The COVID-19 pandemic has fundamentally transformed the global education landscape, compelling institutions to adopt e-learning as an essential tool to sustain academic activities. This research examines the critical impact of e-learning on arts and science college students in Coimbatore, with an emphasis on its influence on their readiness for campus recruitment. Using a survey of 300 students, this study investigates their perceptions of online education, highlighting both its advantages, such as flexibility and accessibility, and its challenges, including engagement barriers and technical limitations. Data was collected through structured questionnaires and analyzed using statistical methods to draw meaningful insights. The research also explores the efficacy of online assessments in recruitment processes and assesses students’ awareness of available e-learning platforms and courses. The urgency of this study lies in addressing the pressing need to optimize digital education models as institutions globally transition toward blended learning post-pandemic. The findings underline the dual potential and limitations of e-learning, concluding with actionable recommendations to enhance its effectiveness, particularly in preparing students for competitive employment opportunities.

Credit risk assessment is one of the most important aspects of financial decision-making processes. This study presents a systematic review of the literature on the application of Artificial Intelligence (AI) and Machine Learning (ML) techniques in credit risk assessment, offering insights into methodologies, outcomes, and prevalent analysis techniques. Covering studies from diverse regions and countries, the review focuses on AI/ML-based credit risk assessment from consumer and corporate perspectives. Employing the PRISMA framework, Antecedents, Decisions, and Outcomes (ADO) framework and stringent inclusion criteria, the review analyses geographic focus, methodologies, results, and analytical techniques. It examines a wide array of datasets and approaches, from traditional statistical methods to advanced AI/ML and deep learning techniques, emphasizing their impact on improving lending practices and ensuring fairness for borrowers. The discussion section critically evaluates the contributions and limitations of existing research papers, providing novel insights and comprehensive coverage. This review highlights the international scope of research in this field, with contributions from various countries providing diverse perspectives. This systematic review enhances understanding of the evolving landscape of credit risk assessment and offers valuable insights into the application, challenges, and opportunities of AI and ML in this critical financial domain. By comparing findings with existing survey papers, this review identifies novel insights and contributions, making it a valuable resource for researchers, practitioners, and policymakers in the financial industry.

This study examines how Artificial Intelligence (AI) enhances Sharia compliance within Islamic Financial Institutions (IFIs) by improving operational efficiency, ensuring transparency, and addressing ethical and technical challenges. A quantitative survey across five Saudi regions resulted in 450 validated responses, analyzed using descriptive statistics, ANOVA, and regression models. The findings reveal that while AI significantly enhances transparency and compliance processes, its impact on operational efficiency is limited. Key barriers include high implementation costs, insufficient structured Sharia datasets, and integration complexities. Regional and professional differences further underscore the need for tailored adoption strategies. It introduces a novel framework integrating ethical governance, Sharia compliance, and operational scalability, addressing critical gaps in the literature. It offers actionable recommendations for AI adoption in Islamic finance and contributes to the global discourse on ethical AI practices. However, the Saudi-specific focus highlights regional dynamics that may limit broader applicability. Future research could extend these findings through cross-regional comparisons to validate and refine the proposed framework. By fostering transparency and ethical governance, AI integration aligns Islamic finance with socio-economic goals, enhancing stakeholder trust and financial inclusivity. The study emphasizes the need for targeted AI training, the development of structured Sharia datasets, and scalable solutions to overcome adoption challenges.

This contribution questions young people’s access to digital networks at the scale of intermediate cities in Saint-Louis. Thus, it analyzes the prescriptions of digital actors responsible for the development of digital economy in relation with the orientations of the Senegal Digital 2025 strategy. This is a pretex to highlight the gaps between official political discourses and the level of deployment of digital infrastructures. The study highlights the need to repoliticize the needs of populations for broadband and very high-speed connections to promote local initiatives for youth participation in Saint-Louis. Indeed, datas relating to access and use of the Internet by young people reveal inequalities linked to household income, the disparity of infrastructure and digital equipment, and the discontinuity in neighborhood development, but also to the adaptability of the internet service marketed. Through urban and explanatory sociology mobilized through the approach of young people’s real access to the Internet, our analyzes have shown at the scale of urban neighborhoods the impact of the actions recommended by those involved in the development of populations’ access to Internet. The result is that the majority of young people are forced to access the Internet through medium-speed mobile networks.

Management and efficiency have a fundamental impact on the performance of public hospitals, as well as on their philanthropic mission. Various studies have shown that the financial weaknesses of these entities affect the planning, setting of goals and objectives, monitoring, evaluation and feedback necessary to improve health systems and guarantee accessibility as an inalienable right. This study aims to analyze the management and efficiency of third-level and/or high-complexity hospitals in Colombia, through a statistical model that uses financial analysis and key performance indicators (KPIs) such as ROA, ROE and EBITDA. A non-experimental cross-sectional design is used, with an analytical-synthetic, documentary, exploratory and descriptive approach. The results show financial deficiencies in the hospitals evaluated; hence it is recommended to make adjustments in the operating cycle to increase efficiency rates. In addition, the use of the KPIs ROA and ROE under adjusted models is suggested for a more precise analysis of the financial ratios, since these adequately explain the variability of each indicator and are appropriate to evaluate hospital management and efficiency, but not in EBITDA ratio, hence the latter is not recommended to evaluate hospital efficiency reliably. This study provides relevant information for public health policy makers, hospital managers and researchers, in order to promote the efficiency and improvement of health services.

While extensive research has explored interconnectedness, volatility spillovers, and risk transmission across financial systems, the comparative dynamics between Islamic and conventional banks during crises, particularly in specific regions such as Saudi Arabia, are underexplored. This study investigates risk transmissions and contagion among banks operating in Islamic and conventional modes in the Kingdom of Saudi Arabia. Daily banking stock data spanning November 2018 to November 2023, encompassing two major crises—COVID-19 and the Russian-Ukraine war—were analyzed. Using the frequency TVP-VAR approach, the study reveals that average total connectedness for both banking groups exceeds 50%, with short-run risk transmission dominating over long-term effects. Graphical visualizations highlight time-varying connectedness, driven predominantly by short-run spillovers, with similar patterns observed in both Islamic and conventional banking networks. The main contribution of this paper is the insight that long-term investment strategies are crucial for mitigating potential risks in the Saudi banking system, given its limited diversification opportunities.