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Effective leadership and organisational performance in technically demanding sectors increasingly depend on values-driven, human-centred approaches that extend beyond conventional managerial competencies. This qualitative study examines how workplace spirituality shapes leadership behaviour, organisational dynamics, employee development, and soft skill cultivation within a South African engineering organisation. Employing an interpretivist phenomenological design with fifteen purposively selected participants and inductive thematic analysis via Atlas.ti, six interrelated themes emerged: (1) understanding of spirituality; (2) challenges in employee development; (3) employee development strategies; (4) impact of spirituality on workplace dynamics; (5) spirituality and leadership decision-making; and (6) soft skills. Findings reveal that spirituality understood as connectedness, calling, integrity, and altruism enables transformational, servant, and spiritual leadership orientations that create psychologically safe, values-aligned environments. These environments demonstrably improve organisational commitment, ethical decision-making, human resource development outcomes, and soft skills formation, with direct implications for leadership strategy and organisational culture design. The study contributes to humanistic leadership and HRD scholarship in emerging economy engineering contexts, with practical implications for workforce transformation in post-apartheid South Africa.

This study investigates how a major South African private hospital group adopts and scales multiple renewable energy sources (MRES) within a mission-critical healthcare environment characterised by chronic grid instability. Using a qualitative single‑case study design, the research draws on semi-structured interviews with senior executives and technical managers, complemented by documentary analysis, to explore the barriers, enablers and governance mechanisms underpinning MRES adoption. The results reveal that financial and economic constraints, regulatory fragmentation, legacy infrastructure, and supply chain limitations constitute multidimensional barriers. In contrast, economic viability, executive leadership, risk-managed implementation, and energy-security imperatives serve as decisive enablers. The study demonstrates that effective adoption arises not from technology choices alone, but from an integrated organisational approach that combines diversified energy portfolios, phased implementation strategies, contractual procurement, and structured sustainability governance. The proposed Integrated MRES Adoption Framework synthesises these dimensions, offering a holistic model for energy transition in high-risk medical settings. The study concludes that hospitals can meaningfully advance renewable energy penetration when technical diversification is embedded within robust governance, financial feasibility assessments, and patient-safety-aligned risk management. Limitations include a single-case scope and senior-level perspectives; future research should compare public and private systems, evaluate long-term performance, and deepen inquiry into staff-level change processes.

Relational leadership is a key antecedent of employee attitudes and rewards perceptions. However, empirical evidence linking its specific dimensions to compensation outcomes within South Africa’s context remains limited. Drawing on social exchange and equity theories, this study examines how specific relational leadership dimensions influence compensation perceptions. Data was collected from (N = 122) permanently employed personnel at a South African organisation, using a quantitative, cross-sectional design and validated self-report measures. The data was analysed by using Pearson correlations and multiple regression to predict employee compensation through relational leadership. The ethical component emerged as the most consistent and dominant predictor of employee compensation across all models. The empowering component showed significance in one model, but the dimensions usually linked to RLP, including inclusive, caring, and visionary components, had no statistically significant impact on reward outcomes. These findings highlight a critical distinction between behaviours that foster a supportive climate and those that validate the structural legitimacy of reward systems. The study concluded that in socio-economically complex environments like South Africa, employees prioritise ethical governance and fairness over interpersonal warmth when evaluating compensation. Consequently, organisations should prioritise ethical decision-making and transparent accountability in LDPs to enhance satisfaction and perceived equity.

