PhD Theses

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A Dynamic parallel algorithm for derivatives pricing and hedging on GPU-CPU heterogeneous systems
(Strathmore University, 2023) Muganda, B. W.
The use of artificial intelligence in the financial services industry has the potential to transform the sector through greater efficiencies, cost reductions and better tools to draw intelligence from large datasets. The access to computing power which is scalable, accurate and reliable has consequently become a major requirement for the industry due to increased competition, increased products and complexity in models, increased volume of data, stricter regulatory environment and desire for competitive advantage. In this regard, this research provides methodological solutions that would result in accurate and fast system throughput, cost saving and speed acceleration for a financial institution’s financial engineering system by adoption of heterogeneous CPU-GPU parallel architecture with algorithms which are freshly created by drafting from dynamic copula framework for option pricing. This price estimation of options and the assessment of their risk sensitivities under stochastic dynamics namely: stochastic interest rate, stochastic volatility and jumps for varying strikes, maturity and asset classes is a computationally intensive task given the complex nature of the pricing methodologies applied. Models that are much more fully analytical and less complex for pricing derivatives under stochastic dynamics are desirable for much more accurate pricing, investment portfolio construction and risk analysis; and with it an associated system prototype that would provide real-time results. This thesis formulated dynamic parallel algorithms for derivative security pricing and hedging on GPU-CPU heterogeneous systems. This was achieved through the design and implementation of a real-time derivative pricing system prototype supported by a parallel and distributed architecture. The parallel architecture was implemented using hybrid parallel programming on CPU and GPU in OpenCL C, Python and R to provide computational acceleration. The GPU implementation resulted to a peak speed acceleration of 541 times by reducing compute time from 46.24 minutes to 5.12 seconds with the dynamic models under stochastic volatility and stochastic interest rates improving pricing accuracy by an aggregate of 46.68% over the Black-Scholes framework. This adopted approach in this thesis is of practical importance in the harnessing idle processor power, reducing the financial institution’s computational resources requirements and provision of accurate and real-time results necessary in trading, hedging, risk assessment and portfolio optimization processes. Keywords: Dynamic copula, empirical dependence, stochastic volatility, stochastic interest rates, jumps, hybrid GPU acceleration, parallelism
An Assessment tool for ICT stakeholder integration and infrastructure performance improvement: case Kenya
(Strathmore University, 2021) Ominde, D. K.
The poor performance of infrastructural projects in the country has been partly attributed to the lack of an evaluation framework for these projects, especially in terms of the stakeholder management model, and need to look into how the projects can achieve their optimal success formed the research problem of the study. This was to be pursued through the development of an assessment tool for stakeholder integration and infrastructure performance improvement in the ICT sector. The specific objectives of the research study were to establish the complexity of project delivery and propose improvements to policy makers and senior project practitioners in the ICT sector in Kenya. Moreover, the study was keen to identify key stakeholder integration determinants that can be used by policy makers and senior project practitioners to enhance ICT infrastructure project planning in Kenya. Additionally, the study focused on identifying some of the key performance metrics that are specific, measurable and relevant to the achievement of stakeholder integration and ICT infrastructure planning in Kenya. In addition, the study was keen to assess how infrastructure policy makers and senior project practitioners can prioritise and ensure there is a holistic end-to-end commitment to realise the defined benefits of ICT infrastructure projects in Kenya. Finally, the research proposed an assessment tool that comprises stakeholder integration, project complexity and performance metric determinants, which can be used to enhance the delivery of ICT projects in Kenya. The study adopted mixed methods research design, specifically, exploratory sequential design to examine how ICT project practitioners and policy makers can improve ICT project delivery. A total of 500 participants formed a target sample for the quantitative method; 290 participants responded and 286 of the filled-in questionnaires were found to be useful for the analysis. For the qualitative method, 47 participants were interviewed, and the data was analysed through NVivo. The number of participants was considered adequate with regards to the context of the study and the realisation of the objectives, which aimed to propose an assessment tool for ICT project delivery in Kenya. Data analysis comprised descriptive statistics, a reliability test, a correlation test and principal component analysis. Validity and reliability were attained through the assessment of the plausibility of variables in relation to the existing knowledge on integration of stakeholders, project complexity and key performance metrics within the context of delivery of ICT projects. The assessment tool was verified through focus discussions with participants. Research rigour was achieved through verification and validation of the methodology coherence and data analysis. The findings