ABSTRACT. In 2025 the European Union (EU) and China reached a significant landmark of 50 years of diplomatic relations. Back in 1975, when formal diplomatic relations were established, the European Community was a 12-member state arrangement, and China was just escaping from the effects of the Cultural Revolution. Both experienced significant changes in these 50 years and both developed from very different starting points. Despite this both have travelled along significantly different paths ultimately both becoming economic and political pillars in the world. This paper will unravel the relationship from its outset in 1975 and pursue the separate journey’s which these two state actors have pursued. The early period of the relationship revealed significant cooperation. Since the 2000s, the declining EU economic standing and the rapid rise of China’s trade and economy have caused increasing rivalry between them. Nonetheless, the EU and China are both willing to improve the relationship in areas where they complement each other such as green energy and technology as well as finding solutions in areas of conflict.

ABSTRACT. The transition of AI and ML from conceptual frameworks to essential instruments for business financial sustainability in recent volatile markets is examined in this review study. The study concludes that real-time analytic and predictive intelligence are dynamic organizational competences rather than merely programs enhancements by synthesizing studies from 2015 to 2025 utilizing the PRISMA framework for selection and a standard approach. By substituting proactive, forward-looking techniques for periodic, retrospective reporting, these technologies enable businesses to become "digitally mature," which allows them to outperform their competition. With a focus on the mechanics of financial supervision, this systematic review looks at 52 high-impact studies to evaluate how predictive intelligence changes risk management. The selected research paper's findings have been presented using the SWOT framework. The investigation was intended to study how "early-warning analytic and predictive intelligence through AI and ML" might prevent financial meltdowns by identifying indications of liquidity stress through real-time analytic.

ABSTRACT. This study examines whether economic development levels across the five member states of the Southern African Customs Union (SACU), the world's oldest customs union, are converging or diverging, and assesses the extent to which globalisation shapes this process. Despite the growing prominence of regional economic communities (RECs) as vehicles for collective development, robust empirical evidence on their effectiveness, particularly in an increasingly interconnected world, remains limited. This study addresses that gap by drawing on panel data spanning 1990 to 2023 for Botswana, Eswatini, Lesotho, Namibia, and South Africa. The study employs a self-constructed, geometrically aggregated economic development index encompassing five dimensions: income, employment, human capital, health, and inequality. Globalisation is operationalised through the KOF Swiss Economic Institute's disaggregated indices capturing economic, social, and political dimensions. The empirical analysis accounts for cross-sectional dependence, structural breaks, and slope heterogeneity, features commonly overlooked in conventional panel estimations. Specifically, the study applies a Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) model and uses second-generation unit root procedures and both Pedroni and Westerlund cointegration tests. The findings reveal several noteworthy contributions. First, evidence of strong sigma (σ) convergence is confirmed, indicating that disparities in economic development among SACU members have narrowed significantly over the study period. This supports the view that SACU, through mechanisms such as the Common Revenue Pool, the Common Monetary Area, and successive trade agreements, has played a meaningful role in propelling the development trajectories of its smaller member states. Importantly, no convergence clubs were identified, suggesting that all members are trending toward a common development level rather than distinct sub-groupings. Second, when globalisation dimensions are introduced as conditional variables, only economic globalisation emerges as statistically significant. Its positive coefficient on the development gap indicates a divergence-inducing effect, suggesting that greater economic openness disproportionately benefits South Africa, given its dominant position as the regional economic hub and primary recipient of foreign direct investment. Social and political globalisation dimensions, by contrast, show no statistically significant influence on development convergence within SACU. These results carry important policy implications. For SACU as an institution, deepening regional integration beyond its current form, particularly through stronger industrial policy, enhanced competition frameworks, and diversification strategies, is essential to counteract the divergence pressures generated by economic globalisation. For smaller member states, reducing dependence on customs revenue transfers and building more resilient, diversified economic structures would improve their capacity to benefit from global integration. Greater participation in global value chains and international economic processes more broadly would further strengthen SACU's collective development trajectory.

ABSTRACT. This paper explores the drivers and technologies shaping the future of sustainable housing in South Africa, using Pretoria as a case study. Drawing on qualitative interviews with six prominent property developers, the study explores economic, environmental, and regulatory factors influencing the adoption of smart green homes. Findings reveal that, despite global momentum, South Africa’s residential sector lags due to high implementation costs, limited consumer awareness, regulatory constraints, and challenges with market receptivity. Nevertheless, drivers such as energy security, long-term cost savings, environmental responsibility, corporate commitments, and evolving consumer trends highlight significant growth potential. Key enabling technologies include solar energy systems, water-saving devices, smart metering, energy-efficient appliances, and eco-friendly building materials. The study contributes to theory by extending sustainability and housing adoption frameworks to the South African context, while offering practical insights into policy design, developer strategies, and consumer education. By situating these findings within the United Nations Sustainable Development Goals (SDG 11 - Sustainable Cities and Communities and SDG 7 - Affordable and Clean Energy), the paper underscores the originality and value of smart green homes as both a feasible solution and a strategic imperative for emerging economies, positioning them as a cornerstone of sustainable urban development. The study also emphasises the crucial role of cooperative alliances between the public sector, commercial developers, and civic society in removing structural obstacles. The case study shows how localised solutions, especially in situations of energy insecurity and rapid urbanisation, can be scaled up to address broader national concerns. By integrating global lessons with South African realities, the paper advances a nuanced understanding of sustainable housing adoption in emerging economies. Ultimately, the findings provide a roadmap for aligning housing innovation with inclusive growth and long-term resilience.

ABSTRACT. Financial distress and company failure continue to provide substantial risks to stakeholders throughout financial markets, highlighting the necessity for dependable early-warning financial distress signals. This study assesses whether the factors comprising the Bankruptcy Prediction Indicators Approach (BPIA) are statistically significant predictors of financial distress and evaluates the Bankruptcy Prediction Indicators Approach (BPIA)'s efficacy as a practical instrument for measuring and anticipating financial failure. A quantitative research design was adopted, with secondary data sourced from the IRESS database. Using purposive sampling, a research sample of nine companies delisted from the Johannesburg Stock Exchange (JSE) in 2022 was selected based on pre-defined eligibility criteria. Statistical analysis was conducted using SPSS to test the study's objective and examine the predictive capacity of the Bankruptcy Prediction Indicators Approach (BPIA) factors. The findings reveal that 55% of the variance in financial distress outcomes is explained by the Bankruptcy Prediction Indicators Approach (BPIA), with results demonstrating statistical significance, confirming the factor's strong explanatory and predictive power. These results establish the Bankruptcy Prediction Indicators Approach (BPIA) factors as a credible and reliable instrument for identifying early warning signs of financial distress before failure becomes irreversible. The study makes a meaningful empirical contribution to corporate governance and financial risk literature by providing stakeholders with a validated analytic tool. Those charged with governance are urged to integrate Bankruptcy Prediction Indicators Approach (BPIA) assessments into routine financial oversight practices, enabling the early detection of distress signals and the timely implementation of corrective measures. Regular Bankruptcy Prediction Indicators Approach (BPIA) monitoring equips management to act proactively, reducing the likelihood of corporate failure and protecting stakeholder value.

ABSTRACT. Investors obtain data from the trading market and make investment decisions based on this information, which reflects their expectations of future price movements. Consequently, numerous contemporary trend-analysis techniques have been developed and refined over time. Nonetheless, precise trend forecasting remains difficult due to the sheer volume and complexity of market information. Although traditional time series models such as ARIMA and GARCH have been widely examined and shown to be effective for forecasting, their performance often remains insufficient. In recent years, machine learning (ML) has emerged as a powerful alternative, delivering remarkable advancements in tasks such as regression and classification. This progress suggests strong potential for applying ML methods to financial time series prediction. In this study, the predictive accuracy of traditional and ML algorithms is compared through application of South African stock price data. The findings revealed that models capable of capturing nonlinear relationships and asymmetric volatility, such as ANFIS, provided clear advantages in stock price forecasting. ML algorithms surpassed the traditional models in precision. These results offer practical value for investors and market analysts by enabling more robust predictions in volatile market conditions. Future research could expand the analysis to multiple firms, incorporate macroeconomic and sentiment indicators, and explore hybrid models integrating ANFIS with deep learning for enhanced forecasting accuracy.

ABSTRACT. In this study we investigate the determinants of bank failure risk in emerging and developed markets through the integration of Basel regulatory frameworks, ESG performance indicators, and political economy factors. We argue that bank failures are not only affected by the standards developed by the Basel committee on bank supervision, but by also ESG performance, and political economy factors. Although ESG performance is generally recognized as a key non-financial risk indicator, it is generally not incorporated into traditional bank failure models. Furthermore, political economy factors such regulatory quality, governance quality and state ownership are generally not included into the bank failure models, although they can significantly influence bank risk and the effectiveness of regulatory institutions. We use a panel data from listed banks in emerging and developed markets over a period of 20 years from 2005 -2025. The study uses dynamic panel estimation models. The study contributes to knowledge through understanding the linkages of regulation, ESG performance and political economy factors. Finally, the study also offers a comparative analysis of bank stability between emerging markets and developed markets.

ABSTRACT. This article is envisioned to identify the predictors of attrition using the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and logistic regression. A review of the literature shows that traditional statistical methods are used to identify predictors, but do not support multi-criteria decision-making under uncertainty. To give the theoretical grounding for the current study, Mobley, Griffeth, Hand, and Meglino's (1979) model, grounded in the withdrawal decision process, was adopted. The study was influenced by the positivist paradigm, and it was quantitative. A dataset of 1470 employees accessed from Kaggle was used to achieve the study objective. The data were analysed in Python, and since the target variable was binary, logistic regression was deemed an appropriate statistical technique. The logistic regression model identified employees with predicted attrition probabilities ranging from approximately 0.08 (lowest risk) to 0.85 (highest risk). A strong negative Spearman's rank correlation of approximately -0.89 was found between Fuzzy-TOPSIS coefficients and logistic regression. The other key insights were that the sales had the highest attrition rate (20.63%). Another key finding was that employees in the research and development department had the highest number of employees who resigned, and further analysis revealed that, on average, younger employees have fewer total working years and earn less monthly income. They also tend to have slightly lower job satisfaction. The implication of the study is that it empowers managers with strategies to mitigate employee attrition, as it is costly.

ABSTRACT. Outward foreign direct investment (OFDI) has been widely regarded as a critical strategy for emerging market firms (EMFs) to access overseas resources and innovate. However, existing research has not reached a clear consensus on whether, and to what extent, OFDI contributes to EMFs’ innovation performance. Drawing on resource orchestration perspective, we contend that OFDI divergently influences firm innovation through resource acquisition and resource allocation mechanisms, and illuminate an inverse U-shaped relationship between an EMFs’ OFDI and innovation performance. Furthermore, this nonlinear relationship, we posit, is conditioned by multi-level institutional environment factors, namely international relations between home and host governments (international level), distance to central government of home country (country level), and local factor market development (regional level). Using a sample of 1,102 Chinese publicly listed manufacturing firms during 2008-2021, we find that the nonlinear relationship between EMFs’ OFDI and innovation performance is attenuated by favorable international relations and a greater distance to central government while being amplified by factor market development. Overall, our work contributes to international innovation literature in the context of emerging economies, and delivers critical implications for practitioners.

