This study examined the influence of inventory management practices on service delivery performance in manufacturing firms in Uganda, using the Mukwano Group of Companies as a case study. Mukwano Group-one of Uganda's largest indigenous conglomerate manufacturing entities, operating across fast-moving consumer goods, edible oils, plastics, and detergents production presented an ideal research context for examining inventory management given the scale and complexity of its multi-category production and distribution operations. Drawing on a cross-sectional survey of 136 respondents comprising production managers, procurement officers, warehouse managers, logistics staff, and sales representatives, supplemented by financial and operational records analysis, the study assessed how raw material inventory management, finished goods inventory management, and inventory control systems influenced Mukwano Group's service delivery performance across customer order fulfilment, delivery reliability, and product availability dimensions. Descriptive statistics revealed moderate to high levels of inventory management practice effectiveness (means 3.48–3.82). Pearson's correlation analysis revealed significant positive relationships between all three inventory management dimensions and service delivery (r = 0.592 to 0.703, p < .001). Multiple linear regression demonstrated that the three dimensions collectively explained 63.7% of the variance in service delivery performance (R² = 0.637, F = 36.14, p < .001), with raw material inventory management emerging as the strongest predictor (β = 0.391, p < .001). The study recommended Just-In-Time inventory adoption, Enterprise Resource Planning integration, and supplier relationship strengthening as priority interventions for sustained service delivery improvement.

This study examined the relationship between monitoring and evaluation practices and project performance within Kampala Capital City Authority (KCCA), Uganda, addressing a persistent public-sector management concern: that substantial public investment in urban infrastructure, service delivery, and development projects had not always translated into commensurate improvements in project completion rates, budget adherence, quality of output, or beneficiary satisfaction. As the statutory body responsible for administering Uganda's capital city, KCCA managed a large and diverse project portfolio spanning road construction and rehabilitation, drainage and flood-control works, market redevelopment, solid waste management infrastructure, public health facility upgrades, and revenue and citizen-service digitisation initiatives — a portfolio whose scale and technical diversity placed correspondingly high demands on the authority's monitoring and evaluation systems to track progress, identify implementation risks early, and support evidence-based project management decisions. Drawing on a cross-sectional survey of 268 respondents comprising KCCA project managers and engineers, monitoring and evaluation officers, divisional technical staff across Kampala's five administrative divisions, contractor and consultant representatives, and a sample of project beneficiaries drawn from six recently completed or ongoing projects, this study employed descriptive statistics, hierarchy-of-controls monitoring-and-evaluation capability assessment, bivariate Pearson correlation and chi-square association, and multilevel mixed-effects logistic regression to examine the determinants of strong project performance. The findings demonstrated that monitoring data quality and timeliness (β = 0.612, p < .001), stakeholder and beneficiary feedback integration (β = 0.554, p < .001), and corrective action responsiveness (β = 0.527, p < .001) were the strongest independent predictors of project performance, while structural factors including monitoring and evaluation staff technical capacity (OR = 6.34, p < .001), management information system adequacy (OR = 5.47, p < .001), and top management use of monitoring data in decision-making (OR = 4.91, p < .001) were the strongest institutional predictors. The study calls for strengthened KCCA monitoring and evaluation staffing and technical training, investment in an integrated project management information system, formalised beneficiary feedback mechanisms, and stronger institutional linkage between monitoring findings and management decision-making as the priority interventions for improving project performance across KCCA's development portfolio.

