ABSTRACT This study uses bibliometric methodology to explore digital financing, adherence to ESG regulations and IT risk management in audit research from 2015 to 2025. A total of 103 articles out of 72 sources were examined in this subject. Most research is carried out on the domestic market, including small international cooperation, and each article usually has almost three authors. Research defines four primary clusters: digital financial innovation and compliance; ESG report on security and sustainability; Risk management and audit quality; and convergence of technological acceptance, administration and management of enterprises and ethical supervision. The discovery shows that the merger of ESG protocols with digital financial systems and IT audit framework increases transparency, risk reduction and organizational efficiency. Despite restrictions on indexed English publications, studies provide a comprehensive overview of emerging trends, practical consequences and research gaps and offer instructions for scientists, auditors and financial institutions that seek to use technology and management for sustainable and efficient operations.

ABSTRACT AI has become a revolutionary element in international finance, providing innovative methods for risk evaluation, investment choices, fraud identification, and adherence to regulations. Nevertheless, the swift advancement of studies in this area remains dispersed across various disciplines, hindering the ability to grasp its intellectual framework and developing frontiers. This research employs bibliometric methods to examine 151 publications listed in the Scopus database from 2015 to 2025 regarding AI and financial risk. The analysis utilizes the Bibliometrix package in R to explore trends in publications, patterns of authorship, significant sources, contributions from institutions, and networks of keyword co-occurrence. The findings indicate a robust increase in research production, with India, China, and the United States becoming the top contributors, whereas Australia and the United Kingdom excel in citation influence. Keyword clustering uncovers three main thematic paths: (i) quantitative finance and risk modeling utilizing AI and machine learning, (ii) FinTech and digital transformation, and (iii) governance, regulation, and compliance of AI. The results emphasize the interdisciplinary nature of the field and underline the importance of technological advancement and regulatory supervision for future progress. This research aids in charting the developing knowledge framework of AI in financial risk, providing direction for researchers, professionals, and policymakers in maneuvering through a progressively AI-oriented financial environment.

ABSTRACT This study maps how Artificial Intelligence is theorized and implemented within Health Information Systems from a management perspective. Using the Web of Science Core Collection, we analyze 323 English-language articles and reviews published between 2020 and 2025 (book chapters and retracted items excluded). Performance indicators and science-mapping techniques—co-word, co-citation, and bibliographic coupling—were conducted in VOSviewer. Results show rapid growth after 2020 and sustained scholarly visibility. The field is built on three pillars: data and system foundations enabling AI, including big data and governance; machine-learning decision support guided by workflow fit, explainability, fairness, and accountability; and AI deployment in electronic health records, accelerated by COVID-19 and formalized through product-management practices. Journal and publisher profiles concentrate in informatics and open-science venues, while country coupling reveals internationally integrated reference ecosystems. The study specifies the micro-foundations of AI capability, articulates governance for hybrid human–AI decisions, and frames the EHR as a platform for scalable analytics. We offer a reproducible protocol and a management-centered agenda for reliable, equitable, and governable AI in health systems.

ABSTRACT Digital technologies are increasingly becoming central to climate strategies and international development, and with that growth comes additional energy demand and material environmental footprints. As such, it is important to apply regulatory arrangements with accordingly robust governance responses. This paper outlines the international sustainability frameworks ISO standards, the EU Green Deal, UN Sustainable Development Goals and how national and regional governments are putting these ambitions into practice through command-and-control regulations, market-based approaches, and sectoral contexts. It also highlights Environmental, Social, and Governance (ESG) frameworks and corporate sustainability reporting in the digital space. It centers on the ethical implications of computing sustainability including environmental justice, data equity, and socio-spatial dimensions of digital infrastructure. By examining global policy examples, empirical work, and theories relating to justice, the essential gaps relating to implementation, accountability, and equitable access have been identified. Policy recommendations in supporting the improved governance of digital sustainability in national carbon accounting, circular procurement, and local-community-centered digital transitions have been given. Overall, this paper gives a multifaceted mapping of governance related to sustainable computing, while simultaneously calling for more inclusive, adaptive, and accountable policy frameworks.

