoption, and evaluate its effect on Agri-Value Chain performance. The target population includes publicly listed agricultural firms, stakeholders such as farmers, agribusinesses, policymakers, and civil society organizations. The study adopted descriptive design to delve into the adoption of circular economy practices within Agri-Value Chains. The study targeted 438 respondents including 403 farming groups and 35 ministry and development partner key informants. A total of 209 respondents pre-determined using Yamanes formula were selected using stratified random sampling. Data was analysed using descriptive and inferential statistics. The relationship between variables was established using multiple linear equation modelling. The product development demonstrated a beta coefficient that was statistically significant. In light of these findings, it can be inferred that, assuming all other independent variables remain constant, enhancing product development will lead to an improvement in the performance of agricultural value chains in Kenya. The circular supplies exhibited a robust and statistically significant relationship with the efficacy of agricultural value chains in Kenya. Furthermore, circular supplies exhibited a significant beta coefficient. This led to the conclusion that enhanced circular supplies would correlate with an improvement in the performance of agricultural value chains in Kenya. The beta coefficient for product life extension was observed to be both positive and significant. This culminated in the conclusion that extending product life may enhance the performance of agricultural value chains in Kenya. The results suggest that the beta value associated with product recovery was not statistically significant. This study determined that variations in product recovery, whether improvement or decline, would not lead to any significant alteration in the performance of agricultural value chains in Kenya. Of the four variables—product development, circular supplies, product life extension, and product recovery—Product life extension exhibited the most profound influence on the performance of agricultural value chains in Kenya. This study indicates that agricultural firms in Kenya ought to prioritize the extension of their product lifespan, as this approach is anticipated to improve their profitability. The analysis revealed that product recovery exerted a minimal influence on the performance of agricultural value chains in Kenya. Considering these findings, this study advises agricultural firms in Kenya to exercise prudence in allocating substantial resources to product recovery, as such investments may yield limited returns. The results demonstrate that product development, circular supplies, product life extension, and product recovery constitute 69.1% of the performance metrics within agricultural value chains in Kenya. The residual 29.1% can be ascribed to additional variables that were not encompassed within the scope of this study. This indicates the imperative of pursuing additional research that integrates various variables to uncover further elements influencing the efficacy of agricultural value chains in Kenya.
Adoption Of Circular Economy Practices And Performance Of Agricultural Value Chains In Kenya
(KCA University, 2024) Karanja, Jackson Munyoroku
This research explored the adoption of circular economy practices within Agri-Value Chains in Kenya under varying external factors, a critical step towards enhancing sustainability, efficiency, and resilience in agriculture. The primary objectives were to assess the level of circular economy practices integration, identify barriers to its adoption, and evaluate its effect on Agri-Value Chain performance. The target population includes publicly listed agricultural firms, stakeholders such as farmers, agribusinesses, policymakers, and civil society organizations. The study adopted descriptive design to delve into the adoption of circular economy practices within Agri-Value Chains. The study targeted 438 respondents including 403 farming groups and 35 ministry and development partner key informants. A total of 209 respondents pre-determined using Yamanes formula were selected using stratified random sampling. Data was analysed using descriptive and inferential statistics. The relationship between variables was established using multiple linear equation modelling. The product development demonstrated a beta coefficient that was statistically significant. In light of these findings, it can be inferred that, assuming all other independent variables remain constant, enhancing product development will lead to an improvement in the performance of agricultural value chains in Kenya. The circular supplies exhibited a robust and statistically significant relationship with the efficacy of agricultural value chains in Kenya. Furthermore, circular supplies exhibited a significant beta coefficient. This led to the conclusion that enhanced circular supplies would correlate with an improvement in the performance of agricultural value chains in Kenya. The beta coefficient for product life extension was observed to be both positive and significant. This culminated in the conclusion that extending product life may enhance the performance of agricultural value chains in Kenya. The results suggest that the beta value associated with product recovery was not statistically significant. This study determined that variations in product recovery, whether improvement or decline, would not lead to any significant alteration in the performance of agricultural value chains in Kenya. Of the four variables—product development, circular supplies, product life extension, and product recovery—Product life extension exhibited the most profound influence on the performance of agricultural value chains in Kenya. This study indicates that agricultural firms in Kenya ought to prioritize the extension of their product lifespan, as this approach is anticipated to improve their profitability. The analysis revealed that product recovery exerted a minimal influence on the performance of agricultural value chains in Kenya. Considering these findings, this study advises agricultural firms in Kenya to exercise prudence in allocating substantial resources to product recovery, as such investments may yield limited returns. The results demonstrate that product development, circular supplies, product life extension, and product recovery constitute 69.1% of the performance metrics within agricultural value chains in Kenya. The residual 29.1% can be ascribed to additional variables that were not encompassed within the scope of this study. This indicates the imperative of pursuing additional research that integrates various variables to uncover further elements influencing the efficacy of agricultural value chains in Kenya.