Maternal mortality remains one of the most persistent public health and development challenges in Sub-Saharan Africa. Although global initiatives have placed maternal survival at the centre of Sustainable Development Goal 3, the burden of infectious diseases continues to weaken progress in many disease-endemic settings. This paper examines the impact of neglected tropical diseases and malaria incidence on maternal mortality in selected Sub-Saharan African countries, using the first objective of the underlying doctoral thesis as the analytical focus. The study used annual panel data covering 1990 to 2023. Maternal mortality ratio served as the dependent variable, while neglected tropical diseases, proxied by Human African Trypanosomiasis, and malaria incidence were the principal explanatory variables. Current health expenditure, prevalence of undernourishment, number of physicians, female secondary school enrolment and immunisation coverage were considered as health-system and socioeconomic controls where relevant to the broader dataset. Given the evidence of cross-sectional dependence, heterogeneous country experiences and mixed order of integration, the paper relied mainly on Augmented Mean Group and Common Correlated Effects Mean Group estimators for the maternal mortality model. The findings show that neglected tropical diseases exerted a positive and statistically significant effect on maternal mortality. The paper concludes that maternal mortality reduction in Sub-Saharan Africa requires integrated disease-control and maternal-health strategies, with priority given to malaria control, neglected tropical disease surveillance, maternal nutrition, healthcare financing and country-specific interventions.

This paper examines the influence of neglected tropical diseases (NTDs) and malaria incidence on child health and their heterogeneous effects across different levels of maternal and infant mortality in Sub-Saharan Africa. The paper is developed from the second and third objectives of a doctoral study on NTDs, malaria incidence and maternal and child health in the region. It uses annual panel data for selected Sub-Saharan African countries covering 1990-2023. Infant mortality rate is used as the core child-health outcome for the second objective, while maternal mortality ratio and infant mortality rate are jointly used for the distributional analysis under the third objective. NTDs are proxied by Human African trypanosomiasis, while malaria incidence is measured per 1,000 population at risk. Control variables include immunisation coverage, current health expenditure and physician density for the infant mortality model; prevalence of undernourishment, current health expenditure and female secondary school enrolment are used in the maternal mortality quantile model. The Augmented Mean Group (AMG) and Common Correlated Effects Mean Group (CCEMG) estimators are employed to account for heterogeneity and cross-sectional dependence, while the Method of Moments Quantile Regression (MMQR) is used to identify distribution-specific effects. The findings show that both NTDs and malaria incidence significantly worsen infant mortality. Country-level estimates further reveal that Zimbabwe, Equatorial Guinea, South Sudan, Mozambique and Cameroon record some of the strongest diseaserelated mortality effects. The quantile results show that NTDs matter more at lower infant mortality quantiles, while malaria incidence remains consistently harmful and becomes more severe at higher quantiles. For maternal mortality, malaria incidence increases steadily across the distribution, while NTDs show a stronger effect at the lower quantiles and re-emerge at the extreme upper quantile. The paper concludes that disease-control policies in Sub-Saharan Africa should be both integrated and distribution-sensitive, combining NTD eradication, malaria prevention, immunisation, health financing and expansion of healthcare personnel.

This study examined the role of non-governmental organisations (NGOs) in addressing the educational needs of refugees in Kyangwali Refugee Settlement, Hoima District, Uganda. Kyangwali, one of Uganda's oldest and largest refugee settlements hosting over 124,000 predominantly Congolese refugees, presented a critical case for examining NGO education programming given the scale and complexity of educational needs spanning early childhood development, primary schooling, secondary education, vocational training, and adult literacy. Drawing on a crosssectional survey of 182 respondents including refugee learners, teachers, NGO programme staff, and settlement education officials, the study assessed how NGO interventions in school infrastructure provision, teacher capacity development, and learner support services influenced educational access, quality, and retention outcomes in the settlement. Descriptive statistics revealed moderate levels of NGO intervention effectiveness across all dimensions (means 3.18–3.54). Pearson's correlation revealed significant positive relationships between all three NGO intervention dimensions and educational needs fulfilment (r = 0.561 to 0.674, p < .001). Multiple regression analysis demonstrated that the three dimensions collectively explained 57.3% of the variance in educational needs fulfilment (R² = 0.573, F = 24.87, p < .001), with school infrastructure provision as the strongest predictor (β = 0.374, p < .001). The study concluded that NGO contributions were indispensable but insufficient without stronger government coordination and sustainable financing, and recommended integrated Education in Emergencies programming, teacher professionalisation, and learner-centred support service expansion.