ABSTRACT. This study examines which innovation practices are supported by public funding in firms belonging to the PROVERE iNature collective efficiency strategy financed under CENTRO2020. The paper responds to a clear gap in the literature: studies on innovation typologies rarely connect those typologies to the direct allocation of public subsidies, particularly in tourism and other service-intensive activities. Drawing on the Oslo Manual 2018 classification, the analysis focuses on product innovation (goods and services) and business process innovation (production, logistics, marketing and sales, information and communication systems, administration and management, and product/business process development). The study uses secondary data from 12 approved projects submitted by private firms in the consortium between 2016 and 2020. Project applications were coded through content analysis and combined with firm-level data from SABI. Descriptive statistics, Pearson correlations, exploratory factor analysis, and cluster analysis were conducted in SPSS 28. The results show that public funding supported innovation in a broad and transversal way rather than in isolated categories. Product-service innovation and process innovations in marketing and sales, production, information and communication systems, and administration and management were the most salient categories. Most firms combined product and process innovation, and repeated mixed patterns were identified across cases. Although the small sample and low KMO value advise caution, the evidence suggests that public funding in this setting encouraged diversified innovation portfolios. The paper contributes by integrating innovation architecture, public funding, and firm characteristics in a single framework, and it offers implications for regional innovation policy, tourism development, and future evaluation of subsidy programs.

ABSTRACT. This paper reviews procurement and quality control challenges in South Africa’s energy sector, highlighting how inefficiencies, corruption, and governance failures contribute to load-shedding, inflated costs, and project delays. While blockchain has been explored in various sectors, its application to the unique complexities of South Africa’s energy procurement, marked by bid manipulation, political interference, and weak quality oversight, remains underexplored. This study addresses that gap by situating blockchain within this context and assessing its potential to enhance transparency, accountability, and operational efficiency. A total of 160 academic and industry sources published between 2018 and 2024 were identified, with 28 selected based on relevance, credibility, and impact for detailed thematic analysis. Findings indicate that blockchain’s decentralised, tamper-proof structure can streamline procurement processes, automate verification through smart contracts, and strengthen quality control. The study also identifies adoption barriers, including resistance from entrenched systems, high implementation costs, and the absence of clear regulatory frameworks. Recommendations include establishing public–private collaboration structures, implementing targeted pilot projects, and introducing legislative measures to enable adoption. By addressing both the opportunities and barriers, the study advances the discourse on digital transformation in public procurement and offers practical pathways to promote transparency, efficiency, and sustainable energy delivery.

ABSTRACT. The integrity of operational processes in policing increasingly depends on the effective integration of digital and forensic technologies, particularly in complex investigations where evidence management influences organisational performance and public trust. This study examines the digital transformation of firearm evidence management in murder investigations, using the South African Police Service (SAPS) as a case study. Although firearm evidence plays a critical role in case progression and accountability, the study identifies persistent operational challenges, such as knowledge gaps, inconsistent procedures, and chain-of-custody failures that weaken investigative efficiency and institutional credibility. Semi-structured interviews were conducted with investigating officers, crime-scene specialists, and ballistic experts to explore practitioners' experiences and identify systematic weaknesses across the investigative chain. Drawing on the qualitative findings, the study proposes a digital transformation and organisational capabilities conceptual framework that demonstrates how technologies such as electronic chain-of-custody systems, automated evidence-tracking platforms, ballistic-imaging tools, and AI-supported crime scene reconstruction applications can enhance accuracy, transparency, and process standardisation in firearm evidence management. Findings indicate that while personnel recognise the value of firearm evidence, procedural inconsistencies and documentation lapses disrupt workflow continuity and contribute to delays. The results demonstrate that digitalisation can significantly reduce administrative errors, streamline evidence flow, strengthen oversight and enhance organisational accountability. Practical implications include integrating digital platforms into operational protocols, standardising procedures, and prioritising continuous professional development to support technology adoption. The study highlights how a digitally driven forensic process can serve as a strategic asset in transforming public-sector performance and advancing evidence-based policing. The study concludes that technology-enabled firearm evidence management offers a scalable model for improving investigative performance and broader policing outcomes.

ABSTRACT. Additive manufacturing (AM) has increasingly emerged as a strategic capability with potential to improve manufacturing flexibility, supply-chain resilience, and sustainable production performance. However, implementation outcomes remain uneven across industrial contexts due to differences in technical feasibility, operational suitability, and organisational readiness. This study examines AM implementation within resilient and sustainable supply-chain systems through an interdisciplinary literature synthesis integrating engineering, operations-management, and organisational capability perspectives. The analysis demonstrates that AM provides strongest strategic value under conditions characterised by low-to-medium production volume, high component complexity, rapid responsiveness requirements, and disruption-sensitive supply environments. The findings further indicate that implementation success depends not only upon manufacturing capability, but also upon alignment between operational production requirements, workforce capability, governance adaptation, certification requirements, and digital infrastructure readiness. While AM offers opportunities for distributed manufacturing, digital inventory management, and improved production flexibility, its benefits remain contingent upon the organisational capacity to integrate these capabilities effectively within existing manufacturing and supply-chain systems. To integrate these dimensions systematically, the study develops an implementation-oriented decision-support framework structured around three interrelated dimensions: technical feasibility, operational suitability, and strategic implementation readiness. The framework conceptualises AM implementation as a systems-level capability-development process rather than a discrete technology-adoption initiative. The study contributes to AM and supply-chain resilience literature by providing a unified analytical framework explaining how technological capability, operational conditions, and organisational adaptation interact to shape implementation outcomes. The findings additionally provide practical guidance for managers evaluating AM deployment within resilient and sustainable manufacturing systems and offer a foundation for future empirical research examining implementation effectiveness across different industrial sectors and operational environments.

ABSTRACT. Orientation: Digital inclusion is increasingly recognised as a key enabler of organisational effectiveness and sustainability among Small and Medium Enterprises (SMEs). However, the role of indigenous languages in facilitating inclusive ICT adoption remains underexplored in the South African context, especially in rural areas. Research purpose: This study explores how integrating indigenous languages into information and communication technology (ICT) promotes digital inclusion and enhances SME development in South Africa. Motivation for the study: Despite advances in digital technologies, many SMEs, particularly in rural and linguistically diverse regions, remain excluded due to language barriers, limited infrastructure and inadequate institutional support. Research approach/design and method: A mixed-methods research design was applied, with quantitative data collected from 116 SMEs and qualitative data obtained through semi-structured interviews with SME owners and managers across district municipalities in Limpopo Province. Descriptive statistics and thematic analysis were used to analyse the data. Main findings: Integrating indigenous languages into ICT enhances communication, customer engagement, and market accessibility. SMEs utilising indigenous languages reported improved operational efficiency and stronger relationships with local communities. Practical/managerial implications: The study highlights the need for policymakers to promote multilingual digital platforms, strengthen ICT infrastructure, and support SMEs through language-inclusive digital solutions. Contribution/value-add: This study adds to the literature on digital inclusion and SME development by establishing linguistic accessibility as a fundamental factor influencing ICT effectiveness, business sustainability and inclusive economic growth in South Africa.

ABSTRACT. This study examines the implementation of the vertical lift module spare parts shuttle within Global Automotive Company in the maintenance warehouse operations, concentrating on the optimization of storage utilization through Artificial Intelligence driven analytics. The study aimed to explore how Artificial Intelligence can enhance inventory management by altering inventory levels in response to changes in storage capacity and developing affordable solutions to overcome storage limitations. Using qualitative data collected from semi-structured interviews with key stakeholders at Global Automotive Company, the findings reveal that vertical storage systems significantly improve operational efficiency, space utilization, and inventory accuracy. Although challenges such as technical issues and the need for ongoing training were also identified. The study concludes that to enhance training initiatives, funding automation, and encouraging continuous improvement methodologies. Global Automotive Company Maintenance Warehouse can improve its supply chain performance and keep a competitive edge in the automotive sector by tackling these issues and utilizing cutting-edge technologies.

ABSTRACT. The global fashion industry has undergone profound transformation over the last decade as digital technologies reshape value chains, consumer engagement, and sustainability practices (Liu and Liu, 2025). Valued at approximately USD 1.7 trillion in 2023, the sector increasingly relies on artificial intelligence (AI), blockchain, and augmented reality (AR) to enhance efficiency, transparency, and responsiveness (Pereira et al., 2022). Brands such as Zara now deploy AI‑driven predictive analytics to optimise inventory and reduce waste, while luxury houses including Louis Vuitton and Gucci employ blockchain technologies to strengthen supply chain transparency and combat counterfeiting (Lall, 2023). Digital transformation has therefore moved beyond operational efficiency to become central to ethical governance, competitiveness, and sustainability in fashion. Despite these global advances, digital transformation remains unevenly distributed. Dominant digital adoption frameworks such as the Technology–Organisation–Environment (TOE) model (Tornatzky and Fleischer, 1990) largely assume stable infrastructure, institutional capacity, and high levels of digital readiness. These assumptions limit their applicability in developing economies, particularly in South Asia, where fragmented supply chains, infrastructural constraints, and socio‑cultural factors significantly shape technology use (Akbari and Hopkins, 2022). Consequently, existing research reflects a persistent Eurocentric bias, underestimating how context‑specific realities influence digital adoption in countries such as Pakistan. Pakistan’s fashion industry presents a particularly salient context in this regard. Contributing approximately USD 3 billion annually to GDP and employing over 15 million people, the sector is deeply rooted in artisanal skills such as embroidery, weaving, and textile production (Hussain et al., 2023). Yet fashion SMEs remain weakly integrated into digital and global supply chains, with e‑commerce adoption described as limited and uneven (Ahmed, 2023). This lag increasingly threatens competitiveness, as international visibility, online marketing, and platform‑based trade become central to market access. At the same time, domestic consumers - especially younger generations - are demonstrating growing expectations for digital retail experiences (Khalid and Alam, 2020). Without meaningful digital engagement, Pakistani fashion SMEs risk marginalisation in both international and domestic markets. Barriers to digital transformation in Pakistan are structural, cultural, and organisational. Infrastructural weaknesses, including low internet penetration of approximately 45.7 percent and frequent power disruptions, undermine the reliability of digital platforms (Kemp, 2025). Culturally, artisans often perceive digital technologies as threats to traditional craftsmanship and employment, fearing the erosion of heritage skills (Choudhury, 2024). Organisationally, many fashion SMEs operate as family‑owned enterprises embedded in patriarchal and hierarchical decision‑making structures, which tend to centralise authority and restrict experimentation and innovation (Nahar, Karim and Sena, 2025; Mikail, Çora and Çora, 2025). These intersecting constraints help explain the sector’s slower pace of digital adoption relative to regional competitors. While existing studies acknowledge these barriers, the role of leadership in mediating or overcoming them remains insufficiently explored. International research suggests that transformational and adaptive leadership styles can reduce resistance and enable innovation during technological change (Bass and Riggio, 2006). However, such insights are largely derived from Western or East Asian contexts characterised by comparatively stable infrastructure and less rigid organisational hierarchies, limiting their transferability to Pakistan. Emerging scholarship indicates that hybrid leadership approaches, combining transformational vision with culturally embedded paternalistic authority, may be more effective in South Asian SME contexts (McKearney et al., 2022), yet empirical evidence remains limited. Accordingly, this study addresses the problem of how Pakistani fashion SMEs—constrained by infrastructural deficits, cultural resistance, and hierarchical organisational structures—can leverage leadership strategies to enable digitally driven yet culturally sensitive transformation. The study is theoretically justified by the need to contextualise digital adoption and leadership theories for emerging economies where assumptions embedded in models such as TOE and Diffusion of Innovation do not fully hold (Rogers, 2003). Practically, the research responds to policy imperatives articulated in Pakistan’s Digital Vision 2025, which identifies SMEs as central to economic growth but lacks context‑specific, evidence‑based guidance for implementation (MOITT, 2025). By examining leadership as a mediating mechanism between structural barriers and digital adoption, the study contributes both to scholarship and practice, offering culturally grounded pathways for preserving artisanal heritage while enhancing competitiveness, sustainability, and integration into digital fashion value chains (AL‑Abrrow et al., 2019; Duxbury, Kangas and Beukelaer, 2019).