of the study suggest that ICT performance be measured against the achievement of stakeholder integration and realisation of benefits. Commitment to project objectives, competence of key stakeholders, alignment of stakeholder skills, understanding of core project processes and addressing stakeholder needs and expectations were found to be key to stakeholder integration. Through theory elaboration, the study structured the sequence relations of project management and stakeholder management constructs that could be used to assess and optimise the delivery of ICT infrastructure projects. The findings gave the novelty of the research study to be viewed from two perspectives: ▪The research study findings intended to streamline the delivery of ICT projects in Kenya as a way of enhancing the performance of these projects. The development of an assessment tool for the evaluation of stakeholders delivering ICT projects in Kenya is likely to be an important step in addressing the missing link between theory and practice. ICT project practitioners now have an assessment tool on which they will be able to base their project delivery model as a way of enhancing the outcome of their project. ▪From a policy viewpoint, the research study findings are likely to form part of the appraisal models that the government apply in monitoring the progress of ICT stakeholder integration. As already noted, the final outcome of the research was the proposal of an assessment tool that can be used by infrastructure policy makers and senior project practitioners in Kenya to ensure a mind-set of accountability and a structured approach to ICT project planning and stakeholder integration. Keywords: Information communication technology (ICT), Key performance metrics, Stakeholder integration, Benefit realisation, Project complexity
Are emerging markets prepared to adopt integrated reporting? evidence from listed companies in Kenya
(Strathmore University, 2021) Injeni, Geoffrey Ikavulu
The purpose of this study was to establish the extent to which listed companies in emerging markets like Kenya are ready for integrated reporting. An integrated report demonstrates how a company’s strategy, governance, performance, and prospects, in the context of its external environment, leads to the creation of value. The International Integrated Reporting Council (IIRC), working with local regulators like the Capital. Markets Authority (CMA) is encouraging companies to adopt integrated reporting. However, there is no empirical evidence that listed companies in Kenya are making sufficient disclosures to adopt integrated reporting and whether preparers, regulators, and users are open to this innovation in corporate reporting. Also, corporate reporting disclosures are influenced by different country contexts and company factors. Therefore, this study first used self-constructed indices to Analyse the annual reports of 50 companies listed on the NSE from 2010 to 2016 for financial information using International Financial Reporting Standards (IFRS), sustainability, corporate governance, and integrated reporting disclosures. Second, the relationship between the disclosures and the company factors was established using static and dynamic panel data econometric models. Third, a semi-structured questionnaire was used to obtain the perspectives of 20 preparers and semi-structured interviews conducted to obtain the perspectives of 5 regulators and 10 equity analysts. Findings and results reveal opportunities and challenges for the adoption of integrated reporting. First, IFRS, corporate governance and integrated reporting disclosures are high and trending upwards, but sustainability disclosures are low though improving. Size is the only company factor that is positive and significant across all the disclosures. Large companies, with those in telecom and banking sectors, in addition to those that report high sustainability and corporate governance disclosures will likely adopt integrated reporting. However, only 14% of companies analysed had formally adopted integrated reporting by 2016. While regulators and users support the voluntary adoption of integrated reporting, only half of the preparers are for mandatory adoption. Regulators do not expect corporate reporting regulation to be harmonized, while users do not see improvements in the investment process from adopting integrated reporting. Despite improvements in corporate reporting, with stakeholders open to the adoption of integrated reporting, the different country and company features, the varying needs of different stakeholders, remain challenges that need to be overcome. Besides, the three stakeholders consider integrated reporting as a stage in corporate reporting and therefore more research is required to establish the optimal corporate reporting.
Business development services (BDS)
Otieno, Hellen; Kiraka, Ruth
While the role that micro, small and medium enterprises (MSMEs) play in all economies is universally acknowledged, only a small segment of small businesses is capable of making full use of opportunities and coping effectively with threats without assistance. Smallness confers some inherent competitive disadvantages and same sort of external support is warranted in order for these enterprises to each their full potential (OECD, 2004). Services to promote and enhance MSME competitive performance accordingly constitute important policy instruments in many countries including advanced ones, such as the USA. However, programmes and institutions designed to support small enterprises have reached and assisted only a minority of them. This chapter examines the meaning, scope, role and the changing perspectives of business development services (BDS).
Corporate governance and financial and non-financial performance of state-owned enterprises in Kenya
(Strathmore University, 2022) Abang'a, A. O.