This systematic review examines how organisational culture (OC) influences organisational change in developing countries, addressing a literature gap concentrated in Western, high-income contexts. Following PRISMA 2020 guidelines, we analysed 35 studies published between 2000 and 2025, spanning healthcare, manufacturing, higher education, public administration, and finance across 15 developing nations. The synthesis employed thematic analysis guided by the Competing Values Framework and institutional theory. Results indicate that organisational culture operates as a contingent mediator rather than a uniform driver or barrier. Clan culture consistently facilitates change through empowerment, trust, and participative decision-making. Conversely, a hierarchy culture typically impedes implementation through centralised authority, information hoarding, and suppressed psychological safety. Adhocracy and market cultures produce context-dependent effects, moderated by sectoral constraints and managerial practices. National cultural dimensions, political interference, and resource scarcity significantly moderate these relationships, often neutralising formal change policies. The findings demonstrate that change management practices mediate the culture-outcome link but require multi-level alignment to succeed. This review contributes a contextual model for OC-change dynamics, extending Western frameworks by showing that hierarchy in developing contexts is frequently an institutionalised norm rather than a managerial preference. Practically, the study provides evidence-based guidance for diagnosing cultural fit, adapting change strategies to national realities, and addressing systemic resource constraints.

Financial institutions predict the probability of default when making lending decisions using conventional credit risk scoring models. However, in emerging economies, the underbanked, widows, small and medium enterprises owners and youth are not able to access traditional forms of collateral or identification required by financial institutions due to lack of data for them to get access to loans. Financial institutions cannot obtain much of the information required about an applicant and they use alternative data sources such as public data or social media to deal with the problems of information asymmetry, adverse selection and moral hazard. To eliminate such problems, credit risk assessment models must be built on the foundation of artificial intelligence and machine learning approaches in an effort to perform an accurate credit risk analysis, to properly assess the behaviour of the customers and subsequently perform a thorough verification of the potential of the applicant to repay the loan thereby allowing less privileged people to access credit. However, big data sourced from the internet and public data sources is characterized by huge volume, variety, veracity, the curse of dimensionality, class imbalance, concept drift and non-linearity among others. These challenges affect the generalization performance of credit risk assessment models used by most financial institutions. This paper proposes an efficient and effective credit risk assessment model capable of learning incrementally based on machine learning algorithm called Adaptive Heterogeneous Dynamic Ensemble Selection (AHDES) that uses big data from alternative sources for financial for the underbanked. The algorithm is agile and adaptive to unexpected world events, changes in customer behaviour and cognitively counter bias likely to be introduced by information asymmetry. Experimental results on four large credit datasets and five evaluation metrics show that our proposed algorithm performs better than other selected benchmark models allowing the underbanked and less privileged to access loans to stimulate economic growth.

Organisations in emerging markets, particularly on the African continent, are transitioning from linear value chains towards complex platform ecosystems, and Generative Artificial Intelligence is accelerating this shift. GenAI introduces new skill demands, hybrid human-machine roles, and the need for adaptive continuous learning. In the African context, leaders must navigate this alongside infrastructural brittleness, institutional voids, and the need for contextually grounded governance. This study explored how senior leaders in an African financial institution make sense of and navigate GenAI-enabled transformation. The study adopted a qualitative, exploratory, and constructivist case design, involving the purposive sampling of seven senior leaders from a financial institution, who were interviewed. Data was thematically analysed. The findings reveal that in some African emerging economies, financial institutions face transformational challenges stemming from strategic misalignment, capability fragmentation, and tensions between global technological pressures and locally rooted ethical expectations. The study provides a contextually grounded account of how senior leaders in an African financial institution interpret GenAI-enabled transformation amid infrastructural fragility and institutional voids, guiding executives and policymakers in creating sustainable value within GenAI-driven digital ecosystems. The value-add of the article lies in challenging the applicability of canonical Western-centric models to African contexts and in advancing a contextually grounded understanding of leadership sensemaking.    

