This study assessed learner readiness for applied real estate education among prospective and current learners in Uganda, with a focus on the specific skills, tools, and knowledge required to seize emerging market opportunities in the country's rapidly urbanizing property sector. A cross-sectional survey design was employed, involving a stratified random sample of 300 participants drawn from urban centers including Kampala, Entebbe, Jinja, and Gulu. Data were collected using a structured, pre-tested questionnaire comprising validated Likert-scale items across six readiness dimensions: real estate market knowledge, digital tools proficiency, financial literacy and valuation, legal and regulatory awareness, entrepreneurial and business skills, and communication and negotiation competencies. Univariate analysis characterized sample distributions and readiness score profiles; bivariate analysis using chi-square tests and Cramér's V examined associations between learner characteristics and readiness dimensions; and Structural Equation Modelling (SEM) was applied to delineate direct and indirect pathways through which background variables and sub-competencies predicted overall readiness. Findings revealed that the overall mean readiness score stood at 2.86 out of 5.0 (SD = 0.62), indicative of a moderate but sub-optimal preparedness level. Educational attainment, prior real estate exposure, and occupation were significant determinants of readiness across all dimensions. The SEM model demonstrated acceptable fit (CFI = 0.953; RMSEA = 0.048) and confirmed that entrepreneurial skills (β = 0.448) and financial literacy (β = 0.367) were the strongest predictors of overall readiness. The study concludes that structured, competency-based real estate education curricula are urgently needed in Uganda and recommends integration of experiential learning, digital training modules, and legal literacy components in future programme designs.

Learner readiness constitutes a foundational yet frequently underexamined dimension of educational quality in Ugandan higher education. This study investigated learner readiness for skills acquisition, tool proficiency, and knowledge application among undergraduate students enrolled in accredited universities in Uganda, with a particular focus on the misalignment between theoretical instruction and practical preparedness. A crosssectional quantitative design was employed, drawing a stratified random sample of 412 undergraduate students from four purposively selected public and private universities in the central and western regions of Uganda. Data were collected using a structured self-administered questionnaire comprising validated scales for cognitive readiness, digital tool proficiency, attitudinal engagement, and perceived institutional support.
Analytical procedures encompassed univariate descriptive statistics, bivariate inferential analyses including Pearson correlation and chi-square tests, and confirmatory Structural Equation Modelling (SEM) implemented using maximum likelihood estimation. Results revealed that only 38.1% of respondents demonstrated high overall learner readiness, with digital tool proficiency registering the lowest mean score (M = 2.74, SD = 0.81). SEM findings confirmed that institutional support (β = 0.47, p < 0.001) and attitudinal engagement (β = 0.39, p < 0.001) were the strongest direct predictors of learner readiness, while cognitive readiness partially mediated the relationship between institutional support and overall readiness (indirect effect = 0.18, 95% CI: 0.11–0.26). Chi-square analyses indicated statistically significant associations between learner readiness categories and both gender (χ² = 14.32, df = 2, p = 0.001) and university type (χ² = 18.67, df = 2, p < 0.001). These findings underscore the urgent need for curriculum reforms, investment in digital infrastructure, and targeted pedagogical interventions that bridge the persistent theory-practice gap in Ugandan higher education institutions.