State-owned enterprises (SOEs) have social and economic objectives whose achievement depends on good corporate governance. As a result, this thesis sought to determine the relationship between corporate governance and financial and non-financial performance of SOEs in Kenya. Multi-theoretical framework is adopted to understand the extent to which corporate governance (CG) provisions, such as board meetings, gender diversity, board skill, board sub-committees, board size, board independence, board chair age and combined corporate governance provisions (CCG) influence financial and non-financial performance of SOEs in Kenya. Explanatory sequential mixed-methods approach was applied in which secondary data was first obtained from the annual financial reports and analyzed using balanced panel data, fixed-effects regression. The result indicates that board meetings, board skill and board gender diversity are the only significant CG provisions in determining financial performance. The result also finds that board skill and CCG are the only CG provisions that determines SOEs non-financial performance. In the second phase, responses of questionnaire survey obtained from the audit committee chairpersons of SOEs in Kenya were analyzed using independent sample t-tests. The results revealed that board skill is the only significant variable that positively influence both financial and non-financial performance. Interviews to SOEs directors unearthed the politicization of board appointments in Kenya. Overall, the findings demonstrate that CG reforms have improved performance, however, some CG provisions require re-considerations in order to attain full potential. The findings of this study have theoretical, practical and policy implications. The results advocate for the multi-theoretical framework in studying the relationship between CG provisions and financial and non-financial performance. State Corporation Advisory Committee, the Office of the Auditor General and the National Treasury that are mandated to overseeing the operations of SOEs in Kenya are called upon to re-evaluate the governance of SOEs to improve their performance. Also, the academic community are encouraged to approach CG studies in SOEs using mix-method approach to gain better understanding of the complex relationships devoid in a single approach. The study makes six important contributions. First, the study contributes by confirming that individual provisions of CG that constitute CCG provision have different impact on performance; Second, study adds to relatively few available literature on CG in SOEs ; Third, the study responds to a call for more CG studies in a developing country context; Fourth, this study shows the link between CG provisions and financial and non-financial performance of SOEs in a single study; Fifth, through mixed-methods research approach, this study uncovered important governance challenges that may have not been possible in purely quantitative analysis. Finally, by showing that CG studies should be approached from multi-theoretical framework. This study is limited by the fact that equal weight in binary coding is used, focus was on disclosures in annual financial reports, impact of moderator and mediating variables were not examined, qualitative data inquiry involved limited number of interviewees and single framework of non-financial performance. Future research may consider assigning weight, consider other information sources like websites, establish the impact of moderator and mediating variables, study other developing countries over time, include more interviewees and use broader measure of non-financial performance.
Deriving a transparent dataspace-oriented entity associative algorithm
(Strathmore University, 2014-06) Shibwabo, Bernard K.; Wanyembi, Gregory W.; Kiraka, Ruth; Ateya, Ismail; Orero, Joseph
Organizations possess data residing in varied data sources though there is no effective way of integrating these repositories to provide information to end users transparently. This is primarily caused by the fact that the existing data is stored in databases that consist of varied models and techniques of both storage and access to data. The main aim of this research was to formulate a set of algorithms to support the development of a dataspace support platform that integrates data residing in divergent data stores. These techniques facilitate the association of data entities in a dataspace by enabling entity coexistence for integrating data residing in divergent data stores. The research objectives were to analyze the state of dataspace implementation, to develop a model that outlines the criteria for successful dataspace design, to develop a dataspace support platform that integrates data residing in divergent data stores and to conduct experiments to validate the scalability of the implemented dataspace support platform. In order to achieve these objectives, the soft systems theory is applied. A literature survey approach is adopted and supplemented from the findings by use of brainstorming and further experiments. The findings have been used to identify facts pertaining to the principles, design and implementation of a dataspace support platform. The final outcome consists of a set of algorithms, models and a test dataspace support platform. Access to information is facilitated through a more scalable, flexible and transparent platform regardless of the underlying data models. This results to a O(log n + k ) query response time coupled with a O(n) build time on the entire dataspace. In conclusion, the triggers for enterprise systems integration are apparent, and compliance is only one of numerous drivers pushing organizations towards achieving a more integrated outlook of enterprise data. With the dataspace-oriented entity associative algorithm, users can have the ability to harness or filter informational requirements so as to enhance decision making in terms of time, accuracy and availability of information.
Determining the rational homotopy type of the component of inclusion in the space of continuous mappings from gr(k, n) to gr(k , n + r)
(Strathmore University, 2020) Otieno, Paul Antony
The complex Grassmann manifold Gr(k, n) is the space of k dimensional sub spaces of en. Fork= 1, one gets epn-l, the space of lines in en. There is a natural embedding G(k , n) <-+ G(k, n + r). Moreover, any complex manifold can be embedded in some projective space epN. In particular, there is an embedding Gr(k, n) <-+ epN-l where N = (~) 0 To a simply connected topological space, Sullivan associates in a functional way a commutative differential graded algebra (cdga) henceforth (/\ V, d) which encodes the rational homotopy type of X. This is called a Sullivan model of X . Given that H *(ePn, Q) is the truncated polynomial algebra 1\xj(xn+l ), one gets a Sullivan model of the form (1\(x, y), d) where lxl = 2, jyj = 2n + 1 and dx = 0, dy = xn+l . For k 2: 1, one might use the homeo morphism G(k, n) = U(n)/(U(k) x U(n- k)) to find a Sullivan model. Moreover, iff :X --+ Y is a continuous mapping between CW-complexes, then there is a commutative differential graded algebra ( cdga) morphism ¢ : (1\Vy, d) --+ (1\Vx, d) between Sullivan models of X andY. This is called a Sullivan model of f. In this thesis, we use a Sullivan model of the inclusion Gr(k, n) ~ Gr(k, n+ r) to compute the rational homotopy type of the component of the inclusion in the space of mappings from Gr(k , n) to Gr(k, n + r). Further, we will compute an L00-model of the component of the inclusion i and deduce its Sullivan model, using the generalised cochain Quillen functor. We seek to define a model both Sullivan and Quillen for the component of the inclusion and from it obtain the cohomology algebra and even attempt to determine whether the space is formal or not.