ABSTRACT The digital transformation in African higher education necessitates the establishment of a digital culture. This paper examines the challenges faced by these institutions and evaluates their current digitalization status. The Fourth Industrial Revolution highlights the importance of comprehensive digital strategies beyond essential skill development. However, integrating these strategies into African higher education poses significant challenges. To remain competitive in the global digital education market, African higher education institutions must address these issues. Further research needs to examine whether digital transformation has an effect on educational accessibility within remote locations. Graduates need rapid advancement to enter a job market that focuses on digital skills effectively. The transformation can improve management systems, teaching methods, research practices, and infrastructure. Moreover, more studies are needed to understand its impact on digital competencies, particularly for students.

ABSTRACT This study examines Moroccan women entrepreneurs’ communication methods within digital markets and focuses on the cultural and technological barriers, along with gender-related challenges they face in digital business settings. The research utilizes quantitative surveys, qualitative interviews, and document analysis to examine Moroccan female entrepreneurs’ communication strategies in the digital economy, which remain culturally appropriate. The study shows that Moroccan women digital entrepreneurs successfully use multiple social media platforms for customer engagement, yet face difficulties achieving business targets because of cultural barriers. The analysis reveals technological skills, cultural sensitivity, and audience understanding deficiencies. Digital platforms create new opportunities for women to break through traditional barriers, but introduce specific challenges that demand culturally aware approaches for resolution. The study reveals the significance of digital business ventures led by women in emerging economies and offers recommendations to help policymakers develop better support systems for Moroccan female entrepreneurs.

ABSTRACT The aim of this study is to examine the application of the principles of risk management and intelligent management strategies in engineering projects to support long-term sustainability. It examines the environmental and social impacts of business operations, with special attention to optimizing resources’ use and alleviating their own risks. The research focuses on a case study in Jordan and uses analysis of documents to evaluate the performance of sustainability in the industrial sector. The study, by comparing operational data from 2020 to 2021, emphasizes the advantages of integrating approaches to the management of intelligence and risks in achieving sustainable industrial operations. It also identifies opportunities to improve existing sustainability procedures and offers recommendations that other organizations can carry out similar sustainable methodologies. Overall, this study provides valuable knowledge of effective harm risk management and intelligent management procedures to support environmentally responsible and durable industrial development.

Deep Learning (DL) applications in the Internet of Things (IoT) have garnered significant attention, with numerous studies exploring various models and implementations. Concurrently, the emerging field of the Internet of Behaviors (IoB) has captured broad interest, extending the capabilities of IoT through the synergy of DL. This transformative approach presents novel possibilities across diverse domains (e.g. healthcare, business, education, and insurance). In this survey, we uniquely contribute by elucidating the synergistic potential of integrating IoB with DL. Our literature review provides a state-of-the-art analysis of DL implementations within the IoB ecosystem, highlighting architectures, features, and advantages over traditional machine learning methods. Through a meticulous examination of findings, we reveal specific insights gained from the survey, and we discuss issues, challenges, and future research directions in applying DL in IoB applications. Our survey stands as a testament to achievements in this dynamic intersection and serves as a call to action for exploring uncharted territories.

This study presents a comprehensive learning analytics system designed behind machine learning to analyze student data collected from the Moodle Learning Management System (LMS) of the University of Sultan Moulay Slimane. The system in the said university connects to Moodle’s API to extract data, which are student information, engagement metrics, and performance data; this data is then processed to visualize trends and build predictive models to help this learning process. The researchers have implemented several machine learning algorithms like Random Forest and Support Vector Machines (SVM) to create the model for identifying at-risk students early in their academic process. Afterward, the researchers optimized the Random Forest Model, which achieved 85% accuracy in predicting student results, with engagement metrics being the most predictive features. The proposed system is a proposition for educational data mining to support timely interventions and improve student retention and success rates.

Artificial intelligence (AI) in healthcare analytics represents a transformative force with the potential to revolutionize clinical decision-making, operational efficiency, and patient-centered care. While its applications in precision medicine, predictive modeling, and administrative optimization are promising, the integration of AI also raises critical ethical, governance, and trust-related concerns. This paper explores the evolution, use cases, and associated challenges of AI in healthcare analytics, emphasizing the dual-use nature of these technologies. Drawing on agency theory and moral responsibility theory, the study highlights the shared responsibilities of developers, healthcare institutions, regulators, and patients in ensuring equitable, transparent, and accountable AI deployment. It proposes a multi-pronged strategy combining technical safeguards, regulatory oversight, and ethical capacity-building to align AI innovation with public interest. Through this comprehensive analysis, the paper offers guidance for ethically sustainable integration of AI in healthcare systems while preserving human dignity and social trust.