An Academic Cloud Model For Enhancing Operations Efficiency In The Public Universities
(KCA University, 2014) Githua, Regina N.
The cloud computing paradigm has become an acceptable and adoptable technology in today's world. Its' an advanced technology that provisions ubiquitous computing resources such as hardware and software applications in a datacenter on a utility and pay-on-the-fly basis. The growth of cloud computing has been envisioned in many economic sectors to foster productivity and efficiency in the changing global economy. In order for organizations to retain customers and offer quality services, they have to keep abreast with changing innovations which are costly and expensive to maintain. Thus, cloud computing offers a platform for these organizations to have access to these technologies at an affordable rate as they only pay for what they have consumed. The Education sector has not been left behind in the adoption of cloud computing. Funding pressures, advances in IT field, the need to accommodate and improve the academic performance of the ever increasing population are some of the major reasons that have compelled institutions of higher learning to adopt to cloud computing services. The major objective of this research is to develop an education cloud model standard that will also make use of the existing computing infrastructure. The study also presents a review of related literature on cloud computing implementation by various research scholars who have also delved into the technology. The researcher has also explored how public cloud can be integrated with private cloud created within the institution to offer the services to the different users. The researcher has examined and analyzed the existing methodologies and highlighted how the proposed methodology will integrate all the services. If implemented, institutions will be highly reliable due to ubiquitous information that can be accessed from any location, improved data security and integrity, scalability of information and a greater return on economic value, since the institution will only pay for what it consumes.
An Analysis Of Corporate Governance As A Strategy To Address The Performance Of Sugar Manufacturers In Kenya (A Case Study Of Mumias Sugar Company Limited)
(KCA University, 2016) Nyongesa, Ben S.
Currently, a talk around the planet is whether there is proper stewardship geared towards organizational performance. Any outcomes of decisions made by the leaders in those organizations are supposed to benefit environment, the stakeholders and the communities in which they operate. This therefore underscores the need to improve the use of resources, which in turn increases the effectiveness and efficiency of firms. Sugar firms use various strategies for employing existing resources optimally so that a responsible and beneficial balance can be achieved over the longer term. The recent corporate governance erosion in Mumias Sugar Company which contributes more than half sugar production in Kenya warrants this study. It is therefore, against the status of affairs that the present study was conducted to fill this knowledge. The study analyzed corporate governance as a strategy to address the performance of sugar firms in Kenya. The study target population was the 113 officers of Mumias Sugar Company. Since the sample population was manageable and readily accessible, the study used census to collect data. The primary data collection method was through administration of structured questionnaire. The collected data was analyzed using descriptive statistics and inferential statistics. Narratives were used for interpretations of the results and findings and thereafter multiple regressions was then carried to establish the relationship between the Independent Variables (IVs) and the Dependent Variable (DV). Descriptive data was analyzed with assistance of SPSS ver. 20.0 statistical tool. The study concludes that firm performance of sugar companies in Kenya is moderate and that it is influenced by corporate governance, since the indicators of corporate governance; board characteristics, top management characteristics; and stakeholders’ communication characteristics are established to predictors of firm performance of sugar companies in Kenya. The study established that board characteristics highly affects the performance of Sugar Companies, top management characteristics highly influenced the performance of sugar companies, and revealed that stakeholders’ communication characteristics highly affected performance of sugar companies in Kenya. The study recommends that the sugar companies in Kenya should address the issues of board characteristics in their firm through establishment of effective policies and strategies, establish systems and policies to audit and trail the top management performance of sugar companies to ensure transparency and accountability of the directors and the CEO and the sugar companies in Kenya should significantly review the Stakeholders’ Communication polices to ensure that the stakeholders are also informed beforehand of any happenings in their investments.
An Assessment Of Accessibility Of Credit By Rural Small And Medium Enterprises (Smes) Within Migori County, Kenya.
(KCA University, 2023) Nyangaresi, Joseph O
The research focus on an assessment of accessibility of credit by rural SMEs within Migori County. The study intended to have a significant role to lending facilities, entrepreneur owners, wealth investors, and the county government of Migori to accelerate the formation of various policies regarding credit and also support other scholars on literature review. With the accessibility of credit serving as a dependent variable, the research examined interest rates charged, collaterals, financial institutions and literacy levels as predictor variables. Descriptive research methodology was employed. The population target was 1020 Small and Medium Enterprises operating within Migori County. A stratified Random sampling technique was employed and then followed by simple random sampling to select respondents from the selected strata. From the strata 102 respondents were selected as a sample size. The questionnaires were distributed by means of drop and pick technique. The statistics analysis was done using SPSS to capture both descriptive and inferential statistics. The study however, found that the interest rate, financial institutions had a positive relationship and were all significant while the collateral and literacy levels had a strong relationship but they were all insignificant. Therefore, the study recommends that the policy makers and the government should review the rates of interest and support training SMEs owners to impact the skills and create financial institutions network among the SMEs and also establish a diverse form of security for loans. The study also suggests further research using a larger sample and the research extended to other counties in Kenya.