Energy-efficient resources utilization algorithm in cloud data center servers
(Strathmore University, 2019) Kenga, D. M.
In recent years, the use of cloud computing has increased exponentially to satisfy computing needs and this is attributable to its success in delivering service on a pay-as-you-go basis. As a result, Cloud Service Providers (CSPs) are putting up more Data Centers to meet the demand. However, the high amount of energy consumed by cloud data center servers has raised concern because CSPs experience high operating costs (electricity bills), which reduces profits. The cause of high energy usage in data center servers is energy wastage, which results from the low level of server utilization. This problem is currently addressed through Virtual Machine (VM) consolidation and Dynamic Voltage and Frequency Scaling (DVFS). Unfortunately, VM consolidation does consider workload types and VM sizes, which are factors that affect the level of server utilization. On the other hand, DVFS is designed for processor-bound tasks because dynamic power ranges for other computing resources such as memory are narrower. In this study, the effect of workload types (heterogeneous or homogeneous) running in VM and VM sizing on data center server energy consumption was investigated. The results obtained from conducted experiments show that heterogeneous workload is consolidation friendly as compared to homogeneous workloads from a data center energy consumption perspective. Further, a review of the literature discovered that oversized VMs lead to a low level of server utilization and thus leads to energy wastage. Consequently, VM allocation and VM sizing algorithms have been proposed and tested. The VM allocation algorithm co-locates heterogeneous workloads whereas the VM sizing algorithm is used for VM right-sizing. To test the applicability of the proposed algorithms in the cloud, the algorithms were evaluated using simulations on a cloud simulator (CloudSim Plus) using workloads logs obtained from a production data center (Grid Workload Archive Trace 13 (GWA-T-13)). Results on the evaluations carried out on the designed VM allocation algorithm showed that data center server energy consumption was reduced by 4%, 11%, and 17% when compared with Worst Fit (WF), First Fist (FF), and Best Fit (BF) VM allocation algorithms respectively. On the other hand, the VM sizing algorithm reduced energy consumption, memory wastage, and CPU wastage by at least 40%, 61%, and 41% respectively. From the results, we concluded that workload types and VM sizes affect the level of server utilization, which in turn determines the amount of energy consumption. Thus, the right workload types combined with the right VM sizing leads to a high level of server utilization leading to energy savings.
Estimating a finite population mean under random non-response in two-stage cluster sampling with replacement
(Strathmore University, 2020) Bii, Nelson Kiprono
Non-response is a regular occurrence in sample surveys. Developing estimators when non-response exists may result in large biases when estimating population parameters. In this study, a finite population means estimator has been developed under two-stage cluster sampling with replacement in the presence of random non-response. It is assumed that non-response arises in the survey variable in the second stage of cluster sampling assuming full auxiliary information is known. A weighting method of compensating for non-response has been applied. Kernel density estimation was used and the modified transformation of data method was incorporated in order to address the boundary effects due to the Nadaraya-Watson estimator used in the estimation process. Asymptotic properties of the proposed estimator of the finite population mean have been derived. The performance of the proposed estimator has been compared with other estimators based on bias, mean squared error, and confidence interval lengths using simulated data. The results revealed that the estimator proposed has smaller mean squared error values and shorter confidence interval lengths when compared to other estimators of the finite population mean. The bias results also indicated that the proposed estimator of finite population means performed better than the Nadaraya-Watson and the improved Nadaraya-Watson estimators. The transformed estimator proposed to address boundary bias due to Nadaraya-Watson has also been shown to have smaller values of the bias, smaller mean squared error values, and shorter confidence interval lengths compared to those of the Nadaraya-Watson estimator. The results obtained can be useful in choosing efficient estimators of finite population mean for instance in demographic health sample surveys.
Income tax compliance behavior of large and medium-sized business taxpayers in Kenya
(Strathmore University, 2019) Abdul, Farida
The main objective of this study was to establish the drivers explaining tax compliance behaviour among medium and large business taxpayers in Kenya. In so doing the researcher tested the validity and adequacy of the Theory of Planned Behaviour (TPB) and Procedural Justice Theory (PJT) in explaining tax compliance behaviour. A Structural Equation Model was built using survey data on 142 respondents and covering 19 key sectors of the economy. The study specifically sought to examine the influence of measures of perceived behavioural control, subjective norms, procedural justice measures, and tax system attributes (fairness, complexity, compliance costs as well as international compatibility) on tax compliance behaviour, while controlling for the hypothesized influence of firm size, age, sector and legal structure. The results indicate that tax compliance behaviour in Kenya significantly increases with increased perceived behavioural control, but declines significantly with an increase in tax compliance costs. In addition, the only firm characteristic that significantly increases with tax compliance is firm size. The model constructs account for about 39 per cent of variations in tax compliance behaviour in Kenya, which is above the empirically accepted minimum for exploratory studies. From the results, the study recommends a focus by the tax authority and policymakers on measures to reduce tax compliance costs. The authority should concentrate on those costs that relate to understanding the existing complex tax laws, changes in tax rules, as well as general costs of meeting compliance and regulatory requirements. In addition, greater emphasis should be put on investing in opportunities that reduce financial pressure on firms and on reducing incidences of firms that operate outside the tax system. Further, the authority should reduce incidences of financial distress in firms through prudent macroeconomic management and general surveillance to ensure that firms face minimal opportunities that would encourage them to underreport income- such as incomes not reported by third parties. The significance of the perceived behavioural control measure indicates the relevance and applicability of the theory of planned behaviour to tax compliance behaviour in Kenya.