How users perceive and respond to cybersecurity warning messages under cognitively demanding conditions can result in unintended cybersecurity failures. Digital banking environments can create cognitively demanding conditions, as users are required to make quick decisions while managing many other routine tasks. This can lead to cognitive overload and pressure to comply with cybersecurity warning messages. This study examined how cybersecurity messages are framed and how this framing could influence behavioural responses under cognitively demanding conditions. The study draws on behavioural and psychological perspectives, including the Cognitive Bias Theory, the Framing Effect, and the Cognitive Load Theory, offering critical insights into compliance cybersecurity behaviour. A quantitative survey was administered to 267 South African users in digital banking environments. Path analysis, an extension of multiple regression analysis, was used to examine the relationships among message framing, mental load, and familiarity bias, and how these factors influence behaviour, thereby impacting digital banking resilience. Findings showed that, for organisations in digital banking to be cybersecurity resilient, such resilience is largely shaped by message framing and cognitive processing load. This means message framing is a central behavioural mechanism that shapes behaviour and an organisation's overall cybersecurity posture. Similarly, mental load affects behaviour change, meaning that concerted cognitive pressures will influence users’ ability to engage with cybersecurity warnings. Familiarity bias was negatively associated with desired behaviour change, highlighting a risk of habitual reliance on familiar cybersecurity messages. The study contributes to ongoing cybersecurity research on aligning cybersecurity communication with users’ cognitive capacity, prompting institutions to rethink and redesign clear, cognitively efficient security messages that support decision-making under pressure.

The COVID-19 pandemic accelerated hybrid work adoption, essentially altering line managers' roles as they navigate supervising geographically dispersed teams. Despite widespread implementation, limited qualitative research examines how managers adapt their leadership practices within this evolving work model. This study explored the perceived challenges, opportunities, and leadership adaptations amongst line managers in hybrid settings, aiming to reveal factors that enhance leadership capability, team performance, and strategic HR practices. Inadequate understanding of managerial perceptions hinders evidence-based leadership development tailored for hybrid contexts. Line managers experience increased stress managing distributed teams whilst balancing flexibility with accountability, yet empirical research focusing on their experiences remains scarce. Adopting an interpretivist paradigm, this generic qualitative study conducted semi-structured interviews with 12 line managers from diverse sectors possessing at least two years of managerial experience supervising hybrid teams. Manual thematic analysis following Braun and Clarke's (2006) framework identified recurring patterns. Four themes emerged: challenges characterised by a trust-visibility paradox requiring structured communication and output-based monitoring; leadership opportunities demanding trust-based, emotionally intelligent, digitally fluent approaches; transformed practices shifting from presence-based to performance-based supervision; and critical organisational support needs including emotional intelligence training and clear hybrid policies.  Organisations must implement targeted interventions including hybrid-specific leadership development programmes, formalised communication protocols, output-based performance systems, and systematic wellbeing support.

The study investigates governance challenges in South Africa’s state-owned entities (SOEs) by assessing disclosures provided in SOEs’ annual reports and financial statements regarding fraud, unauthorised expenditure, irregular expenditure, and fruitless and wasteful expenditure between 2022 and 2024, in line with section 55 of the Public Finance Management Act (PFMA) No. 1 of 1999. Adopting an interpretivist research philosophy, the study utilizes qualitative methods through a content analysis of the annual reports and financial statements of the five sampled SOEs. The analysis revealed that, although the selected SOEs demonstrated partial compliance with Section 55 of the PFMA, significant governance and reporting shortcomings persist. While most SOEs maintained records and produced financial statements, none provided evidence of submitting these reports within the required timeframes, and one entity had not produced its 2024 reports by the cut-off date of 10 October 2025. The financial statements frequently lacked a fair and accurate reflection of each SOE’s financial position and performance. Disclosures related to financial misconduct were particularly weak and inconsistent, with irregular, fruitless, and wasteful expenditure reported more often than cases of fraud or unauthorised expenditure, which were largely omitted. These disclosure shortcomings suggest that compliance among SOEs remains superficial and procedural rather than substantive, undermining accountability, transparency and the overall integrity of financial reporting.

