International Journal of Business Ecosystem & Strategy

The utilization of powerful machine learning models in artificial intelligence offers novel prospects for the identification of fraudulent activities. Artificial Intelligence (AI) is a revolutionary technological tool that enhances the ability to detect and prevent fraud by improving efficiency and effectiveness. This research offers a thorough examination of the utilization of artificial intelligence technology in the realm of procurement fraud prevention and detection. Additionally, it highlights the obstacles that arise when employing machine learning techniques for the purpose of identifying and preventing fraudulent activities. A mixed methods approach was employed in this study, wherein data was collected through an unstructured interview and questionnaire. We conducted a comprehensive review of relevant scholarly articles and online resources. The findings indicate that fraudsters are progressively advancing in their skills, which poses a significant challenge in detecting fraudulent activities. The advent of AI in fraud detection has demonstrated its transformative impact. AI has achieved unparalleled precision and velocity in crime detection and prevention, surpassing the capabilities of any human. Artificial intelligence (AI) enhances the capacity for automation. Accessing unstructured data in the form of spreadsheets, digital documents, and email inboxes poses a significant issue for the procurement function. In order to achieve a successful procurement transformation, businesses should prioritize the creation of essential tools, guarantee acceptance through the establishment of a superior user experience, and integrate both novel and pre-existing technology. It is imperative to disseminate knowledge to the general public regarding the escalating sophistication of artificial intelligence (AI) in the realm of fraud detection and prevention. This includes elucidating the potential benefits of AI in identifying patterns of suspicious activities, assessing its efficacy in predicting potential threats or fraudulent activities prior to their manifestation, and exploring its utility in analyzing historical data pertaining to both familiar and unfamiliar forms of fraudulent behavior.

Road’s infrastructure is regarded as an essential factor to achieve development goals. It is recorded that most people living in the rural areas are constrained by poor road infrastructure, thereby causing poverty, hunger, and food insecurity. This situation calls for more investments in road infrastructure to promote agricultural activities. Using systematic review method, this study reviewed literature pertaining to road infrastructure in South Africa, the review focused on the importance, benefits, and present state of road infrastructure and the socio-economic effects of poor road infrastructure. The study revealed that Most South African roads are in bad shape, especially roads in the rural areas. due to lack of qualified personnel to manage road infrastructure, government regulations and policies and financial challenges. The implications of this study's findings are substantial for future research. Firstly, in order to ensure the timely delivery of infrastructure construction projects, the study's findings are expected to provide guidance to decision-makers and stakeholders in South Africa and other nations on how to proactively implement measures to provide and maintain sustainable, good road infrastructure.

The main aim was to determine how the supply chains of the FMCG industry may enhance their resilience through the adoption of digital technologies. Additionally, enhancing visibility and transparency through the augmentation of operational efficiency to elevate overall performance. This analysis utilised the Uncertainty Framework theory, which provides a systematic approach for identifying, categorising, and managing uncertainties within the supply chain. Organisations can formulate strategies to effectively manage and mitigate risks by understanding the many dimensions of uncertainty within the supply chain and their interrelations. The research utilised a qualitative methodology, gathering data via semi-structured interviews with 25 supply chain specialists and senior executives possessing extensive experience in the FMCG sector. The study's findings indicate that digital transformation enhances agility, transparency, and data-driven decision-making, which is crucial for bolstering the resilience of the FMCG supply chain. Six themes emerged from the findings: data-driven decision-making, supply chain visibility and transparency, automation and robots, collaborative platforms and ecosystems, predictive analytics and forecasting, and traceability and sustainability. The research will enhance our understanding of the implementation of digital transformation initiatives throughout FMCG supply chains. This involves analysing the application of digital technologies in supply chain operations. The study may ascertain the impact of these technologies on various resilience criteria, including flexibility, agility, visibility, and responsiveness, by analysing the role of digital transformation in FMCG supply chains. The research findings can assist supply chain managers in making educated decisions on investments and strategic planning for digital transformation initiatives.Research on digital transformation in the FMCG sector is limited, particularly on these unprecedented upheavals. Moreover, there is little study connecting digital transformation with sustainability and resilience in FMCG supply chains, which is essential for comprehending how these projects might collaboratively enhance robust supply systems.