Influence of celebrity endorsements on young consumers’ brand recall behaviour in Kenya : a case of Nairobi County
(2015) Njuguna, Simon Peter; Otieno, Hellen Nyolo
Celebrity endorsement has become a major form of advertising and Kenyan companies are increasingly using it to promote and position their brands targeting different market segments. The purpose of this study was to examine the Influence of Celebrity Endorsements on Young Consumers’ Brand recall behaviour in Kenya. Researcher-administered questionnaires were used to collect data from a sample of 167 youth drawn from Nairobi County. A multi-stage non-probability sampling was employed and the data analyzed using descriptive and factor analysis. The main findings revealed that celebrity endorsement generally influenced young consumers’ brand recall behaviour. When used as endorsers, celebrities were found to add an appeal to the endorsed brand making it easier for consumers to correctly remember it as having been previously seen or heard in the crowded market. The findings will provide guidance to marketing and advertising practitioners on how to improve the effectiveness of celebrity-based advertising by way of aligning their brand with a celebrity that resonates with the target market. To future researchers, this study will act as a catalyst and help them in defining future research agendas. Replication of this study using larger samples, different age groups and in different geographic settings is suggested for cross-validation purposes.
Innovative Private Sector Development Instruments – an African Perspective
Kiraka, Ruth
Small and medium enterprises (SME) are viewed as a key driver of economic and social development in the African context. They represent a large number of businesses, generate a relative large proportion of employment and are widely considered to be vital for a country’s competitiveness. To be competitive, they need one key ingredient: innovation. However, they are often unable to develop appropriate and innovative products due to a general lack of financial strength as well as technical and managerial skills. A part from that, they operate in an environment with multiple challenges: On the macro level, these include bureaucratic legal and regulatory frameworks, poor physical infrastructure, and a multiplicity of taxes. On the meso level, the challenges include inadequate support in terms of business training and skills, the unavailability of information on markets, suppliers and partners, a limited access to finance as well as weak, fragmented and uncoordinated institutions supportive of SME. Nevertheless, opportunities for investing in SME development are given, they include the commercialisation of SME innovations, the provision of resources to SME so that they are able to conduct research and market testing, business incubation, the funding of indigenous knowledge development and transfer, the development or rejuvenation of industry clusters, and the establishment of SME support centres These initiatives can enhance SME competitiveness, create more opportunities for employment and economic development and address a number of the challenges listed above.
Managing International Development Agencies (IDAs)
(www.Management-Journal.com, ) Kiraka, Ruth; Manning, Karen; Armstrong, Anona
International development agencies (IDAs) operate in a context of diverse stakeholder interests. This requires them to consider the significance of each category of stakeholders to determine the level of interest and power to influence the operations of the IDA. Using interviews and mail questionnaires, fifty-six Australian-based IDAs were examined to determine the extent to which they perceive external stakeholders as influencing their work. The research showed that two categories of stakeholders – donors and governments, were considered the most influential and powerful, hence the need to give priority to their expectations and needs. The “weaker” stakeholders – development clients and partner agencies, had a high level of interest but low power of influence over IDAs. However, they legitimise the existence of IDAs, hence their needs cannot be overlooked. The challenge for the IDA is in balancing the needs of its different categories of stakeholders as ignoring some could result in undermining its credibility.
Mathematical modelling of the impact of HIV intervention strategies in Kenya
(Strathmore University, 2020) Omondi, E. O.
Since the identification of the first cases of AIDS almost three and half decades ago, HIV/AIDS continues to inflict major public health and socio-economic challenges. Although various intervention strategies have been employed, cases of new infections are still quite high especially in sub-Saharan Africa. At the end of 2018, nearly 37.9 million people were infected with HIV globally. In Kenya, approximately 1.6 million people are living with HIV with 25,000 deaths resulting from AIDS-related illness yearly. The rise in the cases of infections obviously poses danger in the efforts to contain HIV pandemic. HIV prevention and intervention measures need to be enhanced in order to achieve an HIV free society. In this work, mathematical models for HIV transmission dynamics with focus on the impacts of testing and counselling, PrEP uptake and ART treatment are formulated and analysed. Vital analyses that include positivity, steady states and their stability conditions for the models are precisely established. Numerical results from fitting the models to real-time surveillance data to show the evolution of populations over time are obtained. Through Pontryagin’s maximum principle, qualitative optimal control measure against HIV is established. Results are indicative of the fact that combination of various control measures lead to reduction in cases of new infections. Our findings show that the introduction of PrEP has a positive effect on the limitation of spread of HIV when the coverage is maintained at 40%. Furthermore, a combination of PrEP uptake, condom use and ART treatment is likely to offer the best control measure against HIV infections. It is thus critical to devote more resources to education on HIV preventive measures and treatment programmes. In summary, control of new cases of HIV infections should take into account PrEP uptake and combination of condom use and ART treatment. However, PrEP program coverage and individual-level adherence is very critical. These results have the potential to help in escalating programs against HIV infections in high risk populations by modifying the implementation of current interventions, or by adding new control measures.