An Assessment Of Organizational Factors Influencing The Financial Performance Of Access Kenya Group.
(KCA University, 2013) Kirira, Ruth N.
Since financial performance is important to the success of any business then improved financial performance in Access Kenya Group provided the main motivation for this study as expenses were seen to be growing much faster than revenues in the five year financial statement analysis of 2008 to 2012. It was therefore, the purpose of this study to assess the organizational factors that influence the financial performance of Access Kenya Group. The key indicators for financial performance being: to determine the awareness of revenue growth opportunities available for Access Kenya Group; to assess the relationship between business expenses and revenue growth for Access Kenya Group and to evaluate whether Access Kenya Group has people capabilities required to implement financial performance. In order, to achieve the stated objectives of the study, a questionnaire containing structured questions was used. It was however, accompanied by probing questions when the need arose for elaboration. The returned questionnaires were first sorted, coded, edited and keyed in the computer using SPSS (Statistical Package for Social Sciences). Considering that the data to be collected was quantitative data, descriptive analysis technique was best suited for data analysis. The conclusions and recommendations of the study were that the organization should maintain a balance between revenue growth and cost reduction. Secondly, it is important to note that customer retention and new products are critical for the organization and this can only be achieved through a detailed grasp of the changing risk profile of the institution which can only be achieved by building quality data and infrastructural investments. It is also increasingly important for Access Kenya Group to understand the regulatory codes emerging at both national and international level as this will assist the business in growing sustainable revenues. Finally, the organization will require to better align the way people work to enable them focus on business objectives, training and skills programmed’ to better achieve these objectives, infusing retailing skills and a cultural revolution in the way staff are led, managed, trained, measured and rewarded. For, further study the causes of low market share of Access Kenya Group in rural areas should be looked into considering as it is very popular in Nairobi and other major towns in Kenya. It is also important to look into the impact of regulatory framework on financial performance in future.
An assessment of training and safety needs of motorcyclists in Kenya.
(KCA University, 2011) Minju, Elvis M.
The motorcycle population in Kenya has soured in the recent past with the motorcycle numbers on Kenyan roads rising to 350,000 units from 30,000 units in seven years (2003 – 2009) according to government economic survey 2009. With the increase in numbers of motorcycles there has been concern as the riders are major causes of fatal road accidents. Riders are not properly trained and this compromise riding standards and road safety as training is inadequate. Motorcyclists can avoid some of the crashes with proper training. Currently some hospitals across the country are dedicating special wards for crash victims because of their numbers and frequency. The research work analyzed and assessed the safety and training needs that the motorcyclists require in order to reduce accidents on Kenyan roads. The study applied descriptive research to obtain precise information concerning the motorcyclists in Nairobi and five of the suburb towns with a population of one hundred motorcycles each. A simple random sampling procedure was adopted to select the sample of eighty motorcyclists in each locality after every ten minutes as they arrive at their work stations. Data was collected using questionnaires containing both structured and unstructured questions. After the field work, the questionnaires were checked for completeness, consistency and accuracy then arranged for coding. The data was then transcribed and analyzed using Microsoft excels to generate statistically inferable information. It was found out that the motorcyclists are male between ages 16-25years, with good basic education, who are self employed with half being married. They are not ignorant of the statutory requirements governing the operations of the motorcycles and they seem to be aware of all the rules. It was established that less than ten per cent have the requisite riding license. Although fifty six per cent indicated that they had actually attended a riding school, only fifty five per cent of those who attended sat for the government test and only fifty three per cent of the ones who sat for the test passed. This shows that only fifteen per cent of the motorcyclists have passed the government test with only six per cent being able to produce their licenses.
An Empirical Analysis Of The Weak Form Efficient Market Hypothesis Of The Nairobi Securities Exchange
(KCA University, 2013) Kamau, Albert M.
With the increased interest in the African economy, it is vital that we measure the performance of our capital markets to know where they stand. The Efficient Market Hypothesis (EMH) seeks to test whether a stock market is efficient in either the weak, semi-strong or strong form. With Kenya being an emerging market, the weak form efficient market hypothesis was put to test by the researcher, by determining whether successive daily stock market returns on the Nairobi Securities Exchange follow a random Walk or otherwise. The EMH briefly argues that for an efficient market, future share prices and returns should be random and unpredictable, such that any information regarding a stock is quickly assimilated into the market to reflect on the new share price Data in the form of historical daily closing NSE 20-share Index from 1st January 2008 to 31st December 2012 was obtained from the Nairobi Securities Exchange. The use of a longer time period was to eliminate the thin trading bias that is characteristic of emerging stock markets, while the use of indices is to maintain consistency of data used in the research. Both parametric and non-parametric tests were used, to confirm results obtained in either of the tests. The data was analysed using STATA statistical package to test for stationarity of the model, normal distribution of stock prices, randomness of successive price changes and independence of stock price changes. Unit root test, runs test and Autocorrelation tests were carried out to test for the afore mentioned characteristics of the stock price and returns. Mixed results were obtained from the research, with the runs test concluding that the NSE daily market return series was random and therefore the NSE followed the random walk model. The autocorrelation tests and unit root tests, however, concluded the NSE was not weak form efficient. The autocorrelation tests detected serial correlation in the successive daily market returns and there was absence of a unit root in the time NSE time series. The research concluded that the NSE was not weak form efficient, since all the tests conducted did not conform to the characteristics of weak form efficient market hypothesis. Information flow from the listed companies to the public is not efficient, giving some investors an advantage over others. It was recommended after the study that the NSE should put policies in place to ensure informational efficiency and also educate the public on the advantages of investing in the stock market to improve trading on the bourse.