ABSTRACT. The South African logistics industry stands to gain greater benefits from Adoption of intelligent systems driven transformation, which are technologies that have positioned global logistics industry players at accelerated advancements, while South Africa’s (SA) logistics remained at a technological crossroad. While intelligent logistics technologies continued to revolutionise logistics and supply chains globally, their adoption and integration into SA’s transport and logistics systems presents unique limitations. This study examined the adoption of intelligent systems within SA’s logistics industry, focusing the current adoption practices of intelligent technologies, the key drivers and barriers influencing adoption, and possible implementation improvement factors for the industry. the study extracts three-constructs - The impact and benefits of Intelligent logistics (F1), Implementation of AI Technologies (F2), and Intelligent Systems Adoption (F3), using Principal Component Analysis with Varimax rotation. The Cronbach's alpha is used to confirm reliability of constructs; Shapiro-Wilk normality assessment at both group and full-sample levels;the one-way ANOVA with Levene's test and Tukey HSD post-hoc tests across company sizes; zero-order Pearson and Spearman correlation matrices computed at the corrected individual level (N=109). Key obstacles slowing widespread adoption include financial barriers, a pronounced skills gap in technical expertise, and underlying infrastructure limitations. This study reveals that well automated logistics process associated with intelligent technologies would substantially enhance logistics capabilities; furthermore, increase efficiencies in the logistics environment, thereby reduce significant costs of operations

ABSTRACT. Although the impact of green human resources management is increasingly being adopted by organisations across the globe, the impact of these practices, especially green staffing on organisational performance remains unclear. Further the mediating role of the legislative framework governing these practices within the South African health sector remains scanty. The primary aim of this study was to examine the impact of Green Human Resource Management (GHRM) and green staffing on the public sector hospitals and the extent to which the legislative framework mediates this relationship. From a theoretical standpoint, the findings support the Ability-Motivation-Opportunity (AMO) Theory, which posits that employee performance and behaviour are shaped by their capabilities, motivation, and the opportunities provided by the organisation. A qualitative research design was employed, with in-depth interviews serving as the primary method of data collection. A purposive sampling technique was used to select 14 participants from a total population of 500 staff members at the selected hospital. This non-probability sampling method was chosen to enable the selection of individuals with specialised knowledge and experience relevant to the research objectives, thereby increasing the depth, credibility, and relevance of the findings. The collected data was organised and analysed thematically, in alignment with the study’s objectives. NVivo 11 software was utilised to facilitate the qualitative data analysis process, supporting the systematic identification of themes and patterns. Findings were presented both thematically and with direct verbatim quotations from participants, providing rich contextual insight. The study’s results posits that green interviews would assist the hospital with its environmental programmes that promote diversity, equity and inclusion. However, their current job descriptions are not in line with environmental standards. Respondents felt the hospital could attract and retain top management responsible for environmental values, commitment and sustainability by embedding sustainability into job description and aligning it to the needs of the staff. Further, there are no formal policy guidelines, frameworks or institutional strategies to direct the green HR agenda in the hospital and this poses an inconsistent approach to be implemented across the hospital.

ABSTRACT. The biopharmaceutical industry is embracing artificial intelligence (AI) and generative AI (GenAI) to accelerate drug discovery, clinical trials, and personalized medicine. While this digital transformation offers promises of increased efficiency and innovation, it also raises urgent environmental concerns. From massive water and energy consumption to increased carbon emissions and mineral exploitation, the hidden ecological cost of AI adoption threatens the sector’s sustainability goals. This Impact Paper explores how the widespread implementation of AI technologies in biopharma could exacerbate environmental challenges and potentially undermine firms' commitments to climate neutrality. Based on a comprehensive review and case studies, this contribution argues that “sustainable AI” must become a guiding principle for the sector. It highlights key risks and suggests actionable strategies such as AI-optimized green chemistry, eco-designed data centers, and regulatory alignment to ensure that biopharma’s AI revolution becomes an ally, rather than an obstacle, to environmental responsibility.

ABSTRACT. Healthcare organisations worldwide, continue to face growing pressures in achieving the quadruple aim of healthcare: improving population health, enhancing patient experience, supporting healthcare workforce wellbeing, and reducing the rising cost of care. These aims are fundamentally linked to organisational performance (OP) in healthcare settings. Although artificial intelligence (AI) has been widely researched and applied across several sectors, there remains limited understanding of its specific impacts on organisational performance within healthcare. Prior to the COVID 19 pandemic, AI adoption was more prominent in non healthcare sectors; however, recent years have seen increasing interest in the potential of AI to enhance healthcare organisational performance. This paper critically reviews the application of AI to organisational performance in healthcare organisations, with a specific focus on linking AI capabilities to core OP dimensions such as efficiency, quality, workforce outcomes, and financial performance.

ABSTRACT. Health and care e-procurement is recognised as a strategic lever for innovation. Like other web-based platforms, e-procurement also serves as an enabler in supply chain management, electronically enhancing an organisation's purchasing process by integrating buyers and suppliers through relevant information technology systems. This proposed review is aimed at understanding and identifying the drivers and advantages within healthcare, examining the risk factors and success factors that influence the development and implementation of the e-procurement usage in the global healthcare; and identifying innovative approaches, technologies, and mechanisms driven by digital technologies to enhance the performance of healthcare supply chains. The current study is a systematic review undertaken in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (2009). A comprehensive search was performed from 2021 to 2026 across four global databases (Web of Science, SCOPUS, Academic Source Complete, and Business Source Complete). Eligibility was restricted to full-text, peer-reviewed articles that had undergone rigorous journal review and were authored in the English language. The exclusion criteria omitted book chapters, theses, reports and existing systematic reviews. The Joanna Briggs Institute Critical Appraisal Tools were applied as a criterion to assess the methodological robustness of various studies before their incorporation into the final analytical phase. The synthesis of the extracted data was employed using a narrative synthesis approach, combining evidence derived from both quantitative and qualitative data. This research is exempt from institutional ethical review approval since it was conducted using desktop data. Dissemination of the protocol was achieved by submitting it to a conference in this field. The analysis showed that several interrelated factors affect how AI is integrated into e-procurement management, including the availability of adequate capabilities and digital infrastructure, management commitment to successful e-procurement adoption, ethical and governance frameworks, and resource investment in IT and ICT network infrastructure. These factors interact in a mutually reinforcing manner to shape the processes by which AI is integrated into global e-procurement systems, as well as the reconfiguration of managerial roles and the associated decision‑making processes. It yields notable implications for policymakers and professionals aiming to advance transparency with stakeholders, cultivate ethical governance structures, and strengthen accountability and ethical practice across the health e-procurement system. The analysis provides a conceptual foundation for future research seeking to develop theory at the convergence of AI, global e-procurement management, and strategic supply chain management.

ABSTRACT. This paper explores the accident insurance systems, namely the Road Accident Fund (RAF) in South Africa, in which the RAF is collected through several sources, as outlined in the Fuel levy income and Government grants paid by the National Treasury. However, the paper explores the common cost phenomenon and the impact that the Road Accident Fund Amendment Bill, 2023, will have on South Africans, especially in light of the Occupational Health and Safety Act 85 of 1993 and the Compensation for Occupational Injuries and Diseases Act 130 of 1997 as amended. The Road Accident Fund Amendment Bill, 2023, recognised the common law claim obtained by the innocent injured party against the balance of his/her loss against the guilty party. The injuries received by the innocent injured party must be due to the negligence of the driver or owner of the vehicle. The paper examines discrimination against the working classes who use public transport to get to work or are conveyed in the vehicle during their employment. Another effect of the Road Accident Fund Amendment Bill, 2023, will be an increase in premiums of medical aids since the medical aids will no longer be able to reimburse accident-related medical expenses. The proposed centralised system will remove the right of drivers, passengers, and pedestrians to claim compensation for injuries during accidents, and the payment of funding will be significantly reduced for claimants. The study suggests that the Road Accident Fund Amendment Bill, 2023, conflicts with the primary objective of the Road Accident Fund Act 56 of 1996 and social security regarding the Constitution of the Republic of South Africa, 1996. The authors conducted legal research, where an analysis of primary sources related to South Africa's social security legislation, workplace safety legislation, regulations, and case laws was performed and interpreted. This includes the Constitution of the Republic of South Africa 108 of 1996, Occupational Health and Safety Act 85 of 1993, Compensation for Occupational Injuries and Diseases Act 130 of 1997 as amended, and the Road Accident Fund Amendment Bill, 2023. The authors also used secondary sources, including research reports, publications, journal articles, and books, to conclude their findings.

ABSTRACT. This study investigates the role of intelligence-led policing (ILP) in disrupting gang networks in South Africa, with particular reference to gang-affected areas of the Western Cape. Gang-related violence remains a major contributor to murder rates, firearm proliferation, and broader social instability, necessitating policing approaches that extend beyond reactive enforcement. Adopting a mixed-methods research design, the study integrates quantitative analysis of crime statistics, social network analysis (SNA) of gang affiliations, and qualitative focus group interviews. A total of 20 participants were selected through a purposive sampling technique. The focus groups included eight South African Police Service (SAPS), Crime Intelligence personnel, five public prosecutors, and seven community stakeholders. The community stakeholders comprised representatives from the Community Police Forum, community leadership, neighbourhood safety coordination, non-governmental organisations involved in crime prevention and victim support, civil society, and the local business community. The quantitative component assesses changes in crime trends, network structures, and spatial patterns following intelligence-driven policing operations. The qualitative component explores operational practices, institutional challenges, and community perceptions regarding the implementation of ILP. The findings indicate that intelligence-led policing can produce short-term disruption of gang networks by targeting highly connected actors and key nodes within criminal structures, leading to temporary fragmentation and reductions in violent incidents. However, the resilience and adaptability of gang networks often constrain the long-term sustainability of these disruptions. The study further identifies several institutional challenges, including limited inter-agency coordination, resource constraints, and difficulties in converting intelligence into successful prosecutions. Overall, the findings suggest that ILP is most effective when implemented as part of a broader multi-agency strategy that combines intelligence-driven enforcement with effective prosecution, community engagement, and preventative social interventions. This study contributes to criminological scholarship by highlighting both the potential and limitations of intelligence-led policing within the South African policing context.

ABSTRACT. The evolution of criminal law and criminal procedure in South Africa reflects an ongoing tension between constitutional guarantees and the practical realities of crime control in a high-crime environment. Grounded in the transformative vision of the Constitution of the Republic of South Africa, 1996, the criminal justice system is mandated to balance the rights of accused persons with the need to ensure public safety and effective law enforcement. However, persistent challenges including case backlogs, investigative inefficiencies, evidentiary weaknesses, and procedural delays continue to undermine the administration of justice. This paper critically examines the intersection between substantive criminal law and procedural frameworks, with particular focus on arrest, bail, and trial processes under the Criminal Procedure Act 51 of 1977. It interrogates how procedural safeguards, such as the right to a fair trial and the presumption of innocence, are applied in practice, especially in cases involving violent crime, gender-based violence, and organized criminal activity. The study further evaluates the impact of judicial interpretation and landmark case law in shaping procedural justice and accountability within law enforcement institutions. Drawing on doctrinal analysis and recent empirical trends, the paper argues that while South Africa possesses a robust constitutional and legislative framework, systemic inefficiencies and institutional limitations hinder its full realization. The paper concludes by proposing targeted reforms, including enhanced investigative capacity, procedural streamlining, and improved inter-agency coordination, to strengthen the effectiveness and legitimacy of the criminal justice system.