Cybersecurity threats pose a growing challenge for organizations in digitally dependent economies, with South African organizations facing increasing incidents of data breaches and ransomware, among other threats. This study investigates how organizations can enhance cybersecurity resilience by aligning data privacy regulations with business resilience strategies. A quantitative survey of 201 professionals across multiple industries in South Africa was conducted, guided by Protection Motivation Theory (PMT), Diffusion of Innovation Theory (DIT), and Resilience Theory. Analysis revealed that while organizations perceive the severity of cyber threats, internal threat perception alone does not drive innovation. Instead, external regulatory and institutional pressures emerged strong driver of cybersecurity innovation, which in turn strengthens cybersecurity resilience. Based on these insights, a Cybersecurity Resilience Model was developed as a defence mechanism against cybersecurity threats and attacks.

Entrepreneurship policy occupies a significant role in the economic and social development policies of BRICS Plus states, but its efficacy is still debated. This study seeks to analyse the congruence between entrepreneurship policy frameworks, institutional conditions, and the realities of entrepreneurial ecosystems in situations where entrepreneurship is extensively advocated as a catalyst for job creation, poverty alleviation, and inclusive growth. This study employs a systematic literature review framework based on PRISMA principles, utilising peer-reviewed research from entrepreneurship, public policy, and development studies to examine the influence of policy instruments and institutional arrangements on entrepreneurial activity and development outcomes. The analysis indicates a continual disparity between policy intentions and actual implementation, marked by the prevalence of formal, organization-focused, and growth-driven policy assumptions that insufficiently address the informal, hybrid, and collective entrepreneurial practices common in BRICS Plus environments. Key findings (i) reveal inadequate integration of community-level ecosystems, (ii) institutional complexity hindering policy implementation, and (iii) misalignment between entrepreneurship policy objectives and inclusive development as well as Sustainable Development Goal (SDG) outcomes. The study proposes a policy-ecosystem alignment framework that redefines entrepreneurship policy as an adaptive, multi-tiered process situated within intricate institutional contexts. The research proposes a Policy–Ecosystem Alignment Framework that synthesises policy orientation, institutional conditions, ecosystem dynamics, and development results to elucidate disparities in entrepreneurial policy efficacy among BRICS Plus nations. The study suggests that achieving more inclusive and context-sensitive entrepreneurship outcomes in BRICS Plus nations necessitates policy frameworks that acknowledge entrepreneurial variety, institutional diversity, and ecosystem dynamics.

The Fourth Industrial Revolution (4IR) altered how institutions and people interact and operate in various contexts. Technological advancements through e-government have resulted in more responsible, transparent, effective, and efficient governance and service delivery in Lesotho. The adoption of e-government and its influence on service delivery in Lesotho are examined in this study using a systematic scoping review process guided by the PRISMA 2020 framework. Using the Technology Acceptance Model (TAM) as its theoretical lens, the study argues that citizen adoption is dependent on perceived usefulness and ease of use, both of which are significantly hindered by local constraints. The evaluation acknowledges gains made through programmes such as the 2013 e-Government Infrastructure Project, which has increased efficiency and transparency, particularly in metropolitan areas such as Maseru. Nevertheless, it also draws attention to a notable implementation gap, with a sizable urban-rural digital divide that marginalises rural residents due to inadequate infrastructure, expensive ICT, and restricted coverage. Serious accessibility issues are also exacerbated by inadequate digital literacy and the predominance of English over Sesotho on government websites. According to the study, resolving these problems calls for a multifaceted strategy. Investing in rural digital infrastructure, lowering access fees, requiring multilingual and accessible digital content, and starting national digital literacy initiatives are all part of this strategy to transform e-government into a tool for equitable service delivery and inclusive development for all Basotho.

