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Determinants Of Financial Performance Of Export Processing Zone Companies At Athi River In Kenya
Get PDFExport Processing Zones (EPZs) in Kenya were created with the aim of enhancing manufacturing
sector output, exports, employment, value addition and technology transfer. However, their
success in promoting trade across countries has been significantly realized. This study assessed
the determinants of financial performance of Export Processing Zones companies in Kenya
Companies with a focus on Export Processing firms at Athi River. The study key objectives was
to assess the effect of investment policies, internal controls, resource management and operational
efficiency on financial performance. The study adopted descriptive research design approach. The
target population of the study was the 73 EPZ companies in Athi River, Kenya. The study adopted
the use of secondary data where panel data was used. The study conducted Multicollinearity,
Heteroscedasticity, Normality test, Autocorrelation Test and Durbin – Wu –Hausman Test. The
data was analyzed using descriptive and inferential statistics. The results indicated that Investment
policy had a positively and significantly relationship with financial performance of the Export
Processing Zones companies in Kenya. Internal controls was also positively and significantly
related to financial performance of the Export Processing Zones companies in Kenya. Resource
Management was positively and significantly related to financial performance of the Export
Processing Zones companies in Kenya. Lastly, Operational Efficiency had a positively and
significantly related to financial performance of the Export Processing Zones companies in Kenya.
The study concluded that Investment policy, Internal Control, Resource Management and
Operational Efficiency affected financial performance of the Export Processing Zones companies
in Kenya in a positive and significant way. The study recommends that the EPZ firms should
consider having more current allocation on investments given the EPZ incentives provided in the
EPZ zones such as ax incentives, lower land rentals, exemption of import, export and value-added
taxes and reduced regulatory oversight in administrative and customs procedures. Further, the
firms should develop internal control systems that are in line with their financial performance of
the organization. The study recommends that the EPZ firms should work to reduce their resource
cost variance by to maintain optimal use of their resources. Lastly, the study recommends that
firms should strive to reduce their operating expenses and implement efficient strategies that
address asset and inventory turnover
Effects Of Insecurity On The Profitability Of Matatu Industry In Nairobi County
No full textThe study sought to examine the effects of insecurity on the profitability of matatu industry in Nairobi County. Specifically, the study sought to determine the effect of violent, non-violent and gender-based violence insecurity on the matatu industry profitability in Nairobi County. The target population of the study was 197 Public Service Vehicle SACCOS registered in Nairobi in 2019. The choice of the target population is informed by the fact that the 197 Public Service Vehicles SACCOS are well regulated hence the ease for identification, sampling and data collection. The study adopted an exploratory and descriptive research design. This was informed by the fact that the study sought to explain in detail on the effects of insecurity in the public transport on the transport sector performance. Structured questionnaires with open-ended question were used. A simple Ordinary Least Square regression model was applied to estimate the effect of violent, non-violent and gender-based violence insecurity on the matatu industry profitability. Upon the actual data collection, responses from 182 Public Service Vehicles SACCOS were received which translated to a response rate of 92.39%. The study found that violent, non – violent and gender – based insecurity negatively affects profitability of matatu industry in Nairobi County in Kenya. From the study findings, non – violent insecurities comprising of theft of passengers’ luggage and drugging have the highest negative effect on profitability. This could be explained by the fact that they are the easiest to be perpetrated and therefore are more likely to be rampant as opposed to violent insecurities which are easily noticeable and require much effort and planning for the perpetrators to commit. The study also concludes that although gender – based insecurities negatively affect profitability of matatu industry in Nairobi County in Kenya, the magnitude of their effect is suppressed. This could be explained by the fact that they are less likely to be reported as opposed to other forms of insecurities. Firstly, the study recommends a multi- agent and a multi-stakeholder approach to tackle insecurity in the matatu industry. Secondly is the need for awareness creation and sensitization to the matatu owners and SACCOS on the need to enhance security in their areas of operations given the negative effect insecurity has on their businesses. Thirdly, Efforts such as employing personal guards at the matatu terminals, installing matatus with security monitoring devices would go a long way in reducing such insecurity incidences in the industry. Fourthly, regulations by the National Transport Authority requiring matatu SACCOS to put up security measures and supervise adherence to these regulations is a welcome policy action. Finally, there is the need for national and county government to form a special security unit to deal with insecurity incidences within Nairobi Central Business District and the Nairobi metropolitan at large
Volatility Spillover influences and Response Asymmetries of Interest Rates, Exchange Rates, and Banking StockReturns: Evidence from BanksListed in the Nairobi Securities Exchange
