Fair East Publishers: E-Journals
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Multi-factor forex hedging models: Merging geopolitical news and macroeconomic signals with reinforcement learning
No full textForex markets are influenced by an intricate interrelation of macroeconomic factors, global events, and market sentiment, and therefore successful hedging is a challenging activity. Traditional hedging models depend primarily on econometric and statistical approaches, which are likely unable to react rapidly to sudden shifts in the Forex market caused by global events. This study presents a multi-factor Forex hedging model that combines real-time sentiment analysis of geopolitical news and macroeconomic indicators and reinforcement learning (RL) in order to enhance decision-making and risk management. Our approach applies natural language processing (NLP) to quantify the sentiment of social media headlines and geopolitics news and translate unstructured data into structured trading signals. This sentiment data is combined with fundamental macroeconomic drivers such as interest rate differentials, inflation trends, trade balances, and central bank policy to construct an enhanced risk assessment framework. Deep Q-learning and policy-gradient methods of reinforcement learning are used to dynamically optimize hedging strategies based on learning from previous data and adapting to new market conditions in real time. The model is trained with historical Forex price action, macroeconomic news releases, and geopolitical news events to learn an adaptive hedging strategy capable of limiting downside risk while maintaining profitability. Empirical testing on major currency pairs indicates that the proposed approach outperforms conventional hedging approaches in minimizing drawdowns and improving portfolio stability. The findings look toward the potential of AI-powered adaptive hedging in volatile foreign exchange markets to give financial institutions and traders an effective tool in coping with the risk of currency exposure in an increasingly uncertain international setting.
Keywords: Forex markets, Hedging strategies, Macroeconomic factors, Global events, Market sentiment, Sentiment analysis, Reinforcement learning (RL), Natural language processing (NLP)
AI-Enhanced Knowledge Management Systems: A Framework for Improving Enterprise Search and Workflow Automation through NLP and TensorFlow
No full textIn the era of digital transformation, organizations are increasingly adopting artificial intelligence (AI) to enhance knowledge management systems (KMS) and gain a competitive edge. This paper proposes a novel framework for AI-enhanced knowledge management that leverages Natural Language Processing (NLP) and TensorFlow to improve enterprise search capabilities and workflow automation. Traditional KMS often struggle with unstructured data, inefficient information retrieval, and fragmented workflows, leading to reduced productivity and decision-making inefficiencies. By integrating advanced NLP algorithms with TensorFlow’s scalable machine learning capabilities, the proposed framework addresses these challenges through intelligent content classification, semantic search, and automated knowledge extraction. The framework begins with data ingestion from diverse sources, including emails, reports, and databases, which are processed using NLP techniques such as named entity recognition, sentiment analysis, and topic modeling. TensorFlow models are then employed to train and fine-tune neural networks for document classification and intent recognition, enabling contextual understanding and prioritization of enterprise content. The system supports a dynamic knowledge graph that interlinks related concepts, documents, and workflows, facilitating real-time, query-responsive search and content recommendation. Moreover, the framework incorporates workflow automation by integrating AI models that identify repetitive tasks and suggest optimized processes using predictive analytics. This reduces manual effort, enhances task routing, and supports intelligent alerts and decision support mechanisms. A case study in a mid-sized enterprise demonstrates a 35% improvement in knowledge retrieval time and a 28% reduction in workflow execution delays after implementation. The proposed AI-enhanced KMS offers a scalable, adaptive solution for managing organizational knowledge in real-time, thus supporting knowledge workers with timely, relevant, and context-aware insights. It emphasizes the role of NLP for linguistic comprehension and TensorFlow for deep learning-based model optimization, providing a robust foundation for future enterprise intelligence systems. The research contributes to the growing field of AI in enterprise settings, highlighting the potential of integrated technologies to redefine knowledge access and operational efficiency.