This study’s main goal is to find out how blockchain technology may improve food safety and quality management in supply chains serving emerging markets. The increasing pressure on the global food supply chain to ensure the safety and quality of food products served is the driving force behind this study, particularly in poorer countries where infrastructure and regulatory oversight may be less developed. The information asymmetry, weak traceability systems, and fragmented structures that often define supply chains in emerging markets provide significant challenges to food safety and quality control activities. In recent years, blockchain technology has emerged as a potential solution to these problems. The study employed qualitative research approach using a qualitative data analysis programme, ATLAS. ti 23. Having embraced the interpretivist paradigm, about 25 supply chain professionals were purposefully selected for this study. Following thematic analysis, the following themes emerged from the primary data: Blockchain technology fundamentals, challenges in emerging market supply chains, blockchain applications and mechanisms, benefits and challenges of blockchain adoption, policy and regulatory considerations, socio-economic impacts. Using blockchain technology will enable real-time tracking of agricultural goods from farm to consumer in supply chains in emerging markets, like South Africa. Better traceability is ensured, allowing businesses to promptly pinpoint the cause of contamination or quality problems. This reduces the likelihood of widespread foodborne illnesses and recalls. By making sure that all parties involved farmers, suppliers, distributors, and retailers are held responsible for upholding safety and quality standards, this can lessen fraud and tampering. Blockchain technology is becoming more and more popular in developed market supply chains, but its potential in emerging countries is still limited, especially when it comes to food safety and quality control. This study offers fresh perspectives on how blockchain might be tailored to these regions’ particular opportunities and problems, like disjointed supply chains, constrained infrastructure, and inconsistent regulations.

Customers’ demand for printing industry to be more productive and compete globally in relation to delivery, cost, quality and use of technological factors is one of the factors which have a possible impact on productivity. Printing establishments through the South African printing industry have a major role to play in the country’s economy. Printing industry is characterised by overloading, inefficiency and ineffectiveness affecting overall organisational performance. The purpose of this study is to examine the factors influencing productivity improvement practices and develop productivity improvement model to improve printing division. This study follows a qualitative research approach as it is an exploratory research technique used to understand the underlying reasons, perceptions and motivations of individuals in solving a problem. A sample of Government Printing Works’ (GPW) employees directly involved in the printing, finishing and packaging of Higher Education and Training examination question papers located in Pretoria, City of Tshwane municipality participated in this study. A number of critical success and barriers to productivity improvement practices are identified.  Barriers factors include poorly designed process; poorly designed layout; poor quality materials; lack of effective maintenance plans; unsatisfactory planning; supplier inefficiencies and customer inefficiencies were the major causes of low productivity in the GPW. This comprehensive and holistic framework can assist government printing employees’ and lean practioners’ in their lean manufacturing implementation journey systematically and improve the organisation’s performance.

The swift proliferation of Artificial Intelligence (AI) and algorithmic technologies in the criminal justice system and legal profession is apparent worldwide. Machine learning algorithms are currently impacting sentencing determinations in multiple jurisdictions globally. Artificial intelligence, in contrast to the organic intelligence of humans and animals, possesses the ability to learn, adapt, and evolve through the assimilation of knowledge and new information. AI software can independently learn and enhance its performance based on the data it acquires. These algorithms can identify trends, elaborate on them, and discover more effective methods for executing specific activities via automation. Human fallibility necessitates the integration of AI as an essential instrument in judicial decision-making, especially in criminal sentencing, thereby aiding judges in achieving more precise and efficient outcomes, which permits them to concentrate on other matters. This paper assesses the application of artificial intelligence in criminal sentencing within the judicial system from a comparative standpoint. A mixed-method approach was utilised, integrating qualitative and quantitative techniques for data collecting, encompassing in-person interviews and surveys. The research demonstrated that AI systems can swiftly analyse extensive amounts of legal language, facilitating tasks such as transcription, document summarisation, and legal research. AI employs diverse algorithms to address a multitude of problems through pattern recognition and the execution of precise instructions. Through the analysis of huge datasets, AI can deliver impartial recommendations, resulting in more uniform sentence outcomes for analogous situations. Artificial intelligence can evaluate an offender's likelihood of recidivism by analysing variables such as age and educational background, thereby aiding courts in making educated sentence decisions. The study indicated that the risks and obstacles linked to AI in sentencing encompass prejudice amplification, potential coercion of judges to conform to AI suggestions, and ethical issues related to transparency and human rights. To alleviate these hazards, transparency mandates are crucial for enabling judges to comprehend the elements evaluated by AI systems. Stringent data-quality criteria must be established to avert the recurrence of inequitable sentencing practices. Proactive supervision and regulation of AI are essential, accompanied by rigorous legislation overseeing the design and development of algorithms. Consistent auditing, targeted AI training, and instruction for judges and legal practitioners are essential for the proper integration of AI in the criminal justice system..    