This study designed, developed, and evaluated a web-based system for monitoring employment opportunities for ruralurban migrants in Kampala City, Uganda's principal destination for rural-urban migration flows and assessed its usability, functionality, and uptake potential among the target user population. Kampala City's rapid population growth, driven substantially by continuous in-migration from rural areas across all regions of Uganda, had created a large and poorly served population of recent migrants who lacked the social networks, formal information channels, and institutional connections to navigate the city's complex and predominantly informal labour market. The study combined system development lifecycle methodology with user acceptance testing (UAT), post-implementation survey research among 156 migrant respondents, and key informant interviews with employment service providers, to evaluate the system against four performance dimensions: system usability, employment information comprehensiveness, migrant accessibility, and employment outcome facilitation. Descriptive statistics showed high ratings for system usability (mean = 4.12) and employment information comprehensiveness (mean = 3.89). Pearson correlation confirmed significant positive relationships between all four system dimensions and user satisfaction and employment outcome (r = 0.617–0.748, p < .001). SEM path analysis revealed system usability as the strongest total effect predictor of employment outcome facilitation (total β = 0.534), with employment information comprehensiveness as a significant partial mediator. The study concluded that the developed system addressed a critical information infrastructure gap and recommended institutional adoption by MGLSD, KCCA, and civil society employment services providers.

This study examined the relationship between substance abuse and criminal behaviour among youth in Uganda, with Wakiso Municipality serving as the primary case study. The study was motivated by growing concerns about the escalating prevalence of substance use including alcohol, cannabis, tobacco, and prescription drug misuse among Ugandan urban youth and its documented association with increased criminal activity, public safety challenges, and socio-economic marginalisation. Drawing on a cross-sectional survey of 196 respondents including youth aged 15– 35, community leaders, law enforcement officers, and social workers, supplemented by key informant interviews and focus group discussions, the study employed descriptive statistics, chi-square association tests, Pearson correlation, and multiple linear regression to examine how alcohol abuse, illicit drug use, and prescription drug misuse influenced different categories of criminal activity among youth in Wakiso Municipality. Descriptive findings revealed high prevalence rates of multiple substance use categories, with 62.8% of youth respondents reporting current or recent alcohol use and 41.3% reporting cannabis use. Pearson's correlation confirmed significant positive relationships between all three substance abuse dimensions and youth criminality (r = 0.583 to 0.741, p < .001). Regression analysis demonstrated that substance abuse collectively explained 66.8% of the variance in youth criminal behaviour (R² = 0.668, F = 41.72, p < .001), with alcohol abuse emerging as the strongest predictor (β = 0.438, p < .001). The study concluded that substance abuse was a primary driver of youth crime in Wakiso Municipality and recommended comprehensive drug demand reduction programming, community-based rehabilitation services, and law enforcement capacity strengthening as integrated response priorities.

This study examined the impact of artificial intelligence (AI) on financial accounting practices at Equity Bank Uganda Ltd, one of Uganda's fastest-growing commercial banks with a mission to transform the lives and livelihoods of people in Africa. As AI technologies including machine learning algorithms, natural language processing systems, intelligent process automation, and predictive analytics platforms were progressively integrated into banking operations globally, their specific impacts on core financial accounting functions including transaction processing, financial reporting, auditing, fraud detection, and regulatory compliance were reshaping the skills, processes, and professional judgements that defined financial accounting practice in the banking sector. Drawing on a cross-sectional survey of 186 respondents comprising financial accountants, management accountants, internal auditors, IT and data analytics staff, finance department managers, and senior management at Equity Bank Uganda's Kampala headquarters and regional branch network, the study employed descriptive statistics, Pearson's correlation analysis, multiple linear regression, and Structural Equation Modelling to examine how AI-driven automation of accounting processes, AI-powered financial analytics and decision support, and AI-enabled regulatory compliance and reporting systems influenced financial accounting accuracy, operational efficiency, and professional capability development outcomes. Descriptive statistics revealed moderate to high AI integration levels across all dimensions (means 3.42–3.84). Pearson correlation confirmed significant positive relationships between all three AI dimensions and financial accounting practice quality (r = 0.614–0.761, p < .001). Multiple regression demonstrated that the three AI dimensions collectively explained 68.4% of the variance in financial accounting practice quality (R² = 0.684, F = 46.28, p < .001), with AI-driven automation emerging as the strongest predictor (β = 0.441, p < .001). SEM path analysis confirmed AI automation as the construct with the largest total effect on accounting practice quality (total β = 0.537), with AI analytics and decision support partially mediating this relationship (indirect β = 0.152). The study concluded that AI integration had significantly and positively transformed financial accounting practices at Equity Bank Uganda and recommended strategic AI investment, accountant reskilling, AI governance framework development, and regulatory dialogue as priority actions for sustainable AI-enabled accounting transformation.