An Investigation Of The Effects Of Income Source Diversification On Financial Performance Of Commercial Banks In Kenya
(KCA University, 2013) Akinyi, Benter.
The profitability of commercial banks depends heavily on the net of income generating activities and the related activities expense. Due to the problem of profitability and stiff competition in the industry, commercial banks have changed their behavior of income sources, by increasingly diversifying into non-intermediation income generating activities as opposed to the traditional inter-mediation income generating activities. The purpose of this study was to establish the effects of income source diversification on financial performance of commercial banks in Kenya. The study sought to establish the effects of foreign exchange trading income, bank charges, commission on government securities and agency banking on financial performance of commercial banks in Kenya. The research adopted a descriptive survey research design. The target population was the 43 registered Commercial banks and respondents were the 43 finance mangers at the head offices. Due to the population size of finance managers at the head offices of the 43 registered commercial banks, the research took a census approach. Primary data was obtained through self-administered questionnaires. The researcher used multiple regression model to analyze the relationship between the independent and dependent variables. The findings were presented using tables and figures. The study found that foreign exchange had the highest effect on banks financial performance followed by commission from loans and advances, then government securities while agency banking had the least effect on banks financial performance (r= 0.793, p= 0.0214). A majority of the respondents (70%) indicated that foreign exchange trading affects financial performance of Commercial banks to a great extent. From the findings, exchange rate margins and volume of foreign exchange transactions affected the financial performance of the banks to a great extent as shown by a mean of 3.975 and 3.609 respectively. A majority of the respondents (65%) reported that bank charges affected financial performance of Commercial banks to a great extent. According to the findings, interest rates earned on the loans, credit cards fees and number of loans/advances affected the financial performance of the banks to a great extent as shown with a mean of 3.959, 3.859 and 3.781respectively.From the findings, number of transactions and commission from Agency banking affected the financial performance of the commercial banks with a mean of 3.892 and 3.781 respectively. A conclusion can be drawn from the study that ‘Income source diversification affects financial performance of commercial banks in Kenya’. The banks should increase their foreign exchange trading by increasing volume of foreign exchange transactions, and ensuring that positive trade flows are maintained. Accounts opening fees should be eliminated to attract more customers.Banks should invest on government securities to earn more commission from Treasury Bonds and Treasury Bills to increase their profit.
Analysis Of Changes In Financial Reporting Quality In Japan After Introduction Of International Financial Reporting Standards (Evidence From Firms Listed In Tokyo Stock Exchange)
(KCA University, 2017) Ajiki, David O.
This study analyzed the changes in financial reporting quality in Japan after introduction of International Financial Reporting standards (IFRS). Financial reporting quality has two fundamental attributes according to the conceptual framework of IASB: faithful representation and relevance. The proxy for faithful representation in the study was earnings management measured by discretionary accruals. The objectives of the study were: to determine changes in accruals and changes in relevance of financial information after IFRS introduction in Japan. Modified Jones model was used to measure accruals. Relevance was measured based on the ability of financial information to predict future stock prices. 45 firms which have prepared financial statements for at least 2 years based on IFRS were sampled. Analysis of accruals was done using paired t-test while regression model was used to determine the relevance of financial information before and after adoption of IFRS in Japan. The study found that changes in both discretionary and non-discretionary accruals after adoption of IFRS are not significant. This therefore mean that the efforts made by Japanese agencies and IASB to converge JGAAP with IFRS has eliminated major differences between the standards even though some slight differences still exist. Secondly, the study concluded that adoption of IFRS in Japan has not significantly influenced management’s behavior in financial reporting. Finally, study also found that the relevance of financial information increased after adoption of IFRS.