The research focused on the contribution of forensic accounting to the detection and prevention of money laundering in Zimbabwe. It sought to find out how forensic accounting methods are implemented, evaluate their effectiveness in ensuring compliance with the recommendations of the Financial Action Task Force (FATF), assess the contribution of forensic accountants to the activities of the Financial Intelligence Unit (FIU), understand the institutional challenges of implementation, and create an integrated forensic accounting model. The researchers used a mixed-methods design. Quantitative data were gathered through 235 structured questionnaires, and qualitative data were obtained from 15 purposively selected key informants. Quantitative data were processed using descriptive statistics, correlation, and multiple regression techniques in SPSS. Qualitative data were analysed thematically to determine the main themes and stakeholder views. The results showed that forensic accounting techniques, such as transaction tracing, risk-based auditing, and the use of technology, are extensively practised and, thus, significantly facilitate the identification of suspicious transactions. These activities positively influence the compliance of the FATF, primarily through regular audits and reporting. Nevertheless, limited funding, lack of sufficient training, and poor cooperation between agencies were some of the challenges that prevented the agency's effectiveness. The regression results reveal that the use of forensic accounting techniques, compliance with FATF standards, contributions from the FIU, and technological integration are factors that significantly improve the effectiveness of AML. On the other hand, institutional challenges have a negative impact on the effectiveness of AML, thus the need for a coordinated approach is confirmed. The study recommends integrating the use of technology, joint training, and regulatory compliance into a comprehensive forensic accounting model.

The mandate of correctional services is to uphold and advance a just, peaceful, and secure society by ensuring that the corrections environment is secure, safe, and humane, while ideally rehabilitating criminals to minimise their probability of re-offending. Realising these objectives necessitates a shift from the traditional correctional system to a digital, intelligent, and data-driven approach, encompassing the gathering and analysis of information within correctional facilities to identify and mitigate hazards. Intelligence-driven corrections deploy correctional intelligence, data analysis, specialized software, and databases for mapping complicated relationships, assessing forensic evidence, and exchanging information across jurisdictions. They apply data analytics to foresee prospective dangers, such as the likelihood of violence, contraband introduction, or jail riots. The research examines enhanced corrections and intelligence-based advances in modern correctional services. A mixed-method approach was utilised, integrating qualitative and quantitative designs. Interviews, surveys, and secondary data were employed. The research indicated that more intelligent corrections utilise technology and data to oversee inmates, personnel, and visitors, minimise expenses, and enhance public safety and security. Intelligence-driven corrections utilise gathered and analysed intelligence to guide decision-making and resource distribution within correctional facilities, hence improving safety and security by recognising dangers and thwarting criminal activity. Digital technologies improve offender management, security, safety, surveillance, and efficiency through the use of biometrics, facial recognition, artificial intelligence, data analytics, robotics, and drone detection. Artificial intelligence in correctional services improves safety through real-time behaviour surveillance and incident identification, enhances efficiency by automating administrative functions, and offers personalised rehabilitation through customised educational and mental health initiatives, ultimately seeking to diminish recidivism. Blockchain technology in correctional systems provides improved security, transparency, and efficiency, especially in monitoring inmate movements and preserving the integrity of evidence. Evidence-based risk assessment facilitates tailored rehabilitation programs that aid in crime reduction. The study advocated for the adoption and implementation of advanced correction methods, intelligence-driven strategies, technological innovations, and digital devices to improve safety and security in South Africa, other African countries, and worldwide.