Mathematical models for hepatocytic-erythrocytic dynamics and therapeutic control of Malaria
(Strathmore University, 2020) Orwa, T. O.
Malaria is a mosquito-borne infectious disease caused by parasites of the genus Plasmodium. Mortality and morbidity due to malaria infection is a serious burden to malaria endemic countries. Despite the many years of prevention and control, malaria cases and mortality are still quite high. In 2018, the World Health Organization (WHO) reported about 219 million cases and 435000 deaths due to malaria globally. The threat of parasite resistance, minimal efficacy of malaria vaccines and the high burden of malaria prevention and control measures offer serious challenge to malaria elimination efforts. Improved therapeutic measures is hence necessary for malaria control and possible eradication. In this study, deterministic in-host malaria models with therapeutic control measures are extended and mathematically analysed. Effects of antimalarial drugs and malaria vaccines on disease severity are established analytically and numerically. Parasite resistance and the effects of competition between different parasite strains are also investigated numerically. Each model is analysed and vital properties such as positivity, existence of steady states and their stability conditions are precisely determined. By Pontryagin’s Maximum Principle, the optimal control therapy measure against P. falciparum malaria is determined. Results indicate that a combination of different malaria vaccine antigens yield better therapeutic outcome compared to individual vaccine antigens. A highly efficacious malaria vaccine (efficacy > 90%) is likely to offer the much needed protection against P. falciparum malaria. Multiple-strain infection is likely to increase parasitaemia and hence the severity and cost of malaria control. Malaria therapeutic control efforts should focus on reducing: the parasite invasion rate, the proportions of merozoites that become gametocytes per dying blood schizont, the average number of merozoites released per bursting blood schizonts and the rate of development of resistance during multiple-strain infections. Moreover, a combination of pre-erythrocytic vaccine antigen, blood schizontocide and gametocytocide drugs is likely to offer the best therapeutic control strategy against P. falciparum malaria. In conclusion, future malaria control efforts should consider efficacious malaria vaccines and vaccine combinations. To reduce development of resistance and morbidity, only efficacious antimalarials such as ACT should be used against P. falciparum malaria. The administration and use of current antimalarial drugs alongside efficacious malaria vaccines is likely to offer the much needed therapeutic combination against P. falciparum. Regular and strict surveillance on quality and standards of antimalarial drugs in medical facilities in malaria endemic countries is therefore very critical. Collectively, results from this study highlights the need for continued investment in malaria drug development and urgent drive to improve the efficacy of malaria vaccine candidates such as RTS,S/AS01.
Micro, small and medium enterprise growth and innovation in Kenya: a case study on the Women Enterprise Fund
Kiraka, Ruth; Kobia, Margaret; Katwalo, Allan M.
This study sought to examine the growth and innovation in micro, small and medium enterprises in Kenya by assessing the performance of the Women Enterprise Fund (WEF) on these dimensions. The WEF, a Government of Kenya initiative, aims to develop and grow women-owned MSMEs. Five years since its inception in 2007, it is imperative to establish whether the Fund is achieving its objectives in reaching the intended beneficiaries with the right kind of funding and support. Using a mixed method approach, comprising qualitative and quantitative methodologies, the study examined the performance of the Fund at the micro, meso and macro levels. Fourteen constituencies in four Counties – Kakamega, Nairobi, Nakuru and Nyeri – were purposively selected. Stratified random sampling (the strata being the borrowing stream) of the entrepreneurs was used to ensure representativeness of the sample. Questionnaires were used in the survey of women owned MSMEs in combination with in-depth interviews and focus group discussions with selected respondent groups. Quantitative data were analysed using SPSS. Descriptive results show the extent of growth and innovation in the post loan period. Multivariate regression analysis sought to empirically establish the determinants of growth and innovation among women owned enterprises. Logistic regression models for the selected measures of growth and innovation were estimated using the maximum likelihood estimation technique. Qualitative data were content analysed for emerging themes and patterns which formed the basis for discussing study findings. Study findings show that although the general indicators reflect positive growth among women owned businesses in terms of total business worth, turnover, gross profit and number of employees, they obscure incidences of stagnation or decline in growth. Incidences of decline or stagnation were significant at between 15 to 30 percent across the four measures. The most common form of innovation was observed in the change or addition of new products in the post loan period. Innovations in terms of services, markets and sources of raw materials were, however, less common among women owned enterprises. The study finds no evidence of significant differences in growth and innovation among enterprises across geographical regions, borrowing stream and age groups. Overall, entrepreneur characteristics such as age, marital status, level of education and family size were poor determinants of growth. Business characteristics such as location, the person who manages the businesses and the age of the loans, were significant determinants of growth in the number of employees. Growth in number of