This study examined the influence of Total Quality Management (TQM) on service delivery outcomes in local government, using Kilembe Sub-County in Kasese District as a case study. Kilembe Sub-County-historically the site of Uganda's largest copper mining operations and now a rapidly developing peri-urban administrative area at the base of the Rwenzori Mountains had since 2018 been implementing a phased TQM programme funded through the Local Government Development Programme III (LGDP III) aimed at improving the quality, efficiency, and citizenresponsiveness of public service delivery across health, education, road maintenance, agriculture extension, and administrative services. Drawing on a cross-sectional survey of 216 respondents comprising sub-county administrative staff, health centre workers, school staff, community development officers, and service beneficiaries from across Kilembe Sub-County's five parishes, the study examined how customer focus orientation, continuous improvement practices, and employee involvement and empowerment-the three TQM pillars operationalised in the LGDP III programme influenced service delivery quality, timeliness, and citizen satisfaction outcomes. Descriptive statistics revealed moderate TQM implementation levels (means 3.28–3.61). Pearson correlation confirmed significant positive relationships between all three TQM dimensions and service delivery quality (r = 0.581–0.714, p < .001). Multiple linear regression demonstrated that the three TQM dimensions collectively explained 63.7% of the variance in service delivery quality (R² = 0.637, F = 38.84, p < .001), with customer focus orientation emerging as the strongest predictor (β = 0.418, p < .001). Structural Equation Modelling confirmed customer focus as the construct with the largest total effect on service delivery (total β = 0.521), with employee involvement partially mediating this relationship (indirect β = 0.149). The study concluded that TQM implementation significantly enhanced local government service delivery in Kilembe Sub-County and recommended sustained TQM investment, citizen feedback system development, staff capacity building, and inter-departmental TQM coordination as priority interventions.

This paper examines whether urbanisation moderates the effect of carbon emissions on infectious diseases in Heavily Indebted Poor Countries (HIPCs) in Africa. The study is motivated by the public health risks created when rapid urban growth occurs alongside environmental degradation, weak sanitation systems, inadequate housing and limited health infrastructure. The analysis focuses on 28 HIPCs in Africa over the period 1990-2023 and uses three measures of infectious diseases: prevalence of HIV among the population aged 15-49, incidence of tuberculosis per 100,000 people and incidence of malaria per 1,000 population at risk. Carbon emissions are measured in metric tons per capita, while urbanisation is captured by urban population as a percentage of total population. The model incorporates gross domestic product per capita, current health expenditure and access to basic sanitation as control variables. Anchored on the Epidemiological Transition Theory and the Environmental Kuznets Curve hypothesis, the study estimates a fixed-effects panel regression model with an interaction term between urbanisation and carbon emissions. The results show that carbon emissions exert a significant positive effect on HIV prevalence, tuberculosis incidence and malaria incidence. Urbanisation also increases disease prevalence, although its direct effect on malaria is statistically weak. The study concludes that infectious-disease reduction in African HIPCs requires an integrated policy framework linking clean energy transition, sanitation investment, public health financing and urban disease surveillance. The paper contributes to the literature by showing that urbanisation is not only an independent determinant of infectious diseases but also a transmission channel through which environmental pollution worsens public health outcomes in fiscally constrained African economies.