ABSTRACT. Introduction: This article analyses the judgment of the Gauteng Division of the High Court in MM v NIM, which concerned the validity of an alleged customary marriage and the legal status of an antenuptial contract concluded several years after the parties had observed extensive customary rites. The matter raised complex legal questions at the intersection of customary law, matrimonial property regimes, contractual autonomy, and constitutional values relating to equality and culture. Central to the dispute was whether the parties had entered into a valid customary marriage in terms of the Recognition of Customary Marriages Act 120 of 1998, and whether an antenuptial contract concluded subsequent to the alleged marriage could validly regulate their matrimonial property system.

ABSTRACT. The decision to hire a suitable candidate is sacrosanct for any organisation. Organisations that use proper predictors are empowered to select a competent applicant who will give them a competitive advantage. A review of the literature revealed that hiring decisions are an emerging field of study, and in the Global South, such research is sparse where researcher used machine learning algorithms. Hence, this study was conducted to contribute to the body of knowledge regarding hiring decisions. To provide a theoretical foundation for the study, matching and human capital theories were deemed suitable. Since the data available to achieve the study objectives is sparse in the South African context, the researchers utilised secondary data from Kaggle. The rationale for choosing data from Kaggle is that it is highly reliable and valid. The research approach was quantitative, the research philosophy was positivism, and renowned classification algorithms (i.e., logistic regression, Decision Tree & XG-Boost) were compared. The comparison revealed that the XG-Boost outperformed the other algorithms. The key findings were that recruitment strategy, personality score, and educational levels were the highest predictors of hiring decisions. The managerial implication is that the findings can be valuable for understanding which factors are most predictive in the hiring data and can potentially guide decision-making.

ABSTRACT. Corrective maintenance backlog remains a persistent operational challenge in maintenance-intensive industries, often resulting from ineffective coordination between maintenance processes, quality management practices, and supplier management. This study examined the structural relationships between quality tools, ISO 9001:2015 quality management (QM) principles, maintenance documentation gaps, and supplier management in influencing corrective maintenance backlog. A quantitative explanatory research design was adopted, and data were collected through a structured questionnaire administered to employees at a power generation plant. A total of 204 responses were analysed using covariance-based structural equation modelling. The results indicate that quality tools have a significant positive effect on the implementation of QM principles and on supplier management practices. QM principles were also found to significantly influence maintenance documentation practices. However, quality tools and QM principles did not demonstrate any significant effect on corrective maintenance backlog. Instead, supplier involvement showed a significant positive relationship with backlog levels, highlighting the influence of supplier coordination and spare parts logistics on maintenance performance. The findings suggest that corrective maintenance backlog is driven by indirect organisational and operational factors rather than by quality tools or standards alone. The study contributes to maintenance management literature by providing a systems-level perspective on how internal quality practices and external supplier dependencies interact to influence maintenance outcomes.

ABSTRACT. Earlier research has investigated the influence of using Enterprise social media (ESM) platforms on Employee Engagement (EE) in organisations; however, relatively limited awareness has been created on its role within the banking industry. The study addresses this gap by positioning ESM as a transformative organisational tool that extends beyond communication to support Information Technology Service Management (ITSM) functions such as digital workflows, service requests, knowledge sharing, and cross functional collaboration. By viewing ESM through an ITSM lens, the proposed research will examine how employees’ everyday interactions with these platforms shape service delivery across business functions, including Human Resource (HR). Guided by Social Influence Theory (SIT), the study aims to develop an integrated framework linking ESM, EE, and ITSM based service processes. Focusing on the under explored banking sector, the study adopts a social constructivist, inductive approach to understand how social influence processes unfold within this specific organisational setting. An embedded case study strategy, supported by semi structured interviews will enable in depth exploration of these dynamics. The study aims to contribute to strategic conversations and discussions on ways in which organisations can impact the digital communication systems to foster meaningful Employee Engagement (EE) and create strong digitally enabled workplaces in a changing global economy.

ABSTRACT. Most research presents different frameworks of total quality management (TQM) elements. However, there is a scarcity of literature which depicts a universal framework of critical TQM elements influencing manufacturing productivity. Thus, this study extensively assessed the literature on TQM, in particular to identify “acute” elements which enabled development of a model of productivity enhancement in manufacturing. Out of the 77 journals reviewed, 51 were used to appraise the extent of the relationship between TQM elements and productivity. The descriptive analyses proved that successful critical elements to enhance productivity are; top management support, customer focus, human resource focus, process management, information evaluation and analysis, and supplier quality management. Microsoft office was used; Excel 2013; windows 7 to create a Pareto analysis in order to provide the findings of TQM practices. The model findings obtained by using a correlation analysis demonstrated a positive relationship between TQM elements and productivity. Benefits include increased customer satisfaction, increased manufacturing profitability and competency in the global market. The fact that the study was based on TQM, while other quality improvement practices such as Six Sigma, Lean Manufacturing, and Lean Six Sigma were not covered creates study limitations, but also offers an opportunity for future research. After the literature review, and based on the study outcomes, a developed model can be used as an academic source for both researchers and management.

ABSTRACT. Vehicle theft remains a persistent challenge in South Africa, particularly in high-risk urban areas, despite advances in automotive security technologies. This study explores how lean principles and core philosophies focused on maximising value and eliminating waste can be applied beyond their traditional manufacturing context to enhance vehicle security systems. A quantitative, survey-based design was employed, targeting 100 participants from 26 automotive dealerships in Johannesburg’s East Rand, including technicians, engineers, and vehicle inspectors. Data was collected through a 28-item validated survey and analysed using descriptive statistics and Pearson’s correlation in SPSS Version 29. Findings reveal a strong positive relationship between awareness and application of lean practices and the perceived effectiveness of vehicle security systems. While existing security technologies provide moderate protection, their fragmented and reactive implementation limits their impact. Participants indicated that early integration of technologies such as RFID, biometric access, and AI-powered detection within lean-oriented workflows could improve reliability, responsiveness, and operational efficiency. These insights can guide manufacturers and policymakers in developing integrated, proactive, and cost-effective strategies to reduce vehicle theft in South Africa.

ABSTRACT. The intensifying global emphasis on sustainability and environmental responsibility has fundamentally reshaped consumer behaviour, with growing numbers of consumers adopting eco-conscious lifestyles and favouring brands and products that minimise environmental and social harm (Joo et al., 2022; Correia et al., 2023). This shift is particularly evident within the retail sector, where supermarkets play a pivotal role in influencing consumption patterns due to their scale, reach, and control over product availability and communication. Across both developed and developing economies, demand for green products has increased steadily, reflecting heightened awareness of climate change, biodiversity loss, and resource depletion (Vadakkepatt et al., 2021). Consequently, the concept of the “green consumer” has gained prominence, referring to individuals who incorporate environmental protection, sustainable resource use, and social responsibility into their purchasing decisions (Ansu-Mensah et al., 2021; Li et al., 2021).

ABSTRACT. This study explores how customer service influences consumer buying patterns among SMEs in East London, South Africa. SMEs are crucial to the local economy, yet many face challenges in retaining customers due to inconsistent service quality and limited resources. The research examines how service factors such as staff professionalism, communication, complaint handling, and responsiveness impact customer satisfaction, loyalty, and purchasing choices. Using the SERVQUAL model, Expectancy-Disconfirmation Theory, and Relationship Marketing Theory, a quantitative, cross-sectional survey was conducted. Data from 100 consumers who recently interacted with East London’s SMEs indicate that customer service is the top factor influencing purchasing decisions, surpassing price, product quality, and convenience. Friendly, helpful staff, strong after-sales support, and effective communication are key to fostering loyalty and repeat business. Although perceptions of service quality are generally positive, 25% of respondents expressed dissatisfaction due to delays, poor communication, and a lack of product knowledge. These issues underscore the need for targeted initiatives, including staff training, digital engagement, and loyalty programs. The study highlights the growing role of digital platforms in improving service delivery, especially for younger, tech-savvy consumers. Overall, the study recommends that SMEs should focus on regular training programs centered on customer engagement, product knowledge, and complaint handling. This will enhance service consistency and professionalism, leading to higher customer satisfaction and loyalty.

ABSTRACT. In digital fashion industry, user-generated content (UGC) is becoming more and more important in influencing consumer trust and decision-making. However, a few studies have looked at how UGC affects trust in emerging markets. The purpose of this study is to investigate how consumer trust in the South African fashion sector is shaped by user-generated content. Based on a constructivist worldview, the study uses an exploratory, qualitative research design. The study investigates how consumers evaluate the credibility of fashion-related user-generated content (UGC), guided by the Source Credibility Model and supported by the ideas of homophily, parasocial interaction, and similarity attraction. Eighteen South African customers from all nine provinces participated in semi-structured interviews to gather data, which was then subjected to thematic analysis. The findings indicate that UGC strongly influences consumer trust through authenticity, transparency, expertise, relatability, and community validation. Participants expressed greater trust in content produced by everyday consumers and micro-influencers than in highly curated brand or celebrity content. There were clear platform-specific trust dynamics: YouTube was seen as a source of thorough and reliable reviews, Instagram as aesthetically inspiring, Facebook as community-focused, and TikTok as quick and approachable. Regular content production and engaged audience participation further strengthened trust. By using the Source Credibility Model to examine the South African fashion sector, this study offers qualitative insights from an understudied rising industry. By emphasising platform-specific and culturally grounded trust dynamics in user-generated content, it expands on previous research.

ABSTRACT. The outbreak of the COVID-19 pandemic has brought unprecedented challenges worldwide, impacting various aspects of society, including students living in university residences. This abstract focuses on managing student residences during the COVID-19 pandemic: A public administration perspective at a selected South African tertiary institution. The qualitative study uses interviews and surveys to gather data on how students in their university residence have been affected by the pandemic. Factors such as sudden transition to online learning, social isolation, mental health concerns, and financial pressures are examined to understand the multifaceted impacts of the pandemic on students’ daily lives. Through thematic analysis, common themes emerge that highlight the struggles, resilience, and coping mechanisms of students facing the challenges of the pandemic. The findings shed light on the unique experiences and perspectives of students living in university residences, providing insight for institutions to tailor support services and interventions effectively. Recommendations based on the findings seek to guide policy makers, universities, and support services in the implementation of strategies to mitigate the adverse effects of the pandemic on student general well-being and academic success. The study found that in fact, the Student Residences had been significantly transformed by the Covid19 pandemic. The operations of the student residences had been forced to change in order to comply with Covid-19 regulations, so that student learning was shifted from face-to-face learning to online learning. This meant more time spent indoors, stricter measures now in place, and student residence policies having been broadened to ensure that they also monitor compliance. The researchers can conclude that the Covid19 pandemic has had a huge effect on student residences at the selected university and that students should play their roles effectively to ensure that everyone remains safe.

ABSTRACT. Despite progress in promoting gender equality, patriarchy remains deeply embedded within many higher learning institutions. Universities are often perceived as progressive spaces that promote knowledge, equality, and critical thinking; however, institutional cultures and structural arrangements frequently reproduce gendered power relations that disadvantage women and other marginalized groups. This paper examines the persistence of patriarchal norms and practices within higher education institutions and how these dynamics influence access to leadership, participation in decision-making, and academic advancement. Using qualitative content analysis as a method of data collection and analysis, the study reviews institutional policies, scholarly literature, and publicly available reports related to gender representation and gender equality in higher education. The analysis focuses on identifying recurring themes relating to gendered power structures, leadership representation, institutional culture, and policy responses aimed at addressing gender inequality. The findings reveal that patriarchal structures are sustained through subtle institutional practices, including unequal representation in leadership positions, gendered expectations within academic roles, and the marginalization of women's voices in decision-making processes. While many institutions have adopted gender equality policies, the implementation of these policies often remains limited due to entrenched cultural norms and structural barriers. The paper argues that confronting patriarchy in higher learning institutions requires a deliberate transformation of institutional cultures, leadership structures, and policy implementation frameworks. It recommends the strengthening of gender-transformative policies, the promotion of inclusive leadership, and the integration of gender equality principles within institutional governance. Addressing these structural inequalities is essential for creating academic environments that genuinely promote equity, diversity, and social justice.

