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The study looked at the role and contribution of entrepreneurship industry to foster social and economic development through small, micro, and medium-sized businesses in South Africa. The conceptual research looked at the influence of small, micro, and medium-sized businesses (SMMEs) on South African development. The study's objective was to evaluate how small, medium-sized businesses (SMMEs) are now driving economic growth and solving social issues in a setting where big businesses and governments appear to be doing very little. As a result, the study examines how SMMEs might help the nation solve persistent societal evils including poverty, inequality, and social isolation. A desktop literature review research design was adopted to collect data on the role of entrepreneurship in South Africa, policies and practices of big business and government that exacerbate social issues in communities and impede socioeconomic development, as well as the specific roles that SMMEs play in achieving socioeconomic development goals. Findings from research indicate that, among other development outcomes, SMMEs are at the vanguard of creating jobs and fostering social and political justice in the nation. Future empirical studies that account for and evaluate the importance of SMME contributions to the construction of economic, social, and political justice in the nation are advised because this work lacks the empirical support necessary to substantiate its conclusions and observations.  

The present study undertakes an analysis of monitoring and evaluation as a pragmatic methodology for enhancing the efficacy of municipalities in the context of South Africa. Research findings indicate that a significant obstacle faced by South African municipalities is the issue of substandard performance. These aspects can be linked to several reasons, such as inadequate allocation of resources, limitations in capacity, and deficiencies in monitoring and assessment processes. This article posits that the use of monitoring and evaluation (M&E) is crucial in addressing instances of suboptimal performance within municipalities. There exists a necessity to enhance the monitoring and evaluation (M&E) systems in order to attain efficient performance management and ensure the provision of high-quality service delivery. The research was conducted among three distinct municipalities, namely Amajuba, uThukela, and uMgungundlovu, located in the province of KwaZulu-Natal (KZN). The sample population comprised of municipal officials belonging to the Performance Management System (PMS) and Corporate Services units. The study employed a qualitative methodology and deliberately selected important participants who possessed knowledge and a comprehensive understanding of the subject matter under investigation. Furthermore, it is worth noting that the sample size consisted of 20 people. The researchers organized focus group conversations in order to gather data, which was subsequently controlled through the utilization of the NVivo software application. The findings of the study indicate that monitoring and evaluation (M&E) is a crucial component in enhancing the performance of local government. Its primary purpose is to establish the essential circumstances for achieving greater levels of performance that are sustainable over an extended period. Municipalities are required to demonstrate a firm dedication to the prioritization and adoption of municipal monitoring and evaluation (M&E) as an essential tool for facilitating progressive local governance. This commitment involves the institutionalization of M&E practices, the enforcement of mandatory adherence to established systems and procedures, the integration of information technology systems to enhance and fortify the implementation of M&E, and the utilization of participatory M&E approaches to assess the effectiveness of municipal functions and development endeavors.

This study advances research and practice related to adopting artificial intelligence (AI) in the context of South Africa (SA). The study evaluated AI adoption by South African manufacturing Small and Medium Enterprises (SMEs); established the challenges faced by manufacturing SMEs in adopting AI; and developed a framework for adopting AI for manufacturing SMEs’ growth and survival. The study adopted a systematic literature review approach. Articles from Scopus and Google scholar databases, ranging from the years 2018 to 2024, were used. Of the 206 articles found, 54 were shortlisted. The systematic review analysis was performed using the PRISMA framework. The results identified AI adoption by South African manufacturing SMEs is low, limiting their innovation and productivity. The results also show, despite the numerous benefits AI adoption can offer manufacturing SMEs in the country, a major constraint is the lack of a framework to enhance adoption and implementation. Hence, this study was conducted to develop a framework to improve AI adoption by South African manufacturing SMEs. The findings contribute to the body of knowledge and provide new insights to manufacturing SME owners/managers, policymakers and practitioners into AI adoption to enhance manufacturing SMEs’ ability to compete on the global stage.

The proliferation of technology has innovated new ways of saving and investing money: online savings and investment platforms [OSIPs]. Predicting the intention to adopt Fintech has triggered the interest of many researchers in academia and industries. The primary objective of this study was to examine factors influencing the intention to adopt OSIPs in Nigeria by using data gathered from 640 digitally active citizens from selected cities in Nigeria. Reliability and validity tests were conducted through construct reliability and discriminant validity, respectively, through WarpPLS. Data were computed with the Statistical Package for the Social Sciences (version) 24 and analyzed with structural equation modeling via WarpPLS. The findings of this study showed that performance expectancy, effort expectancy, and social influence significantly affect attitude while facilitating conditions predict intention to adopt. It was also found that attitude significantly influences the intention to adopt OSIPs. The paper also discusses the study’s research limitations and presents implications for theory and practice.