employees is considered a critical proxy for the other forms of growth in terms of total business worth, turnover and gross profit. From the findings, locating an enterprise in an urban area increased the likelihood that the business would either stagnate on decline in its number of employees and gross profit. Urban decline on these indicators was partly attributed to heightened competition among low-end enterprises which characterise most women owned ventures in urban slums and informal settlements. Similar to the case in growth, entrepreneur characteristics of age, marital status, level of education and family size were poor determinants of business innovation. Only some of the business characteristics, growth factors and innovation factors were found to be significant determinants of innovation. Overall, women owned enterprises in urban areas lack the expected ‘urban advantage’ in terms of growth and innovation. The most widely provided complementary service was training which was accessed by one half of women entrepreneurs in the study. Other common complementary services included general education and awareness on how to run business and business progress monitoring. Although reported in interviews and group discussions, the following complementary services were rarely offered: networking, exhibitions, export promotion and product certification, supplementary loans, mobile banking and overdrafts. From the findings, it can ii be deduced that besides training, few complementary services were available to the majority of women borrowers of the WEF loans at a level that could meaningfully sustain businesses on the growth path and spur innovations. The Fund continued to face numerous challenges at the WEF secretariat, lender and borrower levels. The main challenges at the Fund level included inadequate WEF field personnel, inadequate fieldwork facilitation, low loan amounts, delays in disbursements and an inefficient multi-layered Fund structure. High cost of loan administration, competition with commercial bank products, poor dissemination of information, high demand/limited scope of coverage, lack of distinct product branding, lack of individual choices in group lending, high default rates, bureaucratic processes and limited business monitoring were the main challenges at lender level. For the borrowers, the challenges included limited and shrinking markets/competition, lack of business knowledge, misconception about the purpose of the Fund, diversion of the funds, low literacy among segments of women borrowers, lack of loan securities and domestic interference. To reform the Fund in a way that enhances its quality, service delivery and sustainability, as well as the growth and innovation of the enterprises, the study recommends that there should be: improved field level staffing at WEF, improved business monitoring, allocation of more resources to field teams, provision of individual loans, increase in amounts of loans, enhanced and standardised training, development of legal framework for default recoveries, increased funding to the CWES stream, business incubators for start-ups, enhanced revolving funds, rationalization of administrative costs, increase in the number of loan holding banks, timely disbursement of the funds and simplification of the application process.
A Monte Carlo tree search algorithm for optimization of load scalability in database systems
(Strathmore University, 2020) Omondi, Allan Odhiambo
Variable environmental conditions and runtime phenomena require developers of complex business information systems to expose configuration parameters to system administrators. This allows system administrators to intervene by tuning the bottleneck configuration parameters in response to current changes or in anticipation of future changes in order to maintain the system’s performance at an optimum level. However, these manual performance tuning interventions are prone to error and lack of standards due to varying levels of expertise and over-reliance on inaccurate predictions of future states of a business information system. The purpose of this research was therefore to investigate on how to design an algorithm that proactively reconfigures bottleneck parameters without over-relying on an accurate model of a stochastic environment. This was done using a comparative experimental research design that involved quantitative data collection through simulations of different algorithm variants. The research built on the theoretical concepts of control theory and decision theory, coupled with the estimation of unknown quantities using principles of simulation-based inferential statistics. Subsequently, Monte Carlo Tree Search, with a variant of the selection stage, was used as the foundation of the designed algorithm. The selection stage was variated by applying a “lean Last Good Reply with Forgetting” (lean-LGRF) strategy and first tested in the context of a strategy board game, Reversi. The lean-LGRF selection strategy applied over 1,000 playouts against the baseline Upper Confidence Bound applied to Trees (UCT) selection strategy recorded the highest number of wins. On the other hand, the Progressive Bias selection strategy had a win-rate of 45.8% against the UCT selection strategy. Lastly, as expected, the UCT selection strategy had a win-rate of 49.7% (an almost 50-50 win-rate) against itself. The results were then subjected to a Chi-square (χ2) test which provided evidence that the variation technique applied in the selection stage of the algorithm had a significantly positive impact on its performance. The superior selection variant was then applied in the context of a distributed database system. This also provided compelling results that indicate that applying the algorithm in a distributed database system resulted in a response-time latency that was 27% lower than the average response-time latency and a transaction throughput that was 17% higher than the average transaction throughput.