Analysis Of Some Selected Factors On The Adoption Of GDP-indexed Bond As A Budget Financing Option In Kenya
(Kca University, 2020) Waweru, Paul
This study analyses some selected factors that could influence the adoption of GDP indexed bonds as a budget financing option in Kenya. Its specific objectives are to: examine how the openness of the economy could influence the use of GDP-Indexed Bonds as a budget financing option in Kenya; assess how capital market development could influence the use of GDP-Indexed Bonds as a budget financing option in Kenya; explore how government credibility could influence the use of GDP-Indexed Bonds as a budget financing option in Kenya and; determine how the volatility of returns could influence the use of GDP-Indexed Bonds as a budget financing option in Kenya. The study is founded on two theoretical foundations namely: Theory of Policy Credibility, and Keynesian Theory. It adopted the explanatory research design with data being obtained from secondary data sources. The data were checked for completeness, accuracy, and uniformity and cleaned. The data obtained was coded and analyzed. The researcher used the Statistical Package for Social Sciences (SPSS version 24) to analyze the data. Descriptive statistics (weighted means, percentages, and frequencies) and inferential statistics (Pearson correlation and regression analysis) were used to analyze the data. The findings from multiple regression show that openness of the economy, government credibility, capital markets development and volatility of returns had significant relationships with the feasibility of GDP-Indexed Bonds to finance budget deficits. Findings from the multivariate regression model showed that the combined influence of independent variables could explain use of GDP-indexed bonds to finance budget deficits in Kenya though the model was strong. F-test also showed that all the independent variables combined could statistically and significantly predict the feasibility of the use of GDP-Indexed Bonds in Kenya. Regression coefficients for all the independent variables were also significant. In this regard, the level to which the independent variables could statistically predict the feasibility of the use of GDP Indexed bonds to finance economic growth in Kenya were ascertained by the regression model. It could thus be concluded that ensuring openness of the economy, development of capital markets, credibility of the government as well as the predictability and steadiness of stocks returns could enhance the adoption of GDP-Indexed bonds as a financing option in Kenya. Based on the findings of the study, the following policy recommendation is made. The government needs to put in place policies for checking corruption and for enhancing its credibility among local and foreign investors. There should also be efforts to ensure that fiscal rules and the associated legislation are stable and do not change erratically so as to maintain investor confidence. The openness of the economy should also be enhanced to make it able to absorb different financial tools without problems. Limitations posed by taxes and any inflexible trade laws should be dealt with. The government should also constantly revise its legal and policy frameworks to ensure that capital markets adapt to emergent capital market demands to make the country competitive in the international arena. Mechanisms for reducing volatility of stocks should also be put in place.
Artificial intelligence and financial decision-making in manufacturing firms in Nairobi county, Kenya
(KCA University, 2025) Kituu, Peter M.
This study investigated the effect of artificial intelligence on financial decision-making in manufacturing firms in Nairobi County, Kenya, addressing the gap in understanding how AI tools influence financial strategies despite their growing adoption in business operations. With manufacturing firms facing intricate financial challenges, AI’s potential to enhance efficiency, accuracy, and planning remains underexplored locally. The general objective was to establish AI’s impact on financial decision-making, with specific objectives to assess the influence of predictive analytics, evaluate the role of machine learning models, examine the impact of automated financial reporting, and determine the effect of natural language processing tools on these processes. The study was guided by four theories: the Technology Acceptance Model, the Resource-Based View; the Automation Theory; and the Cognitive Fit Theory. The study adopted a descriptive cross-sectional survey design. The target population of this study were all the 2752 manufacturing firms in Nairobi County, Kenya. A sample of 349 was arrived at using Yamane formula. The unit of observation was the finance manager in each firm. Questionnaire was utilized in primary data collection. Data was analyzed using descriptive and inferential statistics, including correlation and regression analysis. The regression results revealed that 77.7 percent of the variation in financial decision-making was explained by the four AI dimensions. The model was statistically significant (F = 207.497, p < 0.05). Regression coefficients showed that all four dimensions had significant positive effects on financial decision-making: predictive analytics (β = 0.325, p < 0.001), machine learning models (β = 0.349, p < 0.001), automated financial reporting (β = 0.206, p < 0.001), and natural language processing tools (β = 0.128, p = 0.001). The study concluded that artificial intelligence significantly enhances financial decision-making by improving budgeting, investment planning, cost management, and risk assessment. The study recommends that manufacturing firms increase investments in AI tools to strengthen decision-making efficiency and accuracy. Managers should prioritize the integration of predictive analytics and machine learning into financial processes while expanding the use of automation for accurate and timely reporting. Firms are also encouraged to adopt NLP tools to reduce cognitive load in financial analysis and improve policy interpretation. Policymakers and industry associations should provide supportive frameworks and incentives to enhance AI adoption across firms, thereby strengthening competitiveness and resilience in the manufacturing sector.
Artificial Intelligence Applications And Performance Of Logistic Companies In Kenya
(KCA University, 2024) Maundu, Antony T.