Small and Medium Enterprises (SMEs) in South Africa previously faced challenges due to limited resources, restricted access to technology, and the need to constantly adapt to a dynamic business environment. The introduction of Generative Artificial Intelligence (AI) emerged as a potential solution to these issues, promising to enhance operational efficiency and strategic decision-making. As a representative of developing economies, South Africa experienced a growing interest in AI technologies. This study was conducted to explore the impact of generative AI on SME productivity in South Africa, an area which had been underexplored. Employing a qualitative methodology, the study evaluated the current state and implications of generative AI in South African SMEs. It involved in-depth interviews to gather perceptions, experiences, challenges, and benefits from SME owners and managers regarding the adoption of generative AI technologies. The findings analysed via R Statistical Software revealed significant insights into the specific areas where generative AI substantially impacted SME productivity. It also identified the challenges and opportunities associated with the adoption of generative AI by SMEs, as well as the potential long-term implications. Key findings included notable improvements in data-driven decision-making, operational efficiencies, and market expansion strategies. However, the study also highlighted barriers such as the lack of technical expertise, initial setup costs, and concerns over data security. Overall, the impact of generative AI on SMEs in South Africa was found to be predominantly positive, paving the way for further technological advancements and adoption in the sector.

This study investigated the effects of digitalisation of tax administration on tax compliance among selected small and medium enterprises (SMEs) in Ibadan North West Local Government Oyo State, Nigeria. The study was anchored on the Technology Acceptance Model (TAM), which explains technology adoption through perceived usefulness, perceived ease of use, and external constraints. A descriptive survey design was adopted, and structured questionnaires were administered to 367 SMEs across key business sectors. Of these, 352 valid responses were analysed using SPSS through descriptive statistics and ANOVA. The study examined the level of digital technology adoption, the perceived influence of digital tax administration on compliance, the drivers of non-compliance, and preferred policy measures for improvement. Findings revealed generally low digital technology adoption among SMEs, with 42.9% reporting very low adoption and 36.6% reporting low adoption. The major barriers were poor internet connectivity, high cost of technology and digital tools, limited technical skills, and inadequate awareness. Perceptions of digital tax reforms showed limited realised compliance benefits, as 48.9% of respondents reported no noticeable improvement in compliance, 21.3% reported improved ease of compliance, while 29.8% stated that compliance had become more difficult. Non-compliance was mainly linked to limited awareness of tax obligations, weak enforcement, affordability challenges, and low digital capability. The study concludes that digitalisation can improve SME tax compliance only when foundational readiness gaps are addressed. It recommends improving broadband reliability, reducing digital access costs, strengthening taxpayer education, simplifying digital tax processes, providing practical training, and ensuring consistent and fair enforcement.

Sophisticated AI applications like ChatGPT and Grammarly offer distinct advantages for enhancing writing proficiency. They assist users in conceptualising ideas, organising material, and refining writing style, whereas Grammarly focuses on improving grammar, punctuation, and clarity with context-aware recommendations. This is particularly relevant for students who are non-native English speakers, as it supports them and helps bridge educational disparities. While these instruments markedly enhance scholarly writing abilities, their efficacy in tertiary education remains a subject of debate. Recent occurrences of academic dishonesty associated with the improper use of generative AI technologies have negatively impacted higher education. This study assesses the impact of artificial intelligence on enhancing academic writing abilities in students who are not native English speakers. In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria, this study consolidates evidence from scholarly literature, policy reports, and institutional case analyses. Keywords, synonyms, and subject headings were employed to query three electronic databases from 2021 to 2025. The electronic repositories included Scopus, Emerald Insight, Google Scholar, and ProQuest. The evaluation of the publications was conducted through titles and abstracts, followed by an assessment of the full-text papers against the qualifying criteria. The results were derived and amalgamated into a narrative synthesis from selected publications. The results underscored AI's ability to customise and improve the educational experience for learners.