Get PDFThis study examines response asymmetries and volatility spillover dynamics of Interest rates, Exchange Rates and returns of a portfolio comprised of Kenyan banks that are listed in the Nairobi Securities Exchange. The study employs [1]Exponential Generalized Autoregressive Conditionally Heteroscedastic (EGARCH) model for empirical modeling. The results suggest the presence of own transmission of returns in the banking sector. Further, they yield evidence of own transmission, high persistence, and asymmetric response of volatility in banking stock returns. Additionally, there is evidence of cross transmission of volatility from exchange rates to banking sector returns. The findings have several policy implications for investors, bank managers, and regulators
Day of The Week Anomaly and Stock Returns Volatility at Nairobi Securities Exchange
Get PDFThis study sought to investigate the effect of the day of the week anomaly on the stock market
returns volatility on the performance of Nairobi Securities Exchange. The study sampled NSE -
20 share index closing prices from September 2000 to December 2019. Data was obtained from
the Nairobi Securities Exchange database. Stata version 12 software was used and descriptive
statistics to analyse the data using the EGARCH (1, 1) model. The mean analysis results showed
the presence of the day of the week effect on the stock market returns of the NSE 20 Share
Index at the Nairobi Securities Exchange. This implies that Nairobi Security Exchange
performance still contravenes the Efficient Market Hypothesis Theory since investors can use
the day of the week anomalies to make abnormal return. The variance analysis showed a
positive asymmetric term, implying that positive shocks have greater impact on volatility more
than negative shocks of the same magnitude. Positive information in the stock market generates
less variance or volatility in the market since positive return translates to high equity prices. This
implies that volatility tends to decrease when the stock market returns at the NSE increases than
when the stock market decreases with the same amount
Factors Affecting The Choice Of Mobile Lending Platforms Among Small And Medium Enterprises In Tharaka Nithi County In Kenya
No full textSmall and medium enterprises (SMEs) have limited access to credit despite their contribution to global economic development and employment creation. The advent of digital lending through mobile lending platforms has improved access to credit for SMEs. However, since mobile lending platforms are unregulated in Kenya, predatory lending is rampant and hence it is vital for SMEs to make informed choices when they are selecting mobile lending platforms. The purpose of this study was to determine the factors affecting the choice of mobile lending platforms among small and medium enterprises in Tharaka Nithi County in Kenya. Specifically, the study sought to determine the effect of transaction cost, risk, and ease of use on the choice of mobile lending platforms among small and medium enterprises in Tharaka Nithi County in Kenya. This study applied a descriptive research design on a population of 745 small and medium enterprises in Tharaka Nithi County. A sample of 260 small and medium enterprises were selected and questionnaire were applied to collect data. The collected data was analysed using descriptive statistics (means, percentages, frequencies, and standard deviations) and multiple linear regression. The presentation of the findings was through figures and tables. The study findings determined that transaction costs had a significant and positive effect on choice of mobile lending platforms by SMEs in Tharaka Nithi County, Kenya (β= 0.185, p < 0.05). Additionally, study findings indicate that risk had a positive and significant influence on the choice of mobile lending platforms among small and medium enterprises in Tharaka Nithi County in Kenya (β= 0.169, p = 0.001). Further study findings indicated that ease of use had a significant positive influence on the choice of mobile lending platforms among small and medium enterprises in Tharaka Nithi County in Kenya (β= 0.314, p < 0.05). After considering the research's findings, the study offers important recommendations. First, the study recommends to policy makers and regulators such as Digital Lenders Association of Kenya (DLAK) and Centra Bank of Kenya to design an effective legal and policy framework that will guide the mobile lending institutions to have transaction costs that are fair and within the CBK legal legislation. The study also recommends to mobile lenders to enhance security of their applications through securing the application’s code, securing the back end, effective mobile encryption and educating their users on security. Lastly, the providers of mobile lending applications should develop the applications while considering platform compatibility so that the apps can work on several phone models, have simple navigation, have concise and clear content, minimize the number of steps when a user is seeking a mobile loan and reduce the need for scrolling through the application’s user interface
Factors That Determine Success Of Crowdfunding Initiatives In Kenya