ABSTRACT. The e-commerce logistic industry’s business environment is characterised by increasing market demands and high competition, and pressure from online shoppers to have goods purchased delivered in their own terms. Technology increasingly plays a major role in modern firms’ value chain. The e-tail logistics industry is highly digitised and as such faces challenges emanating mainly from the online shopper, a typical premise is that home delivery is no longer a sufficient proposition because online shoppers want flexibility in terms of when and where the order can be delivered and want to choose a delivery option that fits their daily schedules in the best possible way. Business agility was conceptualized through two dimensions: market orientation agility and operational agility. Scale reliability was confirmed with Cronbach's alpha values ranging from 0.811 to 0.923. Pearson correlation analysis revealed a high positive correlation between IT capability and market orientation agility (r = 0.761, p < 0.05) and a very strong positive correlation between IT capability and operational agility (r = 0.908, p < 0.05) IT is generally considered an enabler of business agility. On the other hand, IT can hinder and sometimes weaken business agility. This research explores the relationship between IT and agility within the e-tail logistics industry in South Africa. The results reveal that adapting to market related changes often requires changes in operational processes, thus affecting operational agility. Connecting to e-tailers information systems requires an IT Infrastructure with electronic data interchange capabilities. The research results suggests that e-logistics firms required some improvements with regards to handling such requirements.

ABSTRACT. Most South African public schools cannot survive solely on government funding but need assistance from private donations to carry out their operations. Most donations to schools come from mines, local businesses, and individuals, who trust that their donations are used predominantly for the benefit of the schools and for community development at large. However, schools do not have a donations management tool that ensures accurate recording, proper use, reporting, and disclosure of all donations received. Therefore, the main aim of this study is to develop such a tool. Employing a qualitative research design, data was collected through interviews from six (6) school accounting teachers, located in Gauteng (2), Mpumalanga (2), Limpopo (2) and two (2) government officials, from Limpopo and Mpumalanga respectively. It was established in this study that the Department of Basic Education does not provide schools with a donation management policy that requires the disclosure of these donations and that schools do not have donations management policies. Besides this, it is not clear if donations are completely used for the schools’ benefits or not. Therefore, this study will assist the Department of Basic Education and schools in developing and implementing a strict donations management system that will reinforce donors' confidence in the use and application of donations received by schools.

ABSTRACT. This work reviews current literature and studies to examine the overarching impact of technology on four societal components of our confidence: intimacy, veracity, systemic integrity, and esteem. Confidence is defined as full trust; a belief in the powers, trustworthiness, or reliability of a person or thing. While multiple studies have explored the influence of technology on our daily lives, this treatise is unique in assessing the impact of technology on our confidence in relationships, information, systems, and ourselves. Technology has been classically defined as any intentional extension of a natural process. It aids the accomplishment of human processes. This definition is overly broad. For example, a pencil, in facilitating communication, could be considered technology. In this treatise, we limit our definition to something more commonly referred to as high technology, or high tech. High tech is considered scientific technology involving the production or use of advanced or sophisticated devices, especially in the fields of electronics and computers. It encompasses communication, transportation, and medical technologies, including the burgeoning field of artificial intelligence (AI). In intimacy, a traditional component of privacy, the individual is part of a small unit that is allowed to exercise corporate seclusion to achieve a close, relaxed, and frank relationship between two or more individuals. Intimacy relies heavily on trust. It is the “insider” protection afforded to members of special family or friendship units. Veracity refers to the quality of being true, honest, or accurate. Veracity is critically important in a technology-enriched society that increasingly relies upon information found online from sources that are sometimes difficult to trace or verify. The National Institute of Standards and Technology Computer Security Resource Center (NIST) defines system integrity as the quality a system has when it performs its intended function in an unimpaired manner, free from unauthorized manipulation of the system, whether intentional or accidental. Although focused on computer systems, this study expands the definition to encompass systemic integrity. Systemic integrity refers not only to computer networks, but to the systems and processes that regulate the operation of society, including the police, the courts, and the government. Finally, esteem is our confidence in individuals, whether others or ourselves. To esteem another is to regard highly or favorably, with respect or admiration. Similarly, self-esteem is the degree to which a person perceives their own the qualities and characteristics to be positive. The American Psychological Association (APA) finds self-esteem to be an important ingredient of mental health. Confidence in our relationships, information, systems, and ourselves is vital to the effective functioning of society. Without confidence, our lives are filled with uncertainty and mistrust almost to a point of paralysis. One might expect technology to enhance our confidence, particularly in the collection, analysis, and dissemination of information toward aiding the natural processes of life. However, there is evidence that technology may work to erode our confidence. Particularly with the saturation of AI into the fabric of society, we find ourselves more frequently pondering exactly what, if anything, is real and accurate. What, and who, can we really trust? And can society thrive with decreased confidence in relationships, information, systems, and ourselves?

ABSTRACT. Cybercrime continues to evolve in complexity and scale while traditional law enforcement methods often prove insufficient to combat sophisticated digital threats. Artificial Intelligence (AI) and Machine Learning (ML) offer promising avenues for automating threat identification, analysing vast datasets, and predicting criminal behaviours, thereby potentially augmenting the South African Police Services' (SAPS) capabilities. The rationale for this study lies in the need to understand whether these technologies can be effectively and responsibly leveraged within SAPS to strengthen digital investigative capacity. The primary objective is to systematically evaluate the efficacy of AI and ML technologies in enhancing cybercrime detection and investigation within the SAPS, while also identifying the challenges, limitations, and ethical implications associated with their application. Employing a rigorous systematic literature review, this research will meticulously identify, select, and critically appraise existing academic and grey literature about the application of AI and ML in cybercrime forensics, intelligence, and operational response globally. The methodological rigour of this approach ensures comprehensive, reliable, and transparent synthesis through structured search strategies, predefined inclusion criteria, quality appraisal, and systematic data extraction. The review will synthesize findings on the effectiveness, challenges, ethical considerations, and best practices associated with these technologies. Key outcomes will include an assessment of the current state of AI/ML integration in police cybercrime units, identification of successful implementation models, and an exploration of the inherent limitations and risks. The major contributions and implications of this study will include evidence‑based insights to inform SAPS strategic decision‑making, a clearer understanding of the feasibility and impact of AI/ML tools in local policing contexts, improved guidance for resource allocation, and recommendations to enhance cybercrime investigative outcomes in the digital realm. This study, therefore, seeks to provide evidence-based insights and recommendations for SAPS, guiding strategic decision-making in the adoption and deployment of AI/ML tools to more effectively combat cybercrime, improve resource allocation, and enhance justice outcomes in the digital realm.

ABSTRACT. Understanding how visual attention influences human preference formation is a fundamental problem in consumer behavior and cognitive science. In this work, we investigate how eye movement patterns can be used to predict preference decisions when subjects compare two alternatives. To address this problem, we analyze an eye-tracking dataset, where subjects view pairs of face images and their gaze behavior is recorded throughout the decision process. We model this problem using multiple machine learning classifiers and apply the Multi-layer Combinatorial Fusion (MCF) framework to iteratively combine diverse models. The MCF framework expands models to a large pool of model fusions and then reduces them based on cognitive diversity, repeating this process across layers until diversity diminishes. Experimental results show that MCF significantly improves performance over individual models. The best single model achieves a Pre@k of 0.90, which is improved to 0.9143 after the first layer of MCF, and further increased to 0.9286 in the second layer. This progression demonstrates that the second layer not only surpasses the performance of the first layer but also outperforms the best individual model, highlighting the effectiveness of leveraging diversity through multi-layer fusion.

ABSTRACT. Since 2022, the use of generative artificial intelligence (AI) has rapidly intensified in educational and professional contexts. Generative AI is becoming increasingly human-like in its analytical and generative competency. While these developments create opportunities for enhanced sense-making, uncritical reliance on generative AI risks cultivating dependence. Dependence is an outcome misaligned with entrepreneurship education, which traditionally emphasises autonomy, judgment, and responsibility. In response, this paper argues for the need to articulate new competencies that enable meaningful human-AI engagement. This paper proposes Cyber-Social Intelligence as an emerging competency in entrepreneurship education within sustained human–AI interaction. Drawing on cases documenting AI initiatives across South African higher education institutions, the paper develops a practice-informed conceptual framework that illustrates how meaningful human–AI engagement unfolds. Entrepreneurship education is presented as a particularly illuminating site for examining Cyber-Social Intelligence, given its emphasis on uncertainty, decision-making, and accountable action. The paper contributes a human-centred conceptual framework aligned with global business and technology scholarship and offers implications for pedagogy in Entrepreneurship Education.

ABSTRACT. The article evaluates the role of environmental laws in the adaptation to climate change over the past 27 years (since the promulgation of the National Environmental Management Act 107 of 1998) in South Africa. The author will track the emergence of international adaptation Conventions and Treaties within the climate and the non-climate regime, alongside an increasing dire extreme event and a strident consensus in South Africa. The writer will examine the growth in national and local laws for adaptation and reflect on the role and framework of legislation, sectoral laws, policies, and mechanisms in South Africa. In evaluating the progress over the 27 years, the author will outline how the role of environmental laws can be enhanced and accelerated in the future, based on sustainability (as determined by the Brundtland Report, 1987). The author will identify significant trends to adopt legislation and the consideration of the potential for these promulgations to drive the future adaptation in climate change: the sheer growth in the priority and volume of environmental laws such as the Climate Change Act 22 of 2024 which are directed towards adaptation; the intersection of adaptation within other policy domains (for example the Income Tax Act 58 of 1962), with the consideration of disaster risk reduction within the scope of the Disaster Management Act 57 of 2002 as amended; and the critical role of different strategic litigation and case laws. Due to the slow progress in implementing transformational adaptation law reform, the author identifies the following principles for adaptation in environmental laws. The laws must be responsive to change, address the equity dimensions of climate change as well as the Constitution (Constitution of the Republic of South Africa, 108 of 1996), the implementation of innovative and quick solutions, the maximisation of co-benefits for the three government spheres, and the establishment of different processes for the effective management of trade-offs.

ABSTRACT. This paper examines how disability inclusion is understood, operationalised, and sustained within Kuwait’s corporate sector. Despite legislative commitments such as Law No. 8 of 2010, findings reveal a persistent policy–practice gap: organisations demonstrate formal compliance with accessibility requirements yet rely heavily on informal, leader‑driven adjustments rather than institutionalised human resource systems. Drawing on semi‑structured interviews, survey responses, and organisational document analysis, the research identifies leadership behaviour, organisational culture, and culturally embedded perceptions of disability as decisive factors shaping inclusion outcomes. While international models such as the UK’s Disability Confident Scheme and regional frameworks from Dubai and Saudi Arabia offer instructive benchmarks, their effectiveness depends on careful cultural adaptation. The paper argues that meaningful disability inclusion in Kuwait requires moving beyond compliance towards employee‑centred, culturally resonant strategies supported by leadership development, structured training, formal feedback mechanisms, and sustained investment in accessible infrastructure and assistive technologies.