Keywords: Artificial Intelligence, Knowledge Management Systems, Enterprise Search, Workflow Automation, Natural Language Processing, TensorFlow, Semantic Search, Knowledge Graph, Machine Learning, Information Retrieval
Strengthening regulatory compliance in the U.S. food industry to support health system resilience and public health preparedness
No full textFoodborne illnesses continue to pose a significant threat to public health in the United States, with regulatory lapses in food production and distribution contributing to widespread outbreaks that strain already burdened healthcare systems. Incidents involving E. coli, Listeria monocytogenes, and Salmonella have highlighted critical vulnerabilities in the nation’s food safety infrastructure, resulting in increased hospital admissions, emergency response activation, and disruption of healthcare services. These failures reveal the urgent need to reframe food safety not only as a regulatory concern but as a critical component of public health preparedness and health system resilience. This paper examines the cascading impact of regulatory non-compliance in the U.S. food industry on health system capacity, especially during outbreaks and emergencies. It analyzes systemic gaps in current compliance frameworks and identifies missed opportunities to mitigate preventable health crises through stronger regulatory mechanisms. Drawing on real-world case studies, we demonstrate how insufficient inspections, inconsistent enforcement, and a fragmented compliance ecosystem undermine both food security and public health readiness. To address these challenges, we propose a multi-pronged strategy to strengthen regulatory compliance through enhanced digital audits, predictive analytics, workforce training, and integration of real-time monitoring technologies. These tools not only improve risk forecasting and outbreak prevention but also contribute to the agility and responsiveness of health systems during crises. Furthermore, we present actionable policy recommendations for federal and state agencies, emphasizing the alignment of food regulatory functions with national public health preparedness goals. By modernizing food safety oversight and embedding it within the framework of public health resilience, the U.S. can more effectively safeguard communities, reduce economic disruptions, and build a future-ready health system capable of withstanding both biological threats and systemic shocks.
Keywords: Food Safety Surveillance, Public Health Integration, Risk Assessment, Regulatory Compliance
Unveiling the influence of family culture on sustainability of tourism businesses in Mahé Island, Seychelles
Get PDFThis study explores the impact of family culture on the long-term viability of tourism enterprises on Mahe Island in Seychelles. Using a descriptive survey research design, structured questionnaires were distributed to 253 owners/CEOs/managers. The data were analyzed using simple regression analysis guided by the sustainable family business theory. The findings reveal a significant positive relationship between family culture and sustainability of family owned tourism businesses, with family culture accounting for 35.8% of the variation in sustainability outcomes. This study concludes that family culture, which includes shared values, traditions, and interpersonal dynamics, significantly influences the various aspects of these businesses and their sustainability. It recommends that family owned tourism businesses strike a balance between preserving their unique cultural identity and adapting to evolving market demands while implementing strategies that foster a sense of legacy and intergenerational continuity. Future research could investigate how these businesses adjust their family cultures to meet changing market demands, and examine the influence of family culture on employee satisfaction and retention. Comparative studies across different cultural contexts and tourism sectors can further illuminate the role of family culture in shaping successful and sustainable tourism businesses.
Keywords: Family Culture, Sustainability, Family Owned Tourism Businesses, Entrepreneurial Succession and Resilience
The streaming-driven content evolution model: Impact of digital platforms on global film production
Get PDFThis paper explores the profound impact of streaming platforms on global film production, examining the ways in which digital platforms such as Netflix, Amazon Prime, and Disney+ have revolutionized content creation, distribution, and consumption. The study highlights the historical development of streaming services and their role in disrupting traditional distribution models, emphasizing the global reach and accessibility they offer. The research delves into the changing content production strategies, including shifts towards episodic series, short-form videos, and the integration of new technologies like artificial intelligence and virtual reality. Furthermore, the paper investigates the globalization of film production, focusing on the rise of cross-border collaborations, the trend of producing local content for global audiences, and the implications for regional film industries. Economic and cultural considerations are addressed, exploring how streaming platforms influence local industries' financial sustainability and global content's cultural diversity. The study concludes with a discussion of the challenges and limitations posed by streaming, including the over-reliance on data-driven decision-making and the potential homogenization of content. Finally, the paper offers predictions for future trends in the digital content landscape, including advancements in AI, immersive technologies, and shifts in audience behavior. This research underscores the transformative potential of streaming services while highlighting the complexities of balancing global reach with cultural authenticity.