Motives for starting and sustaining BDS : empirical evidence Kenya
Otieno, Hellen; Olomi, Donath R.; Kiraka, Ruth
The paper explains what motivates Business Development Services Providers (BDSPs) in Kenya to venture into and sustain their businesses. The study was done through the use of grounded theory methodology on eleven BDSPs in Kenya over twelve months between May 2008 and August 2010. The start-up motives were classified into three: extrinsic, intrinsic and philanthropic. Contrary to the dominant view that small business start-ups are driven principally by economic necessity, the study revealed that some BDSPs venture into and sustain their businesses mainly for intrinsic and philanthropic motives. These findings suggest that evaluation of sustainable BDS business should not be limited to the traditional economic theory of recovering costs but should take into account intrinsic and philanthropic rewards as well. The study enhances our understanding of “start-up motives” and “success” and in particular in the context of small firms. This knowledge is invaluable to scholars, teachers and policy makers involved in promoting small firms.
Predicting student performance trajectory by analysing internet technology utilization behavioural patterns: case of Kenyan university students
(Strathmore University, 2019) Khakata, E. N. G.
Learning within universities today is continuously being revolutionized by the presence and advancements made on internet technology. The use of internet technology by students in the learning process is greatly influenced by the adoption and utilization of the technology within their learning institutions. However, despite the investments made by the institutions for the provision of internet technology, it is not possible to determine whether the technology positively contributes to better student performance. Similarly, the students expend a certain level of effort in order to use the technology in the learning process. Nonetheless, it is not possible to determine whether their effort contributes to positive performance in their studies. Likewise, taking into account a student’s behaviour and the result they expect to achieve at the end of a learning process, it is not possible to determine the degree to which the effort of the student (effectiveness of student effort) contributes to improved performance. Therefore, there is need to develop a student performance prediction model that considers the investments made by institutions, the student effort expended and the effectiveness of student effort in the utilization of internet technology. The scientific contribution of this thesis involved generation of the student performance trajectory and the development of a student performance prediction model that focuses on student behaviour within a learning environment at a specific instance in time. This model will help educational practitioners to analyse the existing contextual factors within an institution and how the factors influence student performance without carrying out a longitudinal research that will be time and resource intensive. This research considered three major factors in the prediction of student performance, that is, the investment costs, the student effort and the effectiveness of student effort. Investment costs consider student behavioural costs such as the time budget, the physical costs and the mental budget. Student effort encompasses the behavioural intentions and the actions of the students. The effectiveness of student effort considers the expected outcome from performing an action and the behavioural costs. The time budget was mainly influenced by time spent using internet technology and the physical costs are determined by the physical environment and general infrastructure in the universities. The behavioural intentions and actions of a student were examined using the capability of the student, the attitude of the student, the relevance of the technology in the learning process, the productivity achieved in using the technology and the knowledge of a student in the use of the technology in the learning process. The key findings of this research showed that internet technology was a useful resource in the learning process of students and the students had embraced its use in their learning with vigour. The students perceived the technology as easy to use and useful in their studies. They had sufficient knowledge in the use of the technology in learning and they had used the technology to accomplish a number of tasks in their learning process. Furthermore, some universities had invested sufficiently for the provision of internet technology and hence, their students had benefited greatly from the technology. The study concluded by formulating the input factors based on key research findings that were used in the prediction of the student performance perceptions and the student performance trajectory. These formed the major research output and they could be used in predicting student performance at a given instance in time. Keywords: Internet technology, internet utilization, Cobb-Douglas theorem, student performance, predictive model, prediction algorithms, decision tree.
A Qualitative and quantitative assessment of a leadership training programme’s impact on health system performance in 19 counties in Kenya
(Strathmore University, 2020) Chelagat, Tecla
Health service delivery was devolved from the national Government to the counties in 2013 following the adoption of a new constitution in 2010. The aim was to make service delivery more efficient through closer leadership oversight at the counties. However, evidence suggests that health system performance in Kenya remains poor as manifested by inadequate funding and inefficient use of available resources. The main issue appears to be inadequate leadership at national and county levels. To address this issue, several institutions in Kenya have implemented training programmes targeting healthcare leaders. However, most of such training in Kenya focus on “leaders” (individual) development as opposed to “leadership” training (development of groups from an organization). The former approach has been shown to be ineffective in transforming institutional health system performance. The goal of the study was to examine the effect of a project-based leadership training implemented at Strathmore University since 2013 on health system performance in selected Counties in Kenya. A multi-method research design comprising of quasi-experimental time-series and qualitative methods was employed. Questionnaires and in-depth interviews were administered to 39 health managers from the public, private and faith-based institutions from 19 counties in Kenya who had undergone the leadership training followed by coaching and implementation of an institutional improvement project. The control group comprised 39 other health institutions within the same counties with managers that did not receive the leadership training. The proxy measure of the success of the leadership training was completion of implementation of the institutional improvement project. Thirty-three (85%) of the projects were successfully implemented and 29 (88%) and were sustained for a period of 60 months after the leadership training. Control health institutions had no health system performance enhancement activities during the same period. A responsive (health system performance enhancement) leadership training curriculum, alignment of the project to the County’s strategic plan and stakeholders buy-in and support for the programme were reported as the key project implementation and sustainability enablers. These findings show that leadership training and team coaching built around priority institutional improvement projects result in measurable and sustainable health system performance improvements indicators.

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