This study examined the prevailing dominance of Scopus-indexed journals in African scholarly publishing and interrogated its implications for the development and sustainability of local journal ecosystems across the continent. Using a quantitative cross-sectional survey design, data were collected from 420 academic researchers drawn from universities in five African sub-regions: East Africa, West Africa, Southern Africa, North Africa, and Central Africa. The study was guided by three specific objectives: to assess the level of awareness and utilisation of local versus Scopus-indexed journals among African scholars; to identify the key institutional, socio-economic, and epistemological barriers that impede the growth of local journal ecosystems; and to determine the principal components of a supportive policy and infrastructure framework for strengthening local journals. Data were analysed using descriptive statistics (frequencies, percentages, means, standard deviations), bivariate analysis (Pearson chisquare and correlation), exploratory factor analysis (EFA), and principal component analysis (PCA). Findings revealed that while awareness of local journals was moderately high (overall mean = 62.4%), their utilisation remained constrained by institutional pressure to publish in Scopus-indexed outlets, inadequate indexing infrastructure, limited editorial capacity, and low perceived impact factors. The PCA extracted four principal components explaining 88.6% of the total variance, namely: Institutional Prestige Pressure, Resource and Infrastructure Deficit, Epistemological Marginalisation, and Policy and Governance Gaps. The study concluded that the Scopus imperative, as currently operationalised in African institutions, systematically undermines indigenous knowledge production and perpetuates epistemic dependency. The study recommended the establishment of continental journal accreditation frameworks, integration of local journal metrics into academic appraisal systems, and increased funding for open-access local publishing infrastructure. These findings contribute to growing scholarly discourse on decolonizing academic publishing and advancing knowledge equity in the Global South.

This study examined digital credit expansion as a form of compensatory financial infrastructure, with specific focus on MTN Uganda's Mobile Money (MoMo) loan portfolio, which recorded a 66.7% growth between 2021 and 2023. Operating within the theoretical framework of financial intermediation and digital financial services, the study investigated how this unprecedented credit surge influenced financial inclusion, household income levels, and macroeconomic growth in Uganda. A mixed-methods design was employed, integrating quantitative data from 320 respondents drawn through stratified random sampling, alongside qualitative insights from 120 purposively selected key informants including financial regulators, MTN Uganda officials, SME operators, and rural borrowers.
Quantitative data were analysed using univariate descriptive statistics, bivariate Pearson correlation analysis, and Structural Equation Modelling (SEM), while qualitative data underwent thematic content analysis. Results revealed statistically significant positive associations between loan portfolio growth and financial inclusion (β = 0.621, p < 0.001), GDP growth (β = 0.534, p < 0.001), and household income improvement (β = 0.478, p < 0.001). Mobile network penetration emerged as the strongest antecedent of digital credit expansion (β = 0.589, p < 0.001). Qualitative findings identified eight dominant themes including emergency credit access, business capital expansion, high interest rate burden, and regulatory transparency gaps. The study concluded that MTN Uganda's digital credit growth functioned effectively as compensatory financial infrastructure, bridging critical gaps left by conventional banking institutions, though persistent challenges of over-indebtedness, digital exclusion of rural populations, and weak regulatory frameworks undermined the full realization of its developmental potential. The study recommended strengthening regulatory oversight on mobile credit, investing in rural digital infrastructure, and promoting financial literacy programmes to maximize the developmental impact of digital credit systems.

Digital literacy has emerged as a critical institutional imperative in higher education systems across Sub-Saharan Africa, yet its strategic integration into university management frameworks in Uganda remains inadequately theorised and empirically under-examined. This study examined the management strategies employed by Ugandan higher education institutions (HEIs) to drive digital literacy transformation, drawing on a concurrent mixed-methods design involving 348 respondents drawn from six purposively selected universities across Uganda. Quantitative data were collected through structured questionnaires and analysed using univariate descriptive statistics, Pearson correlation analysis, and Structural Equation Modelling (SEM), while qualitative insights were obtained through in-depth interviews and focus group discussions, subjected to thematic analysis. The SEM results revealed that leadership support (β = 0.61, p < 0.001), ICT infrastructure (β = 0.58, p < 0.001), and staff capacity building (β = 0.53, p < 0.001) were the strongest determinants of digital literacy integration outcomes. Bivariate analysis confirmed significant positive correlations between all management strategy dimensions and digital literacy outcomes (r = 0.44–0.62, p < 0.01). Qualitative findings further illuminated that leadership visibility, resource allocation priorities, and alignment with national ICT policy frameworks were central to institutional transformation. The study concluded that digital literacy transformation in Ugandan universities demands a coherent, multi-dimensional management strategy that synchronises leadership commitment, infrastructure investment, staff development, and policy alignment. The study recommends the development of institutional digital literacy frameworks anchored in robust ICT governance structures, ring-fenced budget allocations for digital infrastructure, and mandatory competency-based staff training programmes embedded within human resource management systems.