The integration of Artificial Intelligence applications in logistics has revolutionized the transport sector by enhancing efficiency, optimizing operations, and improving overall performance. In Kenya, Logistics Companies play a critical role in the movement of goods across long distances, yet they face numerous challenges, including operational inefficiencies, high costs, and inconsistent service quality. The study examined the effect of leveraging on artificial intelligence applications in promotion of performance of Logistics Companies in Kenya. In this study, a descriptive research approach was utilized, and the target group consisted of 4725 individuals. Among these individuals, there were 269 managers of long-distance transport services and 4456 drivers of long-distance vehicles. The Yamane Formula was utilized in order to determine a sample size of 376 respondents. For the purpose of selecting the respondents, stratified random sampling was utilized, in which participants from each stratum were chosen through the execution of simple random sampling. In order to collect quantitative data from both the drivers of long-distance vehicles and the management of firms that operate long-distance vehicles, questionnaires were deployed. According to the model summary, it was demonstrated that machine learning, telematics, the internet of things, and big data are capable of explaining 68.6% of the performance of Logistics Companies of long-distance vehicles. The remaining 31.4% of the performance can be described by other variables that were not included in this study. One further thing that the findings demonstrate is that the beta coefficient for machine learning was positive. The findings demonstrate that telematics possessed a beta coefficient that was both positive and significant, which is an indicator that enhanced telematics may lead to enhanced logistical performance. The beta coefficient for the internet of things was found to be positive and significant, which indicates that an increase in the utilization of the internet of things is likely to result in an improvement in the efficiency of the logistics of long-distance vehicles for transportation agencies. Last but not least, it was demonstrated that the large data had a beta coefficient that was both positive and negligible. This indicates that any change in this variable would result in a change in performance that was not substantial for the logistics of long-distance vehicles that are managed by transportation agencies. Taking into consideration these data, the researchers concluded that enhanced machine learning might potentially result in enhanced performance of transportation agency logistics for long-distance vehicles. Additionally, the findings of this study concluded that enhanced telematics could potentially result in enhanced performance of transportation agency logistics for long distance cars. In addition, the findings of this study indicate that the implementation of internet of things could potentially result in enhanced performance of transportation agency logistics for long-distance vehicles. In conclusion, the findings of this study indicate that the performance of transportation agencies in terms of the logistics of long distance vehicles is unaffected by changes in big data. This study recommends that long distance vehicles companies do not need to invest resources in big data since it does not have a major influence on the performance of Logistics Companies of long-distance vehicles.
Artificial Intelligence Integration And Business Management Metrics In The Telecommunication Sector In Kenya
(KCA University, 2024) Munga, Caleb
As a game-changing technology, artificial intelligence (AI) has the potential to completely change a number of industries, including telecommunications. This research investigated how artificial intelligence affects business management metrics in the telecom sector. The main focus was on the effects of AI applications on important KPIs including income generation, productivity, client fulfillment, and predictive analytics. This study's main objective was to examine the influence of artificial intelligence (AI) on business management metrics within the telecommunication sector. The study’s specific objectives were: First, to examine the influence of Data Analytics Platform on business management metrics in Telecommunication sector in Kenya. Second, to assess the influence of Natural Language Processing on business management metrics in Telecommunication sector. Third, to examine the influence of Machine Learning Algorithms on business management metrics in Telecommunication sector and finally, to examine the influence of Robotic Process Automation on business management metrics in Telecommunication sector in Kenya. The study utilized descriptive research design. The target population had 427 employees who work at Airtel and Safaricom Companies corporate headquarters under the various functional departments. Stratified random sampling technique was applicable in the selection of the 206-sample size. The study used a semi-structured questionnaire as the data collection instrument with inferential statistics used for data analysis and presentation. The results analysis highlights the critical role of technological advancements, particularly in the areas of Data Analytics, Natural Language Processing, Machine Learning Algorithms, and Robotic Process Automation, in driving improvements in business management metrics within the telecommunications sector in Kenya. The study concludes that the integration of AI technologies is essential for enhancing business management metrics in the telecommunications sector.
Artificial Intelligence Integration And Business Management Metrics In The Telecommunication Sector In Kenya
(KCA University, 2024) Munga, Caleb
As a game-changing technology, artificial intelligence (AI) has the potential to completely change a number of industries, including telecommunications. This research investigated how artificial intelligence affects business management metrics in the telecom sector. The main focus was on the effects of AI applications on important KPIs including income generation, productivity, client fulfillment, and predictive analytics. This study's main objective was to examine the influence of artificial intelligence (AI) on business management metrics within the telecommunication sector. The study’s specific objectives were: First, to examine the influence of Data Analytics Platform on business management metrics in Telecommunication sector in Kenya. Second, to assess the influence of Natural Language Processing on business management metrics in Telecommunication sector. Third, to examine the influence of Machine Learning Algorithms on business management metrics in Telecommunication sector and finally, to examine the influence of Robotic Process Automation on business management metrics in Telecommunication sector in Kenya. The study utilized descriptive research design. The target population had 427 employees who work at Airtel and Safaricom Companies corporate headquarters under the various functional departments. Stratified random sampling technique was applicable in the selection of the 206 sample size. The study used a semi-structured questionnaire as the data collection instrument with inferential statistics used for data analysis and presentation. The results analysis highlights the critical role of technological advancements, particularly in the areas of Data Analytics, Natural Language Processing, Machine Learning Algorithms, and Robotic Process Automation, in driving improvements in business management metrics within the telecommunications sector in Kenya. The study concludes that the integration of AI technologies is essential for enhancing business management metrics in the telecommunications sector.