The prevalence of drug and substance misuse among youth has emerged as a significant worry for both the government and society as a whole. Presently, South Africa and several nations globally are witnessing a rise in substance addiction among youth. Substance misuse among youth has resulted in engagement in criminal activities, including violence, robbery, cash-in-transit heists, sexual assault, homicide, theft, domestic violence, and gang-related offences. The government and partners are actively working to combat the elevated prevalence of drug and substance addiction among the youth in South Africa. There is a necessity to employ technology for the identification, prevention, and investigation of substance addiction among youth in South Africa. This article examines the application of technology in combating drug and substance abuse among children in South Africa. A mixed-methods strategy was employed, integrating qualitative and quantitative procedures for data collecting. The research indicates that technology-driven universal prevention strategies focus on adolescents. These interventions comprise interactive digital activities aimed at enhancing drug-related information, modifying attitudes and normative beliefs towards substance use, and preventing the initiation of substance use. The interventions are executed in three environments: primary care, educational institutions, and residences. Adolescent engagement in drug and substance addiction arises from adverse economic circumstances, unemployment, political turmoil, ethnic strife, ineffective policy execution, and the consumption of psychoactive substances. Substance misuse constitutes a public health crisis and a global concern, adversely affecting the psychological and emotional well-being of youth. The government is advised to implement measures for the rehabilitation, empowerment, and assistance of youngsters to prevent substance misuse. Technology ought to be utilised in combating drug usage among children, encompassing detection, prevention, and investigation of drug-related matters.

This research investigates the strategic management of pharmaceutical supply chains in South Africa, with a focus on responses to disruptions resulting from the COVID-19 pandemic. The study explores how supply chain professionals navigated unprecedented challenges and implemented resilience strategies during this crisis. A qualitative, exploratory phenomenological approach was employed using semi-structured interviews with 25 pharmaceutical supply chain professionals selected through purposive sampling. Participants represented diverse segments of the pharmaceutical supply chain, including manufacturers, distributors, wholesalers, and retailers. Data were analysed using thematic analysis with Atlas.ti software to identify patterns and relationships within participant experiences. Four major themes emerged from the analysis: (1) disruptions in supply chains due to COVID-19, characterised by panic buying, logistical challenges, and inconsistent supply; (2) impact on strategic decision-making and operational performance, including implementation of skeleton staffing and increased operational costs; (3) resilience and responsiveness strategies, focusing on supplier relationships, enhanced demand forecasting, and increased local production; and (4) lessons learned and future preparedness, emphasising disaster management frameworks and technological advancements. The study highlights the importance of developing balanced strategic approaches that address immediate disruptions and long-term resilience in pharmaceutical supply chains. Key findings reveal that effective strategic management during crises requires simultaneous attention to operational adjustments (skeleton staffing, remote work) and strategic initiatives (local production, technological investment). These insights contribute to understanding how pharmaceutical supply chains in developing economies can enhance resilience against future disruptions through strategic management practices that balance reactive and proactive approaches.

Despite significant initiatives to enhance educational access for marginalised communities in Africa, the prevalence of street children not enrolled in school remains substantial. Despite several studies examining educational access disparities among marginalised groups, obstacles to governmental initiatives aimed at enhancing educational opportunities for street children in Africa remain insufficiently investigated. This study elucidates these constraints, concentrating on Mutare Urban, Zimbabwe.  It examined the obstacles to governmental initiatives aimed at enhancing educational access for street children in Mutare Urban, Zimbabwe. The study employed a human rights-based approach as its theoretical framework to answer this subject. The research employed a qualitative methodology, utilising interviews, focus group discussions, and documentary analysis for data collection. These methodologies enabled the researchers to comprehend the subjective, lived experiences and perspectives of participants on obstacles to governmental initiatives aimed at enhancing educational access for street children in Mutare Urban. The study identified social disintegration, economic limits, insufficient teamwork, and corruption and nepotism as primary obstacles to governmental initiatives aimed at enhancing educational access for street children in Mutare Urban. The report advises enhanced funding, collaboration, monitoring, and evaluation of government programs, as well as a case-by-case approach to facilitate access to school for street children in response to the identified problems.