ABSTRACT. Organised crime in South Africa has increasingly infiltrated the justice cluster, undermining institutional integrity and the rule of law. Rakubu KA’s 2023 chapter, “Government Measures to Combat Organised Crime in South Africa,” published in The Palgrave Handbook of Global Social Problems, critically examines the state’s fragmented and politically compromised response to organised crime. This article builds on Rakubu’s analysis to explore how criminal networks exploit regulatory gaps, politicized appointments, and weak oversight to embed themselves within law enforcement and prosecutorial services. These dynamics are now under scrutiny in the Madlanga Commission of Inquiry (2025), which is investigating allegations of corruption, collusion, and obstruction of justice within the justice cluster. To compare Rakubu’s theoretical insights with the Commission’s emerging findings, the study employs a qualitative content analysis methodology. This involves thematic coding of Rakubu’s chapter alongside publicly available testimonies, reports, and media coverage from the Commission. The analysis identifies convergences in institutional vulnerabilities, enforcement failures, and patterns of state–corporate collusion. The study argues that organised crime’s influence within the justice system constitutes a form of institutional victimisation—where systemic corruption disables justice delivery and erodes public trust. By linking criminological theory to contemporary evidence, the article contributes to debates on state–corporate crime and proposes reforms to enhance accountability, coordination, and political insulation within South Africa’s justice institutions.

ABSTRACT. While counterfeiting destroys legitimate brands and businesses, counterfeiters continue to benefit from a free ride by unduly profiting from the destruction of legitimate businesses and goods they own. The free rider problem indicates a market failure in context. However, research on the counterfeiters’ modus operandi is scanty. The counterfeiters’ operation is characterised by secrecy, and the goods production and warehouses are hidden. Counterfeiters are not targeted by law enforcement in various jurisdictions, as they operate covertly in various countries. The main objectives of this qualitative study were to explore the complexities of counterfeiting in the Southern African countries. The supply chain channels and peddlers of the trade were unmasked. The law enforcement strategies used by various law enforcement agencies to control the illegal trade from spreading further were detailed. Literature study was conducted on the counterfeiting trade, and also an in-depth interview was conducted with ten South African Police Service’s Specialised commercial crime investigators. The information was analysed using the spiral qualitative method. The analysis revealed that counterfeiting is an increasing problem in the global south. Many people continue buying counterfeited goods knowingly and unknowingly. Some countries have no proper strategy to deal with the counterfeiting problem. Law enforcement mechanisms used by various countries struggle to target counterfeiters as the root cause of the menace. The findings suggest that law enforcement targets peddlers other than counterfeiters, causing the problem to continue unabated. Furthermore, counterfeiters should be policed through multi-pronged teams of investigators with complementary skills.

ABSTRACT. The quick rise of cashierless and queueless stores is a major shift in how people use technology in stores. Checkers is testing new formats in South Africa, like Xpress Trolleys and Checkers Rush, that let customers scan items as they shop, keep track of their spending, and pay without having to wait in line at the register. Despite the potential benefits of these technologies, little is known about how South African consumers perceive and intend to adopt them. This research study integrates the Technology Readiness Index (TRI) and the Technology Acceptance Model (TAM) to analyse the psychological and cognitive determinants affecting consumers' adoption of cashierless and queueless stores. A quantitative, cross-sectional survey methodology was employed. A non-probability snowball sampling method was employed to collect data from 378 respondents aged 18 to 65 from all nine South African provinces. The constructs assessed comprised the TRI dimensions of optimism, innovativeness, and discomfort, in addition to the TAM constructs: perceived ease of use, perceived usefulness, and intention to use. The evaluation of the measurement model demonstrated acceptable reliability and convergent validity, as evidenced by Cronbach’s alpha and composite reliability surpassing the recommended thresholds, and the average variance extracted (AVE) exceeding 0.50 for all constructs. The findings from structural equation modelling indicated that perceived usefulness and perceived ease of use were the most significant predictors of the intention to adopt cashierless retail technologies. Perceived ease of use also had a significant effect on perceived usefulness, which supports the structural assumptions of TAM. Optimism had a small but significant positive effect on intention among the TRI constructs, while discomfort had a small but significant negative effect. Innovativeness had an indirect effect on intention by making it seem easier to use. The model accounted for 67.7% of the variance in intention, 31.3% in perceived ease of use, and 52.8% in perceived usefulness. These findings highlight the importance of perceived ease of use and usefulness in driving adoption intentions and show how technology readiness factors shape consumer perceptions of cashierless and queueless stores. The study contributes theoretical insights into the integration of TRI and TAM while offering practical guidance for retailers introducing smart retail technologies in emerging markets.

ABSTRACT. Generative artificial intelligence (AI) services, such as ChatGPT, have rapidly evolved from functional tools into consumer-facing brands. However, much adoption research still relies on average-effect models that assume a homogeneous market, offering limited decision-ready guidance for brand strategy. This study addresses this gap by applying a machine learning-based segmentation approach to develop a brand-centric typology of the intention to use ChatGPT. Using survey data (N = 176) and a reproducible KNIME workflow, we implement k-means clustering on eight focal constructs: perceived control, perceived risk, trust, brand awareness, brand familiarity, brand attitude, perceived brand benefit, and electronic word of mouth (eWOM). Three segments/clusters emerge, demonstrating clear market heterogeneity and strong behavioural validation and differing sharply in high- versus low-intention distributions: a near-universal high-intention group (confident brand-positive advocates), a predominantly low-intention group (sceptical low-control resistors), and a mixed “moveable middle” (cautious familiar users). Segment profiles align with a trust-risk mechanism and customer-based brand equity logic, where higher intention is associated with higher trust, lower perceived risk, stronger brand knowledge and evaluations, and comparatively higher eWOM. Managerially, the results indicate that brand-led adoption strategies should be differentiated by segment, sustaining trust and advocacy among adopters, reducing perceived risk and strengthening trust among cautious users, and building perceived control alongside trust and risk mitigation among resistors. The study demonstrates the value of machine learning segmentation for translating brand-centric adoption theory into actionable guidance for AI service adoption.

ABSTRACT. The rapid advancement of large language models (LLMs) based on generative artificial intelligence has significantly expanded the methodological toolkit available to researchers conducting text-based analysis (Thapa, Shiwakoti, Shah, Adhikari, Veeramani, Nasim, & Naseem, 2025; Zhang, Deng, Liu, Pan, & Bing, 2024). Among these tools, ChatGPT has emerged as one of the most widely adopted generative AI systems due to its accessibility, versatility and capacity for context-aware language interpretation. Traditional sentiment analysis methods have been extensively studied across two broad approaches: lexicon-based tools, such as TextBlob and VADER and transformer-based models, such as BERT. Lexicon-based tools assign polarity scores based on predefined word lists (Qi & Shabrina, 2023; Mao, Liu, & Zhang, 2024), and transformer-based models leverage deep learning to capture contextual language patterns in text (Kokab, Asghar, & Naz, 2022; Talaat, 2023). While both approaches have demonstrated strong performance in structured or formal language contexts, they operate as separate, single-function tools. Lexicon-based methods offer computational efficiency but lack contextual sensitivity, while transformer models offer greater linguistic depth but typically produce numerical outputs without interpretive explanations (Mao et al., 2024; Zhang et al., 2024). The emergence of large language models such as ChatGPT introduces a qualitatively different analytical possibility. While extensive research has examined traditional sentiment analysis methods, limited empirical work has examined ChatGPT’s capabilities as a hybrid sentiment analysis tool. In this study, the term hybrid sentiment analysis refers to an approach that combines lexicon-based computational scoring with the contextual interpretive reasoning of a large language model. This approach enables both quantitative output and qualitative explanations within a single analytical process (Mao et al., 2024; Wang, Xie, Feng, Ding, Yang, & Xia, 2024). Despite the growing scholarly interest in LLM capabilities, limited empirical work has directly evaluated ChatGPT's effectiveness as a hybrid sentiment analysis tool, particularly in social media contexts where informal language, slang, emojis and mixed emotional tones present persistent challenges for conventional methods (Bojić, Zagovora, Zelenkauskaite, Vuković, Čabarkapa, Veseljević Jerković, & Jovančević, 2025; Jim, Talukder, Malakar, Kabir, Nur, & Mridha, 2024). This gap is significant, as existing benchmark studies have tended to evaluate ChatGPT against formal or structured text datasets, leaving its performance on the kind of expressive, colloquial and emoji-rich language characteristic of Instagram influencer content largely unexplored (Zhang et al., 2024; Wang et al., 2024). The objective of this paper is to assess ChatGPT 5.1’s ability in conducting sentiment analysis on Instagram captions produced by mega influencers and its capacity to generate both quantitative and qualitative sentiment analysis outputs to determine whether its interpretive reasoning enhances traditional sentiment typologies. Instagram influencers were selected for their role as key opinion leaders, whose language choices shape audience perceptions, brand engagement, and online persuasion (Casaló, Flavián, & Ibáñez-Sánchez, 2020; Conde & Casais, 2023; Rialti, Zollo, Kim, & Yoon, 2024). A total of 66 sponsored or brand-related captions were purposively sampled across fashion, beauty, storytelling and comedy influencers (van der Harst & Angelopoulos, 2024; Conde & Casais, 2023). Identifying information was removed and the full textual content, including emojis, hashtags, brand mentions and punctuation, was compiled into an Excel dataset. These elements have been identified as meaningful sentiment-bearing features in social media text (Khan, Majumdar, & Mondal, 2025; Jim et al., 2024). An exploratory qualitative research design guided the analysis. A detailed prompt specifying sentiment constructs (polarity, intensity and emotional tone) was developed to ensure consistency and reproducibility when engaging ChatGPT. When generating output, ChatGPT autonomously drew on TextBlob, a widely used open-source Python lexicon-based sentiment analysis tool that assigns numerical polarity scores (ranging from −1 to +1) and subjectivity ratings to text (Qi & Shabrina, 2023; Mao et al., 2024). Unlike specialised implementations where the researcher deploys TextBlob directly, ChatGPT accessed and applied this lexicon as part of its own analytical reasoning, effectively embedding a rule-based scoring layer within its generative output. ChatGPT produced a dual-layered output: first, a quantitative analysis, including frequency counts, percentages, ranges and polarity score interpretation. Secondly, qualitative interpretation, which contextualised sentiment cues, explained ambiguous or slang-driven expressions (e.g., the playful use of “boring” or positive slang such as “obsessed”), and identified misclassification risks (Bojić et al., 2025; Jim et al., 2024). Results show that ChatGPT synthesises lexical sentiment signals with contextual reasoning, offering richer interpretive depth than conventional automated tools while highlighting sources of ambiguity in influencer language. This study demonstrates that ChatGPT can serve as a hybrid sentiment analysis tool, blending computational scoring with analyst-style interpretation. Following established criteria for evaluating sentiment analysis tools (accuracy, contextual sensitivity, handling of linguistic ambiguity and performance) on informal social media language (Mao et al., 2024; Zhang et al., 2024), ChatGPT's outputs were assessed in relation to benchmarks typically associated with conventional lexicon-based tools such as TextBlob and VADER (Qi & Shabrina, 2023), and transformer-based models such as BERT (Kokab et al., 2022; Talaat, 2023). This comparative framing allows for a structured evaluation of where ChatGPT adds interpretive value beyond what traditional automated tools offer. While ChatGPT does not replace specialised sentiment analysis tools, it offers a complementary, contextually sensitive approach that is particularly valuable for social media research, where informal language, emojis, and mixed emotional tones challenge traditional analytic tools. Implications of these outcomes include improved analytic transparency, enhanced qualitative insight and opportunities for mixed-method sentiment research using LLMs.

ABSTRACT. This study investigates the role of AI-powered chatbots in facilitating co-creation between fashion brands and consumers in online shopping environments. Drawing on value co-creation theory, the study explores how chatbots function not only as service tools but as interactive agents that enable collaborative engagement, personalisation, and shared decision-making. Using a social constructivist perspective and an inductive study approach, data were collected through semi-structured interviews with 35 UK-based online fashion consumers experienced in using AI chatbots and virtual personal stylists. The findings reveal that chatbots support co-creation by enhancing convenience, inspiration, and tailored recommendations, while also reducing social pressure during purchase decisions. However, limitations related to emotional intelligence, response speed, and contextual understanding constrain deeper co-creative experiences. The study highlights the need for AI–human-assisted chatbot designs to strengthen emotional engagement, trust, and long-term customer–brand relationships in fashion e-commerce.