Uganda's digital credit market is dominated by two mobile network operators — MTN Uganda (MoMo Loans) and Airtel Uganda (Okoa) — whose overlapping yet structurally differentiated loan portfolios collectively serve more than 1.3 million active borrowers. This mixed-methods study examined the composition, uptake determinants, and default risk profiles of digital loan portfolios offered by these two providers, using data collected from 1,240 active borrowers across five districts in the Greater Kampala Metropolitan Area and a purposive sub-sample of 60 in-depth interview respondents. Univariate analyses revealed that borrowers were predominantly male (57.0%), aged between 26 and 35 years (33.8%), and earned monthly incomes in the range of 200,000 to 499,999 UGX (38.9%). MTN borrowers maintained significantly higher mean loan values (87,400 UGX vs. 74,800 UGX, p < 0.001) and longer repaymentperiods compared to Airtel borrowers, while Airtel borrowers recorded higher mean interest rates (14.1% vs. 12.3%, p < 0.001). Bivariate analysis identified statistically significant differences in agricultural loan uptake (χ² = 5.28, p = 0.038), repeat borrowing prevalence (OR = 1.28, 95% CI: 1.01–1.62, p = 0.048), and mean loan values. Multilevel logistic regression modelling, accounting for district-level clustering (ICC = 0.143), revealed that low income (Q1 AOR = 4.39, p < 0.001), loan stacking (AOR = 2.32, p < 0.001), and provider type — Airtel versus MTN (AOR = 1.36, p = 0.026) — were independent predictors of default. Qualitative analysis identified five dominant themes: accessibility, trust and reliability, financial burden, regulatory awareness, and provider preference, which contextualised and explained the quantitative findings. The study concluded that the two providers serve differentiated but overlapping borrower segments, and that systemic regulatory reform, improved borrower financial literacy, and product redesign are urgently needed to mitigate growing household debt burdens in Uganda's digital credit ecosystem.

This study examined the effect of Environmental, Social, and Governance (ESG) disclosure on firm performance and competitive advantage among listed financial service firms in Nigeria. Adopting an ex-post facto research design, panel data were collected from 31 firms over the period 2020–2024 and analyzed using fixed and random effects regression models. ESG disclosure was measured using environmental, social, and governance scores, while firm performance and competitive advantage were proxied by Return on Assets (ROA) and finance cost respectively. The findings revealed that environmental and governance disclosures had no significant impact on firm performance or competitive advantage in listed financial service firms in Nigeria. However, social disclosure exhibited a significant negative relationship with finance cost, indicating its role in enhancing competitive advantage through reduced financing costs. The results further showed that firm-specific factors such as age and leverage significantly influenced performance outcomes. Overall, the study concludes that ESG disclosure does not uniformly affect firm performance in Nigeria, although social disclosure plays a critical role in improving firms’ financial positioning. The study recommends improved ESG reporting standards and deeper integration of sustainability practices into corporate strategy to enhance long-term value creation.