Artificial Intelligence Technologies And Supply Chain Performance Of Manufacturing Firms In Kenya
(KCA University, 2023) Kirimi, Cate N
Today’s manufacturing systems are becoming increasingly complex, dynamic, and connected. The factory operations face challenges of highly nonlinear and stochastic activity due to the countless uncertainties and interdependencies that exist. Recent developments in artificial intelligence have shown great potential to transform the manufacturing domain through advanced analytics tools for processing the vast amounts of manufacturing data generated, known as Big Data. Adoption of artificial intelligence technologies has been taunted as an enabler of organizational performance. Therefore, the current study sought to assess the level of adoption of AI technologies and their effect on the performance of supply chains of manufacturing firms in Kenya specifically in the automobile subsector. The study was based on socio technical theory and technology organization environment theory. The study adopts descriptive design targeting the seventeen automobile companies in Kenya. Census method was used to select all 153 functional officers in; Finance, Human resource, ICT, Logistics, SCM, Legal, R&D, Security and Operations since the population was small. Data was collected through use of questionnaires send via Google form, analyzed through descriptive and inferential statistics. The finding of the study is presented in tables. It’s expected that the study findings will find use among researchers, policy makers and managers of the manufacturing firms. Key findings of the study are that; all the three artificial intelligence technologies (IOT, Data analytics, Sensors and Drones) have a positive and significant influence on supply chain performance of manufacturing firms in Kenya. Besides government regulations moderating the relationship between AI technologies and supply chain performance. It is recommended that manufacturing firms need to embrace more AI embedded technologies for better supply chain responsiveness, flexibility, reliability and low operational costs. Further research needs to be undertaken on more AI tools and in other institutions so as to verify the study findings.
Assessing The Factors Affecting the Revenue Collection Performance of Counties in Kenya
(KCA University, 2015) Hassan, Abdirahman N.
Although the county revenue management is the vehicle to economic growth and development; and efficient service delivery at the counties in Kenya, the revenue collection in various counties of Kenya faces serious challenges. The general objective of the study was to assess the factors affecting revenue collection performance of counties in Kenya in an effort to make recommendations for ensuring excellent performance of revenue collection. Specific objectives of the study were to establish the influence of revenue sources, revenue collection administration, information communications technology and staff capacity on revenue collection performance of Garissa County in Kenya. The study was based on the public choice theory and tax compliance model. The study used descriptive survey design. The study considered a target population of 136 officers of Garissa County government. Since the target population is accessible and manageable the study used census. The study used a structured questionnaire for collecting primary data from the selected respondents. Descriptive statistics, correlation and regression analysis were sued to analyze data. Quantitative data was analyzed with assistance of Statistical Package for Social Scientists (SPSS). The study established that revenue source significantly influenced revenue collection performance. Further, revenue collection administration, ICT and staff capacity has a positive and significant effect on revenue collection performance. The study makes the following recommendations. First, the county should ensure that it diversifies its revenue sources to widen its tax and revenue bracket. Secondly, the county government should institute innovative and accountable methods of revenue collection and management. Moreover, the county should adopt ICT in various activities and process of revenue collection to ensure that processes with inefficiencies are removed. Lastly, the study recommends that staff capacity should always be improved to ensure that they can keep up with the needs of revenue collection.
Assessing The Kenya Police Capacity To Conduct Financial Fraud Forensic Investigations In Kiambu Sub-county
(KCA University, 2015) Kariuki, Stephen W.
This study examined the Kenya Police and Directorate of Criminal Investigations officers‟ capacity to carry out financial forensic frauds investigations in Kiambu Sub-County. The overall objective of the study was to evaluate the financial fraud forensic capacity of Kenya Police in Kiambu Sub-County. This study was conducted in Kiambu Sub-County, in Kiambu County and targeted the Kenya Police and Directorate of Criminal Investigations officers who are responsible for criminal investigations. The study objectives were; to establish the capacity of Kenya police human resource to carry out forensic investigations on financial frauds in Kiambu Sub-County, to examine the skills capacity of police officers to conduct forensic investigations on financial frauds in Kiambu Sub-County and to assess resource capacity of Kenya Police available for police officers to conduct forensic investigations on financial frauds in Kiambu Sub-County. These objectives sought to answer the following questions: what is the capacity of Kenya police human resource to carry out forensic investigations on financial frauds in Kiambu Sub-County? what skills capacity do police officers have to conduct forensic investigations on financial frauds in Kiambu Sub-County? and what resources are at the disposal of the police officers for conducting forensic investigations on financial frauds in Kiambu Sub-County? The study adopted ex post facto research design. Regular police officers and Directorate of Criminal Investigations Officers (DCI) dealing with criminal investigations were randomly sampled while purposive sampling was employed to select specialised DCI officers at DCI headquarters who provides specialised services to Kiambu Sub-County. From the target population of 90, the study sampled 81 respondents to participate in the study where the response rate was impressive at 85.7%. The study used self-administered questionnaires as primary data collection instruments. Self-administered questionnaires collected primary data while police records provided secondary data. Data collected was analysed both descriptively and statistically. Quantitative data was analysed using descriptive statistics such as frequencies, modes, means, variances or standard deviations. Contingency tables were generated by cross-tabulating variables determine the relationship between the study variables. Chi-Square and One-Way ANOVA was used to test the statistical mean difference among variables. Tables and charts present analysed data to represent quantitative findings. Inferences were made to describe the research findings. The study findings revealed that innumerable capacity challenges face the Kenya Police Service in both skills and resources coupled with other challenges, which has greatly influenced the ability to detect, conduct and prosecute financial frauds. The study recommends there is need to come with measures of addressing limited capacity in the police service in order to improve on financial fraud investigations.