No full textCrowdfunding has been observed to a phenomenon that disrupts conventional financing. However, the success rate of crowdfunding initiatives has been low. Understanding factors that influence success of crowdfunding is important given the growing role and popularity of crowdfunding as an alternative source of financing. This would provide an insight on how entrepreneurs can develop crowdfunding initiatives that are successful. Thus, the study sought to establish factors that determine success of crowdfunding initiatives in Kenya. The specific objectives were; to establish impact of crowdfunding platform on crowdfunding initiatives success, to find the impact of social networks on crowdfunding initiatives success and to find out influence of project quality on crowdfunding initiatives success. The study literatures captured several theories that supports crowdfunding namely social capital theory, game theory and signaling theory. The study adopted qualitative research approach evaluating projects raised in M-changa platform. The study involved a census population of 45 businesses listed in M-Changa platform. The study used questionnaire for data collection and they were analyzed using spss. The study achieved a response level of 91.1%. The results showed that crowdfunding platform was positively associated with crowdfunding success with r = 0.714, social networks was directly associated with crowdfunding success with a correlation of r =0.565 and strong association between quality of the projects and crowdfunding success with r = 0.683. The study recommendations emphasized on the need for founders to make sure that they study the crowdfunding platform well before deciding where to pitch their project. There is need for project founders to use numerous social networking platforms to advertise their projects and to attract friends and other social conducts to back the project. There is also need to have clear and quality videos and adverts so as to enhance the appeal of the projects pitched. Regarding project quality, there is need for project founders to do good research before formulating their projects. They should come up with quality business plans that are easy to pitch to investors
Effect Of Growth Strategies On Performance Of Telecommunication Firms In Kenya
No full textDespite presence of numerous empirical strategic management studies, the study on the correlation between growth strategies and performance of a firm has yet to draw a definitive conclusion on whether companies can stay oriented or diversify into various businesses. Therefore, the main objective of the current research was to assess the effect of growth strategies on telecommunication sector firm performance. The specific objectives were to; determine the effect of diversification strategy on performance of firms in the telecommunication industry in Kenya; analyze the impact of market penetration strategy on the performance of Kenyan telecommunications firms, determine the effect of product development strategy on the performance of Kenyan telecommunications firms, and determine the effect of market development strategy on the performance of Kenyan telecommunications firms.. The study adopted the Ansoff’s market growth theory, resource based view as well as the agency theory. This research used a descriptive survey design. Population of the research were the 62 telecommunication firms in Kenya while the unit of observation was the marketing manager in each firm. This study used primary data obtained using questionnaires and administered via Google forms. Data was analyzed using both descriptive statistics like mean as well as standard deviation and inferential statistics which included correlation and regression analysis. The research discovered a significant positive association between diversification strategy, product development strategy, market penetration strategy, market development strategy and performance of telecommunication firms in Kenya. Its regression analysis found that the collective usage of growth strategies was responsible for 45.6 percent of the variations in performance of these companies. Growth strategies are critical methods for organizations to adopt in their efforts to increase their performance levels, according to the result of this research. Based on the findings, diversification strategy had the largest impact on performance followed by market penetration while market development and product development strategy had the least influence on performance of telecommunication firms in Kenya. It is therefore, recommended that managers and shareholders of the firms that are yet to adopt growth strategies should adopt them to remain competitive and profitable in this turbulent business environment. It is also suggested that telecommunications company executives develop sound policies to guide them when pursuing growth strategies
Fintech Predictive Modeling and Performance of Investment Firms in Kenya
No full textPredictive analytics is concerned with the prediction of future trends and outcomes. The
approaches used to conduct predictive analytics can be classified into machine learning
techniques and regression techniques. This study dteremined the influence of fintech
predictive modeling on performance of investment firms in Kenya. The study population was
57 investment firms. The study employed mixed method research design by incorporating
descriptive and explanatory research designs. Data was collected using questionnaires and an
in-depth interview guide. Coefficient of fintech predictive modeling has a positive and
significant effect on performance of investment firms. The study concluded that fintech
predictive modeling allows investment firms to forecast business growth and customer
behaviour chnages. It is important for an investment firm to be able to understand business
growth by accurately forecasting future growth and survival. Moreover, it is of vital necessity
to understand changes in customer buying/consumption behavior so as to develop products
and services that suit their needs and preferences. As a result, predictive modeling is required
to project future business growth and changes in customer consumption pattern
Effect Of Working Capital Management On The Profitability Of Listed Manufacturing Firms In Kenya