Advancements in science and technology has resulted in substantial transformations inside society. The telecommunications sector has established cyberspace, a virtual domain for online communication, data exchange, and digital interactions. This platform enables individuals to interact and cultivate relationships worldwide, fostering a sense of proximity despite geographical separation. Nonetheless, these improvements provide concerns, since there has been an increase in cyber victimisation via cyberspace, the internet, computer networks, and online systems. Criminals are progressively utilising these technologies to perpetrate illicit actions, endangering individuals, governments, organisations, and institutions.This study analyses the evaluation of cyber policies for regulating, monitoring, and supervising cyberspace activities, along with the implementation of cybersecurity measures to address technologically advanced crime. A mixed methods strategy, including qualitative and quantitative methodologies, was employed for data collecting. The research revealed that although cyberspace provides avenues for social contact, idea exchange, information dissemination, commercial transactions, and additional activities, it remains susceptible to cyber threats including ransomware, fraud, warfare, terrorism, trafficking, and breaches of privacy. Formulating cyber regulations to regulate actions in cyberspace is crucial for efficient law enforcement, alongside the establishment of a cybersecurity framework to safeguard critical cyber systems and bolster security protocols across several sectors. To safeguard both the public and private sectors against cybersecurity risks, it is essential to create and execute plans. These tactics encompass the regular evaluation and auditing of security systems, investment in cybersecurity training programs, maintenance of current systems, formulation and rehearsal of incident response plans, and dissemination of information among experts and professionals.

Currently, numerous institutions, organisations, and governments globally have issues associated with rising technological crimes and misinformation within cyber systems, which jeopardise societal faith in these entities. A cyber-system is a framework that employs cyberspace and encompasses information infrastructures, along with individuals and other entities engaged in the system's business operations and activities. Social media platforms facilitate communication, commercial transactions, and various lucrative endeavours. Nonetheless, these sites have been utilised by cybercriminals and fraudsters for nefarious activities, including executing assaults on their targets and disseminating misinformation. This article examines the assessment of developing technological crimes on social media platforms and techniques for mitigating disinformation in cyber networks. A mixed-method approach was employed for data collecting, incorporating both qualitative and quantitative techniques, with unstructured interviews and surveys. The findings indicated that disinformation has adversely affected multiple sectors, including health, social, security, and education. Conspiracy theorists have utilised cyber systems and social media platforms to propagate misinformation, while fraudsters and cybercriminals have exploited these mediums to victimise individuals. Recommendations encompass the necessity for governmental regulation of online activities, the education of cyber system and social media users to exercise caution regarding their online conduct, the implementation of robust cyber policies and legislation, the verification and authentication of information prior to dissemination, the training and retraining of criminal justice officials, and the engagement of cyber law enforcement to scrutinise messages and information traversing cyber systems and social media platforms. tem. Social media platforms are used for communication, business transactions, and other profitable initiatives. However, these platforms have also been exploited by cyber criminals and fraudsters for malicious activities, such as launching attacks on their targets and spreading false information. This paper focuses on evaluating emerging technology crimes on social media platforms and strategies for reducing misinformation on cyber systems. A mixed method was used for data collection, including qualitative and quantitative methods, as well as unstructured interviews and questionnaires. The findings revealed that misinformation has had negative impacts on various sectors including health, social, security, and education. Cyber systems and social media platforms have been used by conspiracy theorists to disseminate false information, while fraudsters and cybercriminals have victimized their targets using social media and other cyber systems. Recommendations include the need for government regulation of online activities, educating cyber system and social media users to be cautious about their online activities, implementing effective cyber policies and legislation, verifying and authenticating information before sharing, training and retraining criminal justice officials, and engaging cyber cops to filter messages and information passing through cyber systems and social media platforms.

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.