DSpace 9

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Now showing 1 - 5 of 11

Applied Science
Faculty of Applied Science
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Faculty of the Built Environment
Business and Economic Sciences
Faculty of Business and Economic Sciences
Communication and Information Science
Faculty of Communication and Information Science
Engineering
Faculty of Engineering

Recent Submissions

Trade facilitation and revenue enhancement nexus in Zimbabwe
(International Journal of Business Ecosystem & Strategy, 2025-10-11) Gumbo, N.; Nkala, P.
Many developing countries currently base their trade policy modifications on the execution of trade facilitation reforms. There exists a gap between the policy intervention aimed at reform and the practical capacity to implement these trade facilitation reforms. This research employed a straightforward regression model to evaluate the effect of trade facilitation on revenue collections in Zimbabwe from 2009 to 2022, utilising the Logistics Performance Index as a proxy for trade facilitation. Total tax revenue, the variable of interest, is quantified as a percentage of gross domestic product, indicating the efficiency of government tax collection. The findings demonstrate that the efficiency of border clearance and the competence and quality of logistical services positively influence revenue collections, whereas the quality of trade and transport infrastructure negatively affects revenue collection . The findings indicate that governments should prioritise enhancing the efficiency of border processes and the quality of logistics services to increase revenue, while also mitigating the adverse effects of inadequate trade and transport infrastructure. The implementation of public-private partnerships, investment in alternative energy sources, automation of customs processes, and the establishment of quality management systems in customs administrations can facilitate this achievement. This study confirms that effectively implemented trade facilitation initiatives can realise their intended economic benefits, including reduced trade costs, enhanced efficiency, and increased access to international markets.
Blockchain Adoption in Healthcare: Enhancing Interoperability, Security and Data Exchange
(Journal of Information Systems and Informatics, 2025-09-03) Muderere, V.A.; Ndlovu, B.; Maguraushe, K.
Fragmented data across the healthcare industry increasingly impedes interoperability, compromises data security, and ultimately interferes with safe and quality patient care delivery. This research introduces a framework that uses blockchain technology to enhance interoperability and data exchange in healthcare environments. Leveraging qualitative methods, semi-structured interviews were held with fifteen health care practitioners at various facilities who gave their insights and perceptions of data sharing and blockchain technology. The findings were thematic and conceptualized through the Technology Acceptance Model, focusing on perceived ease of use and perceived usefulness, and the Technology-Organization-Environment framework that examined organizational support and regulatory compliance. Thematic analysis identified four main themes, including (i) factors influencing adoption: ease of use with four participants, usefulness with three participants, organizational support with two participants, regulatory compliance with two participants, and technical infrastructure with two participants.(ii) Application areas included patient data management, billing and payment, and remote patient monitoring;(iii) benefits such as a more effective decentralized system, safer storage of data, and patient empowerment.(iv) Challenges included privacy concerns, the costs of implementation and system failure, and patients' knowledge and stakeholders' digital literacy. The findings suggested that stakeholders knew the potential disruption to any blockchain system. However, major issues needed to be addressed before implementation. This research expands the conversation about innovative solutions to health care interoperability. It exposes potential ways to address the challenges to adoption. Recommendations for future research include examining the scalability and integration of blockchain technology across different healthcare environments and addressing the pressing need for empirical evidence regarding its real-world applications and impacts.
Quantile regression-based statistical modelling and forecasting of solar irradiance in Southern Africa
(National University of Science and Technology, 2024-07) Masache, Amon
Solar energy has increased interest because of its enormous and infinite potential to supply the global energy demand. The common and already existing photovoltaic (PV) solar power generation is directly and heavily dependent on so lar irradiance (SI). The rapid fluctuating uncertainty characteristics of SI make PV power generation have intermittent and uncontrollable characteristics that greatly impact the stability of solar power systems. One of the solutions is to improve the prediction accuracy of SI. This thesis contributes to this solution by presenting a guideline for developing an SI forecasting framework based on quantile functions (QFs) and quantile regression (QR). Data exploration was identified as the first and paramount stage in developing a modelling frame work. The thesis presented quantile distributional function modelling (QDFM) to overcome limitations in the currently used deterministic models to explore SI. Deterministic and stochastic elements in the data are combined and analysed simultaneously when fitting the QDFMs. The fitted QDFMs were then used to find population means as explorative parameters that consist of the data’s deterministic and stochastic properties. The thesis