Keywords: Streaming Platforms, Film Production, Globalization, Content Distribution, Cultural Diversity
Financial risk management strategies and their influence on organizational stability
Get PDFThis study investigates the influence of financial risk management strategies on organizational stability, aiming to understand how diverse risk mitigation practices contribute to sustaining firm performance amid economic uncertainties. Employing a systematic literature review methodology, the study analyzes peer-reviewed articles, institutional reports, and empirical research published between 2020 and 2025. Data sources were rigorously selected using defined inclusion and exclusion criteria, and findings were synthesized through a content analysis approach. The review identifies key financial risk management strategies such as hedging, diversification, enterprise risk management frameworks, and the integration of corporate governance and regulatory compliance as critical to enhancing organizational resilience. Technological innovations, including artificial intelligence and blockchain, are found to significantly improve risk identification, monitoring, and mitigation processes. The study also highlights challenges in implementing risk management frameworks, including cultural resistance, resource constraints, and regulatory complexities. Implications for practitioners emphasize the need for dynamic, technology-enabled, and culturally embedded risk management approaches, while policymakers are encouraged to foster regulatory environments that balance oversight with innovation. Limitations of the study include potential publication bias and the rapid evolution of risk technologies not fully captured in the literature. Future research directions call for sector-specific analyses, longitudinal studies on technological impacts, and deeper exploration of sustainability-related risks. The findings underscore the imperative for organizations to adopt integrated, adaptive financial risk management practices to ensure long-term stability and competitive advantage in an increasingly volatile global economy.
Keywords: Financial Risk Management, Organizational Stability, Enterprise Risk Management, Corporate Governance
Cross-functional models for integrating net-zero finance strategies into corporate governance
Get PDFThe integration of net-zero finance strategies into corporate governance frameworks represents a critical evolution in contemporary business practice, necessitating comprehensive cross-functional models that align environmental sustainability objectives with fiduciary responsibilities. This research examines the development and implementation of innovative governance structures that effectively incorporate climate finance considerations into corporate decision-making processes across diverse organizational functions. The study analyzes existing frameworks for net-zero financial integration, evaluating their effectiveness in driving sustainable corporate transformation while maintaining competitive advantage and stakeholder value creation. Through systematic examination of current practices and emerging trends, this research identifies key success factors and implementation challenges associated with cross-functional net-zero finance integration. The research methodology employs a comprehensive analytical framework combining quantitative assessment of organizational performance metrics with qualitative evaluation of governance effectiveness indicators. The study examines multiple case studies across various industry sectors to understand how different organizational structures adapt to net-zero finance requirements while maintaining operational efficiency. Key findings reveal that successful integration requires robust cross-functional collaboration mechanisms, sophisticated risk management frameworks, and adaptive governance structures capable of responding to evolving regulatory environments. The research demonstrates that organizations implementing comprehensive cross-functional net-zero finance models experience enhanced stakeholder confidence, improved access to sustainable capital markets, and strengthened competitive positioning in increasingly environmentally conscious market conditions. The analysis identifies several critical implementation barriers including organizational resistance to change, inadequate technical expertise, insufficient data management capabilities, and complex regulatory compliance requirements. However, organizations that successfully overcome these challenges through systematic implementation of cross-functional models demonstrate significant improvements in environmental performance metrics, financial efficiency, and stakeholder engagement effectiveness. The research concludes that effective net-zero finance integration requires fundamental restructuring of traditional governance hierarchies to enable seamless information flow and coordinated decision-making across all organizational levels. These findings contribute to the growing body of knowledge regarding sustainable corporate governance and provide practical guidance for organizations seeking to implement comprehensive net-zero finance strategies while maintaining operational excellence and competitive advantage in rapidly evolving business environments.