Background: Uganda's child malnutrition crisis remains one of sub-Saharan Africa's most persistent public health emergencies, with approximately 29% of children under five experiencing stunting, 4% wasting, and 11% underweight. School feeding programmes have globally been recognised as effective compensatory mechanisms, yet Uganda lacks a structured, nutrition-focused school lunch model comparable to Japan's renowned Kyushoku system, which has virtually eliminated school-age malnutrition since its formalisation in 1954. Objective: This study assessed the feasibility, potential impact, and structural adaptations required to implement a Japan-inspired school lunch model as a compensatory nutrition system for Uganda's primary school children. Methods: A convergent mixed-methods design was employed, combining a cross-sectional quantitative survey of 412 pupils from 18 purposively selected primary schools in Kampala and Wakiso Districts with in-depth interviews and focus group discussions involving 89 key informants including teachers, parents, health workers, and policymakers. Anthropometric measurements (MUAC, HAZ, WAZ, WHZ), haemoglobin levels, and 24-hour dietary recall data were collected. Data were analysed using univariate descriptive statistics, bivariate chi-square and odds ratio analyses, and Structural Equation Modelling (SEM) to examine pathways from Japan-model adaptability to child nutritional outcomes. Qualitative data were analysed using thematic analysis. Results: Baseline stunting, wasting, and underweight prevalence stood at 42.3%, 18.7%, and 29.4% respectively. Anaemia affected 53.2% of the sample. SEM results confirmed a significant positive pathway from Japan-model adaptability to improved dietary diversity (β=0.612, p

This study examined the transition of artificial intelligence (AI) from a peripheral technical utility to a core strategic and leadership imperative within contemporary organizations, and explored the corresponding implications for advanced business education curricula. Employing a quantitative cross-sectional survey design, data were collected from 320 organizational leaders, middle managers, and business educators drawn from six industrial sectors finance, healthcare, manufacturing, retail, education, and logistics across Uganda and the broader East African region. Respondents were selected through stratified random sampling to ensure adequate sectoral and hierarchical representation. The survey instrument comprised 48 Likert-scaled items measuring AI integration levels, leadership readiness, organizational transformation indicators, and business education curriculum adequacy. Descriptive univariate statistics characterized the central tendencies and dispersions of AI adoption across sectors. Bivariate Pearson correlation analysis identified statistically significant relationships among AI strategic alignment, leadership competency, and organizational performance outcomes. Exploratory factor analysis (EFA) with principal axis factoring revealed the latent constructs undergirding AI leadership capabilities, while principal component analysis (PCA) confirmed a parsimonious two-component structure explaining 45.7% of the total variance in AI competency constructs. Results revealed that the finance sector demonstrated the highest AI integration score (M = 78.4%, SD = 8.2), while educational institutions lagged significantly (M = 52.3%, SD = 11.6). Strong positive correlations were observed between AI strategic alignment and technological investment readiness (r = 0.77, p < 0.001). Factor analysis extracted three interpretable factors—Strategic AI Leadership, Operational AI Readiness, and Ethical AI
Governance—together explaining 63.4% of common variance. The study concluded that advanced business education programs must urgently integrate AI management competencies, data governance frameworks, and ethical AI leadership modules to adequately prepare future organizational leaders for the demands of the fourth industrial revolution.

Uganda's transition toward a knowledge and technology-driven economy demands a critical examination of whether its environmental conditions adequately support the changing nature of work — a shift commonly described as moving from working hard to working smart. This study assessed Uganda's environmental readiness for the changing nature of work, with particular focus on digital infrastructure, workforce skills capacity, and policy frameworks. Employing a cross-sectional survey design, data were collected from 385 workers across six economic sectors in Uganda. Univariate analysis revealed moderate to low readiness across all three environmental dimensions. Bivariate correlations demonstrated statistically significant and strong associations between digital infrastructure, workforce skills, and smart-work readiness (r = 0.641, 0.587, and 0.489 respectively; p < 0.001). Structural Equation Modelling (SEM) confirmed that digital infrastructure was the strongest direct predictor of smart-work readiness (β = 0.421, p < 0.001), followed by workforce skills capacity (β = 0.383) and the policy environment (β = 0.274). Smart-work readiness, in turn, significantly predicted economic productivity (β = 0.512) and labour market transformation (β = 0.441). Sectoral analysis revealed a stark digital divide, with the ICT sector exhibiting the highest readiness (71.2%) and agriculture the lowest (18.4%). The study concludes that Uganda's environmental readiness for smart work remains critically insufficient, and recommends targeted investment in digital infrastructure expansion, skills upgrading programmes, and enabling policy reforms to accelerate an inclusive transition to the future of work.