demonstrated that applying QFs when exploring data is a practical tool that gives more information than approaches that focus separately on measures of central tendency only or empirical distributions. In this thesis, the curse of dimensionality was identified as a problem affecting predictive models’ accuracy. The study suggested solving the problem as a second and paramount stage of developing a forecasting framework. With so many existing variable selection methods, the study sought to identify the best variable-embedded selection method for ii different location and time horizon combinations from Southern Africa solar irradiance data. Penalised quantile regression, regularised random forests, and quantile regression forest were introduced as new variable selection methods when forecasting SI data. Stability analysis, performance and accuracy metric evaluations were presented to determine the best algorithms in the different data situations and conditions. Identification of predictive models was addressed as the third and most common stage when predicting SI. This thesis contributed to renewable energy studies by conducting a comparative investigation of the quantile generalised model and quantile regression random forest as new non-parametric QR-based models to forecast SI. The thesis presented two chapters on the comparative investigation: one on additive models and the other on decision tree-based models. All non-parametric QR-based models presented were valid and stable to forecast SI from the Southern African region. They had similar behaviours regarding the prediction accuracy of the forecast distribution. However, additive models had better forecasting performances than decision tree-based models. Among the additive models, the QGAM had the near-best forecasting performance. Among the major contributions of this thesis is a suggested guideline for developing a solar irradiance modelling and forecasting framework.
Emotional Intelligence and Ageing in a Sedentary World: Impacts on Quality of Life
(IntechOpen, 2025) Dube, A.; Shaw, B.; Gundani, M.; Mathunjwa, M.; Shaw, I.
Ageing is a multidimensional process shaped by biological decline, psychosocial adaptation, and shifting societal roles. While much of the focus in gerontology remains on physical, and cognitive deterioration, emotional intelligence (EI) emerges as a powerful yet underutilised resource that enhances resilience, self-regulation, and social functioning in later life. In parallel, sedentary lifestyles, characterised by prolonged physical inactivity, are on the rise globally, compounding risks of chronic illness, cognitive decline, depression, and reduced quality of life among older adults. This chapter explores how EI functions as a buffer against the emotional, and psychological toll of sedentarism by enabling older individuals to reframe challenges, maintain social connection, and engage in meaningful routines. Drawing on cross-cultural case studies from Zimbabwe, South Africa, and the United Kingdom, the chapter illustrates how socioeconomic, and cultural contexts shape the development and expression of EI, and influence ageing experiences. Community-based initiatives, such as faith-driven programmes, lifelong learning, and intergenerational activities, are shown to foster emotional resilience, and reduce social isolation. Institutional strategies and policy interventions are also discussed as mechanisms to promote EI and active ageing in diverse populations. Ultimately, the integration of EI, along with physical activity, into ageing policy, and practice is positioned as both a preventive, and empowering approach, one that offers a low-cost, scalable, and culturally adaptable means of enhancing quality of life in an increasingly sedentary world. By addressing both emotional and physical dimensions of ageing, interventions hold significant promise for creating more inclusive, sustainable, and emotionally intelligent frameworks for elder care.
Role of Macroeconomic Factors Predicting Financial Performance of Commercial Banks in Zimbabwe 1990-2023
(International Journal of Research and Innovation in social Science (IJRISS), 2025-04-01) Nyathi, L.D.; Kureya, D.; Petegumbo, W.
The financial performance of commercial banks is intricately linked to the macroeconomic environment in which they operate. In Zimbabwe, a country characterized by economic volatility, hyperinflation, and fluctuating exchange rates, understanding the role of macroeconomic factors in shaping bank performance is critical. Therefore, this study investigates the extent to which key macroeconomic variables influence the profitability, stability, and overall financial health of commercial banks. Using a General Moments Methods (GMM) approach the study reveal that macroeconomic instability, particularly high inflation and volatile exchange rates, significantly impacts bank profitability and asset quality. Conversely, periods of economic growth and stable monetary policies are associated with improved financial performance. The study also highlights the resilience of Zimbabwean banks in navigating economic challenges, underscoring the importance of adaptive strategies and robust risk management practices. This research contributes to the broader discourse on the interplay between macroeconomic conditions and banking performance, offering valuable insights for policymakers, bank managers, and financial analysts. Therefore, the study recommends that government of Zimbabwe should address economic problems facing the entire economy. The poor macroeconomic instability facing the country also weighs down heavily to the banking sector. Due because of the poor economic environment and perceived risk tied to the country, local commercial banks are facing significant challenges to attract fresh capital from the international market.