No full textWorking capital management involves the management of the most liquid resources of the firm which include cash and cash equivalents, inventories, debtors and receivables. The inability of many organizations to effectively manage their working capital in such a way that it leads to a sustainable performance has been identified as the bane of growth in organizations. The main objective of the study was to determine the effect of working capital management on profitability of listed manufacturing firms in Kenya. The specific objectives of the study were: To determine the effect of Cash Management (CM) on the profitability of listed manufacturing firms in Kenya; to find out the effect of Inventory Holding Period (IHP) on the profitability of listed manufacturing firms in Kenya; to examine the accounts payable period (APP) on the profitability of listed manufacturing firms in Kenya; and to establish the effect of Accounts Receivable Period (ARP) on the profitability of listed manufacturing firms in Kenya. The study focused on four key theories: cash management theory, agency theory, value chain theory and the asset profitability theory. Descriptive research design was used as it describes systematically the facts and characteristics of a given population or area of interest, both accurately and factually. The target population for this study was the 8 listed Manufacturing firms on the Nairobi Securities Exchange (NSE). The study relied solely on secondary data which were analyzed using STATA. The data were extracted from annual reports and financial statements of the listed manufacturing firms, which data spanned the last 10 years. Descriptive and inferential statistics, particularly panel data analysis models, were used to assess the effect of working capital management on the profitability of listed manufacturing firms. The results of the effect of working capital management parameters of interest revealed that both CM and ARP had a negative relationship with ROA and the relationship was not statistically significant. Although IHP had a negative relationship with ROA, the results revealed a statistically significant relationship with ROA. The relationship between APP and ROA was strong, positive and statistically significant. The study recommends that firms should develop better relationships with suppliers to enable them make favorable agreements concerning accounts payables and accounts receivable days. It also recommends that managers should ensure proper maintenance of inventory books to avoid holding stock for a long period. Firms should automate control techniques like Economic Order Quantity (EOQ) and Just-in-Time to minimize wastage and improve financial performance. It recommends further that firms should review their credit criteria
Regression Model For Predicting Breast Cancer Patients Using Integrated Genomic Data In Kenya: A Case Of Kenyatta National Hospital
Get PDFCancer has been characterized as a heterogeneous disease which has caused havoc worldwide
with the increasing deaths related to cancer. The early diagnosis and prognosis of a cancer type
have become a necessity in cancer research, as it can facilitate the subsequent clinical
management of patients. The importance of classifying cancer patients into high or low risk
groups has led many research teams, from the biomedical and the bioinformatics field, to study
the application of machine learning (ML) methods. The main objective of the study was to
develop a regression model for predicting breast cancer patients using integrated genomic data.
It was facilitated by the objectives that sought to review the literature on factors to predict
breast cancer patients using integrated genomic data, develop a regression model for predicting
breast cancer patients using integrated genomic data and test and validate the regression model
for predicting breast cancer patients using integrated genomic data. Data was obtained online
through openML site. Information will be abstracted from the data obtained was used for
assessing breast cancer patients. The researcher utilized the Kenyatta National Hospital dataset
that includes 44,000 cancer patients. This formed the target population used in the study. The
population was narrowed down to 1,172 new cases between January of 2017 and June 2019.
Analysis was conducted by reviewing the literature, assessing the details and testing and
validating the model for predicting cancer patients using integrated genomic data machine
learning model will be applied. Inferential data analysis was used in reviewing the literature.
In this case, the data was summarized into points in a constructive manner. The analysis was
vital in forming the basis of quantitative data analysis. Regression analysis was used in the
identification of supervised learning models and their influence on the topic. Additionally,
regression analysis was employed as a predictive modeling technique that assesses the
affiliation between the variables. The research findings further established that factors
influencing breast cancer prognosis, screening appropriate predictors as independent variables
are an important step in model construction. In this case, the demographic risk factors are
important in the creation of BC risk prediction model. Additionally, it was found that the
genetic variants, combinations of demographic risk factors yielded a higher risk prediction
accuracy than the individual demographic risk factors. Age, disease stage, grade, tumor size,
race, marital status, number of nodes, histology, number of positive nodes and primary site
code have been entered into many predictive models as predictors, given that these factors
represent key risk factors for onset and survival in breast cancer. The researcher proposed an
ML approach to efficiently combine genetic variants with BC risk factors related to both
familial history and oestrogen metabolism and to search for optimal interactions among them.
According to the research, the choice of the most appropriate algorithm depends on many
parameters including the types of data collected, the size of the data samples, the time
limitations as well as the type of prediction outcomes. Therefore, it was recommended that the
future of cancer modeling new methods should be studied for overcoming the limitations