ABSTRACT. Socially engaged scholarship has emerged as a key response mechanism of higher education institutions in addressing society’s challenges, especially in post-COVID South Africa. Despite the valorising of engagement as an ethical or civic obligation, dominant discourses often conceal the material, interpersonal and temporal contingencies that enable genuine practice. This paper probed SES as a form of institutional ecology, exploring the complex relationships among scholars, communities, governance bodies, policy-making processes, and sociopolitical environments. Based on reflections from longitudinal praxis spanning 2021 to 2025, the paper emphasises several conceptual misunderstandings, temporary lapses, and overarching omissions. There is a need for alignment between institutional expectations, acknowledgement of relational labour, commitment to long-term partnerships, and self-awareness in scholarly practices. The paper offers a more profound and nuanced perspective on socially engaged scholarship, providing a more thorough understanding of community engagement and potential outcomes, while highlighting both its strengths and weaknesses. The discussion also considers the attributes of metrics and valuation, demonstrating that decentralised reporting, publishing-biased reward systems, and uneven institutional support limit participation. The paper emphasises the need for longitudinal studies, equitable workload models, and context-sensitive evaluation methods in the future. This reframing disrupts celebratory and instrumental framings, providing higher education institutions with a basis to support an ethically informed, institutionally sustainable, and socially engaged scholarship that has the potential to be genuinely transformative.

ABSTRACT. The aim of this paper is to analyse mechanisms of translating research evidence in the fields of digitalisation and population ageing into public administration decision-making and to identify factors that facilitate or hinder this process. Although both areas represent strategic priorities of contemporary public policies, a substantial share of relevant research outputs remains underutilised in practice due to institutional, organisational and communicative barriers between academia and public authorities. The study seeks to identify existing forms of research knowledge transfer and knowledge translation and to propose instruments that support the systematic use of research evidence in the formulation of regional policies. The analysis focuses on the Czech Republic and Greece, which represent two distinct yet comparable national contexts within the European Union. Methodologically, the study adopts a qualitative research design combining multiple methods. The primary component consists of a systematic review of secondary sources, including academic literature, national and European strategic documents and policy frameworks related to digitalisation and ageing. This is complemented by qualitative research based on structured interviews with key stakeholders from academia and public administration, aimed at capturing their experiences with research uptake and evidence-based policymaking. A comparative analysis of selected international indicators and institutional arrangements for research–policy interfaces is conducted to enable a systematic comparison of the Czech Republic and Greece within the broader European context. The comparison is guided by predefined analytical categories, including institutional embedding of knowledge transfer, actor involvement and policy instruments supporting evidence-informed decision-making.The main outcome of the paper is a typology of research knowledge transfer and translation mechanisms in the fields of digitalisation and ageing, an identification of key barriers and enabling factors, and a set of policy-relevant recommendations for regional public administration. Based on the comparative analysis of the Czech Republic and Greece, the study highlights examples of good practice as well as structural constraints shaping the use of research evidence in policymaking. The paper contributes to the scholarly debate on research–policy linkages and evidence-based policymaking by proposing an empirically grounded analytical framework applicable to other national and regional contexts.

ABSTRACT. Entrepreneurship education is increasingly recognised as a means for addressing graduate unemployment and enhancing economic participation, particularly in emerging economy contexts such as South Africa. In response, higher education institutions (HEIs) have introduced entrepreneurship development initiatives aimed at equipping students with essential entrepreneurial knowledge, competencies and orientations. The Student Training for Entrepreneurial Promotion (STEP) programme is one such experiential entrepreneurship education initiative, designed to enhance students’ entrepreneurial capabilities through applied learning. Exploring participants’ post-programme perceptions may therefore provide useful insight into how such initiatives are experienced and how entrepreneurship education may be strengthened. Given the nature of the available dataset, this study does not endeavour to evaluate programme efficacy or to test a structured explanatory framework but instead, aims to explore post-programme entrepreneurial perceptions and selected relationships among variables, with the objective of generating insights for entrepreneurship education. A quantitative, cross-sectional research design was employed. Survey data were collected from 40 South African participants using a self-administered questionnaire. The analysis included descriptive statistics, reliability testing, and correlation analysis to identify patterns and selected associations among variables included in the survey. The results indicate positive and statistically significant correlations between a number of variables, such as entrepreneurial intention, entrepreneurial identity, entrepreneurial journey, and growth orientation. The results also suggest value in incorporating experiential learning strategies, reflective learning activities, and developmental support mechanisms that strengthen students’ entrepreneurial orientation. The study contributes to the entrepreneurial education literature by providing context-specific insight into post-programme entrepreneurial perceptions within a South African higher education setting, Rather than asserting causal programme effects, the study emphasises patterns of association that may inform the creation and enhancement of entrepreneurship education initiatives. Specifically, the results point to the value of instructional strategies that integrate experiential learning, introspection, and developmental support in fostering students’ entrepreneurial development. The study is limited by its cross-sectional design and relatively small sample size, which limit generalisability and preclude causal inference. Future research, employing longitudinal and mixed-method approaches with larger samples, is encouraged to deepen understanding of students’ entrepreneurial development over time.

ABSTRACT. Knowledge sharing plays a crucial role in fostering innovation in higher education institutions. This study examines how internal networking, shared values, and team cohesion influence knowledge sharing and innovation among research groups in Portuguese higher education institutions. Data were collected from 174 faculty members and analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings reveal that shared values positively influence knowledge sharing, which in turn enhances innovation. However, internal networking and team cohesion did not significantly affect knowledge sharing. The study provides empirical evidence from the Portuguese context and offers practical implications for managing research groups and promoting innovation in higher education.

ABSTRACT. Even when there are economic challenges in the African continent, South Africa is still a run to country owing to its stable and industrialised economy in the African continent. People search for a better standard of living by being employed or self-employed in the formal or informal sectors. The Johannesburg metropolitan municipality seems to receive a huge chunk of people, and it is referred to as the most populous municipality in the country, with over 6.6 million people as of 2025, compared to other municipalities in the country. It is one of the 100 largest urban areas in the world. The economic activity in this metropolitan city makes it attractive for people who want to open small, medium or even big businesses. Despite the opportunities available, many young people are unemployed and have to contend with the high cost of living. The self-employed people often venture into trades that require skill and labour, such as street vending and artisan work, such as welding, plumbing and many more. Those who advertise their trades in the streets often catch the attention of the public and law enforcement officials. Some of the street traders often operate in public areas in the Central Business District (CBD), closer to where the general public passes through. The street vendors often operate in busy streets and transportation terminals in the city, and they are of varied age groups and among them are even underage children. They are both South Africans and migrants alike. However, some informal traders often complain about law enforcement abuses and trafficking in persons from other countries. The paper examines the human and economic rights violations of informal traders within the Johannesburg Metropolitan Municipality and aims to establish ways to curb the practice. The research will propose a solution that will put a halt to human and economic rights violations of the informal traders by law enforcement agencies and even among the informal traders abusing other vulnerable people whom they have employed to trade on their behalf.

ABSTRACT. Introduction: The Full Bench judgment in Marais NO and Another v Daniels and Others constitutes a significant jurisprudential development in the interpretation of mediation under the Extension of Security of Tenure Act 62 of 1997 (ESTA) and the Land Court Act 6 of 2023 (LCA). While mediation has long existed as a dispute resolution mechanism within ESTA, it was historically under-utilised and treated as peripheral to eviction proceedings. Legislative amendments to ESTA in 2023 and the introduction of mediation provisions in the LCA created uncertainty regarding whether mediation is compulsory, its scope of application, and its temporal effect. This article analyses the judgment’s clarification of these uncertainties and examines how mediation has been repositioned as a mandatory procedural component of eviction litigation, directly linked to the constitutional protection of secure tenure under section 25(6) of the Constitution. Methodology: The article adopts a doctrinal legal research methodology grounded in statutory interpretation, constitutional analysis, and case law evaluation. Primary sources include the Full Bench judgment in Marais NO and Another v Daniels and Others, the relevant provisions of ESTA, as amended, and the Land Court Act 6 of 2023. Secondary sources, including academic commentary on land reform, alternative dispute resolution, and constitutional property rights, are utilised to contextualise the court’s reasoning and situate the judgment within the broader land rights jurisprudence. The analysis focuses on the interpretive questions posed by the court and the legal consequences arising from their resolution. Results:The court held that mediation under ESTA and the LCA is mandatory rather than discretionary. Two procedural consequences were identified: first, parties are required to attempt mediation before instituting eviction proceedings; and second, courts must consider whether a dispute could reasonably have been resolved through mediation before granting an eviction order. The court rejected arguments that mediation is inherently voluntary or that the LCA implicitly excludes certain categories of occupiers from its application. It further clarified that informal settlement negotiations do not constitute mediation and that only mediation conducted in accordance with the statutory framework satisfies legislative requirements. While mandatory mediation applies to eviction proceedings instituted after the legislative amendments, it does not automatically apply retrospectively to pending matters unless deemed appropriate by a court. Conclusions and recommendations: The judgment constitutionalises mediation as an essential instrument for the protection of vulnerable occupiers and the realisation of secure tenure rights. By embedding mandatory mediation into eviction procedure, the court advances alternative dispute resolution as a substantive, rights-protective mechanism rather than a procedural formality. The article concludes that mandatory mediation strengthens tenure security by facilitating meaningful engagement between unequal parties and mitigating power imbalances inherent in eviction disputes. It is recommended that courts, practitioners, and state institutions give full effect to the structured mediation framework to ensure consistency, procedural fairness, and the effective protection of land rights under section 25(6) of the Constitution.

ABSTRACT. South African acting judges and judges of the High Court and Labour Court are appointed in terms of Section 174 of the Constitution of the Republic of South Africa, 1996. South African acting judges are appointed in terms of Section 175 of the Constitution of the Republic of South Africa, 1996. Section 175(1) governs acting appointments to the Constitutional Court, while Section 175(2) covers acting appointments to other courts (such as the High Court and Supreme Court of Appeal) On the other hand, Section 169 (2) of the LRA provides that in order for a judge to be appointed in the Labour Appeal Court (LAC), such person should be a judge of the High court of South Africa. Therefore, a permanent judge of the Labour Court does not qualify to be appointed as a judge of the Labour Appeal Court despite experience and or qualifications. As a result of the above, the Labour Court stands to lose judges to the High Court, more especially those who aspire to become judges of the Labour Appeal Court or the Supreme Court of Appeal.

ABSTRACT. Introduction: The principle of pacta sunt servanda, requiring that contracts be honoured, has long underpinned South African contract law and has been particularly influential in the enforcement of antenuptial contracts (ANCs) within matrimonial property regimes. Historically, courts have shown marked deference to contractual autonomy, even where strict enforcement of ANCs produced manifestly inequitable outcomes. This position has been significantly recalibrated by the Constitutional Court judgment in EB v ER NO and Others and a Similar Matter 2024 (2) SA 1 (CC), which exposed constitutional deficiencies in the rigid application of marital property regimes, particularly marriages concluded out of community of property without accrual. The judgment laid the constitutional foundation for the proposed General Laws (Family Matters) Amendment Bill, 2025, which seeks to embed judicial discretion to prevent serious hardship upon the dissolution of a marriage. This article examines the doctrinal shift from contractual absolutism toward substantive fairness and constitutional justice in South African family law.