Assessment Of Capital Rationing Practices As Deter-minants Of Effective Completion Of Cdf Funded Projects: A Case Of Kasarani Constituency
(KCA University, 2013) Munene, Jacob M.
Effective completion of CDF funded Project depends not only on capital availability but is greatly influenced by the capital rationing practices adopted by management in allocat- ing available funds to various projects. CDF being a government fiscal decentralization mod- el similar to federalism applied in many other parts of the world faces budgetary constraints, which require adoption of sound management capital rationing practices. Successive budget deficits are common phenomena in Africa and most governments bridge the gap through bor- rowing and grants. The introduction of CDF in 2003 triggered massive demand for projects that require financing through the exchequer hence pressurizing the already insufficient fund- ing. The study was based on 72 projects proposed and approved for implementation and fi- nancing by the Kasarani CDF between year 2003/2004 and 2011/2012 financial year from which 22 projects were samples for observation. The study focused on the estimated 1,000 employees of various CDF financed projects within Kasarani constituency from which a ran- dom sample of 280 respondents was drawn and questionnaires administered. The self- administered questionnaires were distributed and collected after a week, which provided pri- mary data, while secondary data was obtained from the CDF website. Quantitative data was analysed by descriptive analysis and in addition, multiple regression was used to explain the strength in relationship between the dependent and independent variables. The study found out that effective completion of CDF funded projects is influenced by capital rationing prac- tices.
Assessment Of Environmental Requirements In Supplier Selection As Pre-requisite For Total Quality Management: A Case Of Selected Manufacturing Firms In Nairobi, Kenya
(KCA University, 2014) Onserio, Thomas B.
Reports and awareness by international stakeholders that environmental tragedies like oil spills from manufacturing firms that contaminate our shores leading to the deterioration of the eco-system, the growing ozone “hole” in the atmosphere and the general human activities that are contributing to environmental degradation and depleting limited resources as a result of global warming serve as an eye-opener towards tackling issues afflicting the physical environment. However, reporting and creating awareness alone fall short of articulating the practical issues that need to be put into place in the manufacturing sector especially in developing countries in order to arrest environmental degradation issues. This study sought to investigate whether environmental requirements are being included, in practice, by manufacturing firms in Kenya in the area of supplier selection as the source of raw materials into the supply chain in an effort to ensure total quality management in order to achieve customer satisfaction and achieve sustainable competitive advantage. It also highlighted how the selected manufacturing firms that are ISO 14001 environmentally certified inculcated green issues in their products and production processes so that those firms that are yet to embrace environmental issues can borrow leaf and start going green as well. The study also sought to highlight the benefits to those firms that implement green issues the supplier selection process, and recommend best practices that can be applied by firms in Kenya in order for them to be able to compete successfully in this dynamic global business environment. A descriptive research design was employed focusing on the three certified manufacturing firms on ISO 14001 Environmental Management Systems in Nairobi and its environs (KEBS-2013). Purposive sampling was used to select a sample size of 60 participants. Data was collected by administering questionnaires that mainly consist of rating scales to a selected sample of respondents from Purchasing, Production, and Sales/Marketing departments of the firms. Quantitative method of data analysis that employed descriptive statistics was used to facilitate examination of the situation in the firms in relation to environmental requirements and data was then analysed using SPSS. The study established that consideration of environmental requirements in supplier selection was at the preliminary stages of implementation and there were major gaps that are yet to be filled in. It also emerged that the supplier selection criteria adopted by the firms studied were not adequate to achieve TQM. The study also established that the environmental management systems in the firms were not well integrated and balanced in their implementation in order to achieve TQM. From the study, it also emerged that supplier relationship management was not done in a way that would enable the firms studied to achieve the objectives of TQM. However, the study established that the firms were in the process of inculcating environmental issues in their business processes and the respondents were found to be aware of the benefits of including environmental issues in the supplier selection criteria for example increased customer satisfaction.