Valley View University

In this study, we develop a mathematical model to describe the dynamics of student absenteeism, incorporating behavioural factors that influence the transition from regular class attendance to habitual absenteeism. The model’s local and global stability properties are analysed using the Routh-Hurwitz criterion and Bendixon’s geometric method. Our results indicate that absenteeism-free equilibrium is globally asymptotically stable when the absenteeism threshold number, ℛ_0<1 , indicating that student absenteeism would reduce over time. However, when ℛ_0>1 , absenteeism behaviour persists within the student population. Furthermore, we conduct local and global sensitivity analysis to determine the impact of the parameters on the absenteeism threshold number, utilizing partial rank correlation coefficients, three-dimensional plots and contour plots. The rate at which occasional and habitual absentees return to regular class attendance compartments, γ _1 and γ _2 , exhibit an inverse relationship with the absenteeism threshold number, while the rate at which regular students become occasional absentees, β , and the transitions rate to habitual absenteeism, δ , are directly proportional to the absenteeism threshold number. These observations highlight the parameters that influence absenteeism behaviour and therefore need to be targeted during intervention. Based on sensitivity analysis results, an optimal control and cost-effectiveness analysis is subsequently proposed to assess the impact of awareness campaigns (u_1) , class attendance monitoring (u_2) , and counselling (u_3) as control strategies. Fleming and Rishel’s technique was employed to investigate the absenteeism control model’s existence. The optimal intervention simulations and the cost-effectiveness analysis results indicate that the class attendance monitoring control strategy (u_2) is the most cost-effective strategy to address students’ absenteeism behaviour in educational institutions.

The rapid economic growth and increasing energy consumption in Africa have led to higher emissions, necessitating urgent and sustainable strategies. This study examines the nexus between environmental taxation, energy consumption, technological progress, economic growth, and CO₂ emissions. Using balanced panel data from 2000–2019 of 10 Sub-Saharan African (SSA) countries, Quantile Autoregressive Distributed Lag (QARDL) and GMM estimations were applied to capture both distributional heterogeneity and dynamic endogeneity. The QARDL results disclose that environmental taxes significantly reduce CO2 emissions in the middle and higher quantiles, while a 1

This study investigates the adoption and use of emerging technologies within the accounting industry, drawing empirical evidence from the Sefwi Wiawso Municipality in the Western North Region of Ghana. The primary objective of the study was to assess the extent to which accounting professionals and business managers have embraced selected emerging technologies and to identify the dominant technologies influencing contemporary accounting practices within the municipality. A quantitative research design was employed to ensure objectivity and allow for statistical generalization of findings. Primary data were collected through structured questionnaires administered to a sample of 154 respondents, comprising professional accountants and business managers operating in both the public and private sectors. The questionnaires were designed to capture respondents’ awareness, usage levels, and perceptions regarding the adoption of emerging technologies in accounting. Descriptive statistical tools, including frequencies, percentages, means, and standard deviations, were used to analyse the data and determine the extent of adoption of the selected technologies. The findings indicate that Artificial Intelligence (AI) is the most dominant and widely adopted emerging technology within the accounting industry in Sefwi Wiawso. AI applications are primarily used in areas such as automated data processing, error detection, and decision-support systems. This is followed by Big Data analytics, which is increasingly utilized to enhance financial analysis, forecasting, and strategic decision-making. Cloud Accounting also shows a moderate level of adoption, largely due to its benefits in terms of accessibility, cost efficiency, and real-time financial reporting. Robotic Process Automation (RPA), however, records the lowest level of adoption, suggesting limited awareness, high implementation costs, and inadequate technical expertise as possible barriers. Overall, the study concludes that the accounting industry in Sefwi Wiawso Municipality is gradually transitioning toward technology-driven practices. However, the adoption of emerging technologies is uneven, with significant disparities across different technological tools. These variations are influenced by factors such as organizational size, availability of infrastructure, technical skills, and financial capacity. Based on these findings, the study recommends targeted capacity-building programmes, including continuous professional training and digital skills development for accounting professionals. It also advocates for increased investment in technological infrastructure and supportive policy frameworks by government and regulatory bodies to facilitate the effective integration of emerging technologies. Such measures would enhance efficiency, accuracy, and competitiveness within the accounting industry, ultimately contributing to improved financial management and economic development in the region.

Foreign technology licensing can give firms rapid access to knowledge that would be costly to develop internally. However, absorptive-capacity theory argues that external knowledge creates value only when firms possess the internal ability to recognize, assimilate and use it. This study examined whether the use of technology licensed from a foreign-owned company was associated with product innovation in Ghana and whether research and development (R&D) engagement strengthened that relationship. The analysis used the Ghana World Bank Enterprise Survey 2023. After removing negative response codes and incomplete controls, the weighted analytical sample contained 682 formal establishments. Product innovation, foreign-company technology licensing and R&D engagement were measured directly from the survey. Hierarchical weighted logistic regression controlled for logged firm age, employment size, foreign ownership, top-manager sector experience, realized industry and region. Average predicted probabilities, alternative survey weights, a domestic-owned subsample, workforce-education controls, six-sector models, influence analysis, cross-validation and 1,000 stratified bootstrap replications were used. The weighted product-innovation rate was 19.0%, 17.4% of firms used licensed technology from a foreign-owned company, and 8.1% engaged in R&D. Licensing had a positive but statistically uncertain association before R&D was included (odds ratio = 1.55, 95% confidence interval [0.95, 2.53], p = .081). In the full interaction model, licensing was not significant among firms without R&D (odds ratio = 0.64, 95% confidence interval [0.31, 1.33], p = .232). R&D was strongly associated with product innovation (odds ratio = 11.26, 95% confidence interval [4.15, 30.54], p < .001). The licensing-by-R&D interaction was not significant (odds ratio = 1.63, 95% confidence interval [0.39, 6.78], p = .503). Adjusted innovation probabilities were 15.5% for firms with neither practice, 10.7% for licensing without R&D, 62.7% for R&D without licensing and 63.6% for firms using both. The findings support the importance of internal R&D capability but do not show that R&D converts foreign-company licensing into a stronger product-innovation advantage. Technology-transfer policy should therefore build internal learning systems and evaluate the depth, relevance and integration of licensed knowledge rather than treating license possession as sufficient.

In this study, a novel deterministic model for the transmission dynamics of Mpox, structured as a nonlinear autonomous system, is constructed from a 13-compartment epidemiological framework. The model incorporates eight human compartments, four animal compartments, and one representing the environmental pathogen load. We obtained the equilibrium points and the basic reproduction number ( ℛ_0 ) by applying the appropriate algebraic manipulations and the next-generation matrix method. A detailed qualitative analysis is carried out to examine the local and global asymptotic stability of the model’s equilibria. A global sensitivity analysis of the basic reproduction number is conducted by using the parameter estimates obtained by fitting the mathematical model to Mpox infection case data from Nigeria, the United States, and Ghana. Furthermore, the study extends to optimal control by incorporating seven time-dependent control interventions into the nonlinear autonomous dynamic model. Using Pontryagin’s Maximum Principle, we derived optimal control strategies that minimize both disease burden and intervention costs. This integrated method provides a strong mathematical foundation for comprehending Mpox epidemiology and informing evidence-based public health policy decisions.