ABSTRACT. Digital banking has revolutionised the financial sector by enhancing accessibility and convenience; however, it has also created new opportunities for cybercriminals, particularly through increasingly sophisticated phishing attacks. As these schemes continue to evolve, Artificial Intelligence (AI) has emerged as a critical tool in combating such threats. This study examines how AI is transforming the detection, prevention, and response to phishing attacks within the digital banking environment. The primary objective is to analyse the effectiveness of AI-driven solutions in addressing phishing-related digital crimes. A qualitative research approach was employed, utilising semi-structured interviews to gather insights from victims and digital fraud investigators. Twenty (20) victims of digital banking fraud and ten (10) digital investigators were selected through purposive sampling. Secondary data were also incorporated to enhance the findings and provide a comprehensive understanding of AI’s role in mitigating phishing threats. The findings indicate that AI technologies such as machine learning algorithms, natural language processing, and behavioural analytics significantly improve the detection and mitigation of phishing attempts. However, challenges including data bias, high implementation costs, and the continuously evolving tactics of attackers remain significant concerns. The study further reveals that AI strengthens cybersecurity resilience and enhances digital forensic investigations by enabling faster identification of attack patterns and digital traces. The research concludes that integrating AI into banking cybersecurity frameworks is essential for proactive defence, improved incident response, and the long-term prevention of phishing-related financial crimes.

ABSTRACT. This presentation contributes to the “Hallway Conversations” session by sharing a, experiential approach to teaching financial literacy through a general education course centered on credit, rewards systems, and real-world financial decision-making. Designed for a broad undergraduate audience, the course addresses a persistent challenge in business education: helping students connect financial theory to everyday behaviors in a way that is both practical and engaging. The course is built around the idea of “using small money to travel big,” introducing students to the strategic use of credit cards, airline loyalty programs, and hotel rewards systems. Rather than focusing solely on abstract financial concepts, the curriculum emphasizes applied decision-making, including responsible credit management, aligning financial products with individual spending patterns, and optimizing rewards to reduce travel and living costs. These topics are explored through structured activities, case scenarios, and simulations that mirror real financial choices students are likely to encounter. This approach reflects the broader goals of the session by prioritizing innovative classroom activities and experiential learning to improve engagement and retention. Students actively analyze reward structures, compare credit options, and design personalized strategies based on their own spending habits. The course is also positioned as a preparatory experience for study abroad, helping students understand how financial tools can support global engagement in a financially sustainable way. In addition, having students transfer this knowledge to their parents would be a great example of how the students are learning practical solutions and efficiencies in our classrooms. The rationale for this design emerged from observed gaps in student financial literacy and a lack of engagement with traditional, lecture-based approaches. Many students enter college with limited understanding of credit systems, yet are immediately faced with financial decisions that have long-term consequences. By shifting to an applied, student-centered model, the course seeks to make financial education both relevant and actionable. Observed outcomes suggest increased student engagement, stronger participation in class discussions, and improved ability to apply financial concepts in real-world contexts. Students report greater confidence in evaluating credit products and a clearer understanding of how everyday financial decisions can accumulate into meaningful opportunities. This presentation will be delivered in a short, interactive format, encouraging discussion about how similar experiential approaches can be adapted across disciplines. Attendees will leave with practical ideas for integrating applied financial literacy into their own courses, reinforcing the session’s goal of transforming informal “hallway conversations” into actionable teaching strategies.

ABSTRACT. This presentation aligns with the “Hallway Conversations” session by addressing a widely recognized challenge in business education: the gap between employer expectations for technical skills and students’ actual proficiency, particularly in Microsoft Excel. While Excel is frequently embedded across business curricula, many students lack consistent, structured opportunities to develop and apply these skills in meaningful ways. This session presents a new course model specifically designed to build Excel competency through applied and experiential learning that also offers students the opportunity to earn industry-recognized certifications. The course targets economics and finance students but is broadly applicable across business disciplines. Its central objective is to support student success and career readiness by integrating technical skill development directly into the learning experience. The instructional approach in this new course emphasizes hands-on engagement through a series of “mini-applications,” where students complete targeted tasks that mirror real-world business scenarios. These activities are scaffolded to build proficiency over time, allowing students to progress from basic spreadsheet navigation to more advanced analytical tasks. By repeatedly applying Excel in context, students develop both technical fluency and confidence. A key motivation for this course design was the recognition that simply requiring Excel use in assignments is insufficient for skill development. Students often complete tasks without fully understanding the tools they are using, leading to superficial learning and limited transferability to other applications. This course addresses that gap by creating a structured environment where Excel is both the medium and the focus of learning. Consistent with the session’s emphasis on supporting student retention and addressing difficult concepts, the course also accounts for wide variation in students’ prior experience. Some students enter with strong technical backgrounds, while others require foundational instruction in basic functions. The course design allows for flexibility, enabling students to build skills at their own pace while working toward certification milestones. Observed outcomes include increased student engagement, improved confidence in using Excel, and greater awareness of the relevance of technical skills in professional settings. Students also benefit from the tangible credential of certification, which enhances their competitiveness in the job market. Presented in a short, discussion-oriented format, this session invites participants to reflect on how technical skill development can be more intentionally integrated into business curricula. It reinforces the broader goal of the “Hallway Conversations” session by offering a practical, scalable approach to bridging the gap between classroom learning and workforce expectations.

ABSTRACT. This presentation contributes to the “Hallway Conversations” session by sharing an applied, classroom-tested redesign of a required statistics course for business majors. The redesign addresses a common challenge in business education: helping students engage with and understand difficult quantitative concepts, particularly when traditional approaches rely heavily on algebraic manipulation. The course transitions from a formula-driven model to an Excel-centered, application-based approach using Microsoft Excel as the primary tool for exploration. This shift allows for innovative classroom activities and experiential learning, as students engage in structured “quests” and guided worksheets that allow them to interact directly with statistical outputs. Instead of emphasizing manual calculations, class time is devoted to interpreting results, communicating findings, and strengthening students’ conceptual understanding of statistics and its applications. A central feature of the course is the use of interactive activities designed to reduce the cognitive load associated with algebra, allowing students to focus on meaning and application. For example, students are asked to explain why Excel functions such as NORM.DIST produce left-tail probabilities and how to interpret those outputs in context, reinforcing deeper conceptual learning. We also use Excel simulations, including a confidence interval demonstration that helps students visualize sampling variability and better understand statistical inference. The rationale for this approach stems from observed difficulties students face in traditional statistics courses, where procedural fluency often does not translate into understanding. By shifting the focus of classroom activities and discussions to how and why we can use different Excel formulas, interpretation of outputs, and appropriate application, the course aims to improve both engagement and reinforce our learning outcomes. Implementation revealed both successes and challenges. While many students became more engaged and confident in interpreting statistical results, a significant number required foundational support in Excel, including basic skills such as navigating cells and managing files. Addressing these gaps became an integral part of the learning process, contributing to students’ overall digital literacy. To support diverse learners, the course incorporates a classroom-embedded tutor, enabling a more flexible and self-paced environment. This structure allows students who grasp concepts quickly to move ahead, while others receive targeted support. This approach aligns with the course’s emphasis on supporting student success and retention. Observed outcomes include increased participation, improved conceptual understanding, and greater confidence in working with data. This presentation will be delivered in an interactive format, encouraging discussion about how similar approaches can be used to teach difficult concepts across business disciplines. It exemplifies the core goal of the session: transforming practical teaching strategies into shared, actionable insights.

ABSTRACT. Technological sanctions are always be viewed as instruments of foreign policy, and they are intensifying in the era of geopolitically tension and de-globalization Therefore, how firms’ strategies respond in the global technology market to sanctions has received much attention from scholars both in the global business and technology management fields. We examine the relationship between technological sanctions and firms’ autonomy in the global technology market through the lens of real options theory. Firms’ autonomy in the global technology market is defined as the extent to which firms independently filing patents in international patent offices rather than jointly filing patents with external partners. Drawing on real options theory, we argue that technological sanctions will improve firms’ autonomy in the global technology market because the increased techno-geopolitical uncertainty induced by sanctions enhances the value of growth option such as layout patents in the global technology market. Based on a sample of Chinese high-tech listed firms between 2013 and 2023, we adopted the U.S. USTR’s List as a quasi-natural experiment with difference-in-difference method. Our results indicate that technological sanctions will increase the autonomy of firms from sanctioned countries in the global technology market by promoting independent patenting. Moreover, government supports can enhance the positive effect of technological sanctions on the autonomy of firms from sanctioned countries in the global technology market. The main contribution of this paper is two-fold. First, this paper adds new empirical evidence and theoretical arguments to the burgeoning literature on technological sanctions in international business. Although sanctions are becoming a global concern, our understanding of its impact on firms’ behavior regarding global technology management remains limited. Second, our paper contributes to the real options literature by focusing on sanction-induced techno-geopolitical uncertainty, an increasingly important type of uncertainty that has received scant attention in extant real options research.

ABSTRACT. The escalating U.S. technological blockade against China has introduced unprecedented economic policy uncertainties, profoundly disrupting global supply chains and impacting the innovative activities of Chinese enterprises. As access to critical external technologies becomes restricted, enterprises are compelled to reassess their innovation strategies. This study constructs a comprehensive framework exploring how such blockades drive enterprises to engage in strategic knowledge recombination. We specifically focus on the integration of emerging general-purpose technologies, such as Artificial Intelligence (AI), into existing technological portfolios, as AI represents a critical frontier for overcoming structural bottlenecks and maintaining competitive advantage. Employing a Difference-in-Differences (DID) empirical design, we systematically investigate how these blockades affect enterprises’ adoption of AI knowledge, measured through two distinct dimensions: knowledge adoption depth and breadth. Furthermore, we examine the moderating influence of existing knowledge dependencies on this mechanism. Our analysis yields several key findings. First, the China-U.S. technological decoupling paradoxically catalyzes innovation by significantly enhancing both the depth and breadth of Chinese enterprises' AI knowledge adoption. Second, an enterprise’s self-knowledge dependence acts as a strong catalyst, promoting both the depth and breadth of AI assimilation. Conversely, historical knowledge dependence on U.S. technologies restricts the depth of AI knowledge adoption, highlighting the vulnerabilities associated with external reliance during geopolitical frictions. By linking macroeconomic decoupling shocks with micro-level knowledge recombination, this study enriches the literature on innovation under geopolitical stress. Our findings provide vital insights for understanding changes in corporate innovative behaviors and fostering resilient ecosystems amidst global technological blockades.

ABSTRACT. Notwithstanding the role of smart cities in rapid urbanisation and the increasing demand for public services, their link to participatory governance remains underexplored. Local government in South Africa face persistent challenges, including infrastructure deterioration, limited resources, and social division, particularly in historically marginalised communities. These communities are characterised by informal economies, high crime, unemployment, poverty and inequality. These challenges have long hindered effective service delivery and deepened spatial inequities, leaving many communities without reliable access to basic municipal services or meaningful avenues for participation in governance. Smart cities, which use technology to improve the quality of life, offer transformative potential through IoT-enabled real-time monitoring, transparent decision-making, and inclusive service delivery. This paper presents a systematic literature review (2019-2026) of peer-reviewed sources from Scopus and Web of Science to address three objectives: (1) to assess the current state of smart city adoption across South African municipalities, with emphasis on community engagement strategies and service delivery outcomes; (2) to investigate how Internet of Things (IoT) driven smart initiatives can enhance participatory governance, particularly in resource-constrained township settings; and (3) develop a taxonomy of smart city. The preliminary results indicate that IoT-enabled solutions, such as capacity-building and digital literacy initiatives, feedback mechanisms that inform policy, and real-time monitoring of municipal outcomes, may promote transparency and socio-economic inclusion. Ultimately, this paper contributes to the growing discourse on smart cities in the Global South by demonstrating how technological innovation, when coupled with inclusive capacity building and community-centred design, can mitigate deep-rooted spatial inequalities and foster a more participatory, responsive and equitable model of urban governance.