Rapid urbanisation in South Africa is reshaping the country’s spatial geography, largely driven by internal migration from rural areas and financially disadvantaged towns to urban centres. Key destinations, such as Gauteng, KwaZulu-Natal, and Cape Town, attract migrants seeking work, education, and better lifestyles. However, this movement places greater strain on urban systems by increasing demand for housing, water, energy, sanitation, transportation, and other basic public amenities. It also adds to urbanisation, overpopulation, the spread of informal settlements, land-use disputes, and governance issues. These shifts underscore the urgency for municipalities to shift away from planning models built on stable demographics and toward governance systems that respond to migration and demographic shifts. This research explores the connection between internal migration and local governance in South Africa, with an emphasis on the effects for inclusive service provision and urban sustainability. A qualitative study technique was adopted, including a conceptual document review of academic, policy, and institutional materials. The research reviewed data on migration patterns, governance capacity, participatory mechanisms, and planning solutions in the context of local government. Results showed that several municipalities have not adequately embraced migration dynamics in their urban planning practices. Existing participation methods generally exclude migrants and other transitory communities, leading to underrepresentation and choices that fail to capture changing urban demands. Delayed planning decisions increase infrastructure pressure, service provision backlogs, informal areas, and spatial inequalities. The study suggests that internal migration needs to be central to urban planning and accountability. It advocates for migration-informed spatial decision-making, increased engagement of mobile residents in Integrated Development Plan (IDP) operations, and unified governance revisions to promote inclusive and urban sustainability.

Information and Communication Technology (ICT) Small and Medium Enterprises (SMEs) in South Africa's Gauteng Province face high failure rates despite their economic importance, thus creating an urgent need to investigate business sustainability. This research examined the implementation challenges of ICT SMEs and the enhancement of competitiveness through shared value creation. A qualitative, interpretivist design was employed, with semi-structured interviews conducted with 12 purposively selected ICT SME owners and senior managers in Gauteng Province. The thematic analysis revealed three principal themes. One key finding was that implementation barriers operate at three interconnected levels: the business environment, industry level, and institutional level. At the Business-Environment level, issues include load shedding, regulatory complexity, and funding gaps. The competitive level interrogates incumbent dominance and high buyer power, while the institutional level reviews skills, competencies, time and cost constraints. Another important finding was that SMEs overcome these barriers through value-chain innovations such as energy efficiency, inclusive hiring, and intellectual property development; through strategic positioning, including focused differentiation and organizational agility; and through cluster engagement, such as vendor partnerships and peer networks. Integrating their selected strategies yields productivity gains, cost reductions, and incidental shared value. The study proposes a Resilience-Through-Shared-Value Framework that provides entrepreneurs with a four-phase process for turning barriers into advantages. It also provides policymakers with guidance on tiered compliance and on infrastructure support and development, and development agencies with a diagnostic framework for multi-barrier mentorship programs.

Enterprise Resource Planning (ERP) solutions such as SAP represent a vital investment for organisations seeking to unify varied operational activities into integrated, data-driven platforms. In institutions of higher learning, the use of ERP systems is a crucial component of digital transformation efforts aimed at improving administrative efficiency, institutional governance, and competitive positioning. This article examines the impact of SAP ERP implementation on both organisational and employee dynamics for administrative staff at the Durban University of Technology (DUT), emphasising technostress, digital fatigue, employee well-being, and post-implementation adaptation within a constrained higher education environment. Utilising a desktop appraisal methodology, the study synthesises existing literature to demonstrate how decisions made in the pre-implementation and implementation phases consistently affect employee experiences and organisational outcomes post-implementation. The study indicates that attaining enduring ERP effectiveness requires continuous capacity development, cooperative implementation approaches, and employee-centered support frameworks. The research develops an interdisciplinary model by integrating socio-technical, psychological, capacity-building, and normalisation perspectives, thereby improving the understanding of the human factors involved in ERP deployment within higher education. The study introduces the ERP Lifecycle–Employee Adaptation Framework (ELEAF), which outlines the progressive escalation of technostress during the pre-implementation, implementation, and post-implementation phases, linking each stage to a pertinent theoretical mechanism and a set of organisational interventions. The findings indicate that inadequate training, limited organisational support, dependence on key users, and absence of employee engagement contribute to technostress, digital fatigue, reduced job satisfaction, and challenges in post-implementation adaptation. The study further demonstrates that decisions taken throughout the ERP lifecycle have enduring impacts on employee well-being and organisational effectiveness beyond the system's implementation. This highlights the tangible consequences for higher education institutions, stressing the importance of continuous training, institutional support, systematic information sharing, employee wellness initiatives, and staff-centric ERP management to enhance long-term value achievement. It consequently lays the groundwork for future research on the human dimensions of digital transformation in resource-constrained environments.