Keywords: Net-Zero Finance, Corporate Governance, Cross-Functional Integration, Sustainability Frameworks, Climate Finance, Esg Governance, Sustainable Investment, Environmental Risk Management
Sustainable low-carbon cement technologies for reducing U.S. construction carbon emissions
Get PDFThe manufacturing of Portland cement is carbon-intensive, making the cement and construction sectors in the United States major contributors to the country's greenhouse gas emissions. This review methodically assesses new sustainable low-carbon cement solutions that lower construction-related emissions without sacrificing performance. Among the key technologies analyzed are supplementary cementitious materials (SCMs), carbon capture and utilization (CCU) strategies, process optimization techniques, and alternative cement chemistries like calcium sulfoaluminate (CSA), Limestone Calcined Clay Cement (LC³), magnesium-based binders, and alkali-activated materials (geopolymers). According to comparative analysis of performance and durability, several of these substitutes provide mechanical properties, chemical resistance, and long-term durability that are on par with or better than those of traditional systems. Global best practices and successful case studies from American infrastructure show that large-scale deployment is feasible. However, to achieve widespread adoption, this review recommends that targeted research investments, long-term durability validation, updated regulatory standards, coordinated pilot projects, and robust workforce training is required
Keywords: Low-Carbon Cement, Cement Decarbonization, Geopolymers, Supplementary Cementitious Materials, Calcium Sulfoaluminate Cement, Carbon Capture And Utilization, Concrete Durability
Exploring the emerging technologies for inclusive growth in Africa
Get PDFEmerging technologies, including Artificial Intelligence (AI), blockchain, and the Internet of Things (IoT), hold transformative potential for Africa’s socio-economic development. Countries such as Kenya, Nigeria, South Africa, and Namibia are integrating these innovations into agriculture, finance, healthcare, education, and governance. However, adoption faces persistent barriers, including inadequate digital infrastructure, low digital literacy, skills shortages, high costs, and regulatory gaps. Despite these challenges, Africa has a unique opportunity to leapfrog traditional development pathways by implementing forward-looking policies, investing in human capital, and fostering public-private collaborations. This article analyses the current state of emerging technology adoption in select African nations, identifies key obstacles, and proposes strategic recommendations to harness these technologies for inclusive and sustainable growth.
Keywords: Artificial Intelligence (AI), Internet of Things (IoT), Emerging Technologies, Digital Transformation, Africa
Architecting scalable data pipelines for learning analytics in higher education: A cloud-native approach
Get PDFThis research presents a cloud-native architecture for architecting scalable, secure, and real-time data pipelines tailored to learning analytics in higher education. With a focus on modernising data workflows from legacy Student Information Systems (SIS) like PeopleSoft, the proposed pipeline leverages Oracle GoldenGate’s log-based Change Data Capture (CDC) capabilities and the Databricks Lakehouse platform to facilitate continuous data ingestion, transformation, and analytical readiness. A novel institutional deployment is demonstrated in which GoldenGate streams transactional data directly to Delta Lake without reliance on traditional staging zones, thereby reducing latency and complexity. Structured around Silver and Gold layers, the pipeline enables real-time data refinement and advanced transformation using PySpark and SQL, ensuring that institutional users have access to curated, analytics-ready data assets. The architecture integrates governance frameworks, observability tooling, and privacy-preserving features, supporting compliance with FERPA and GDPR. Anticipated outcomes include improved ingestion performance, elastic scalability via Databricks’ autoscaling Spark clusters, robust data lineage, and enhanced institutional agility in analytics-driven decision-making. This work contributes a replicable blueprint for higher education institutions seeking to modernise their data infrastructure for scalable learning analytics, real-time interventions, and regulatory resilience.
Keywords: Learning, Pipeline, Analytics