Fair East Publishers: E-Journals
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Integrating taxation, financial controls, and risk management: a comprehensive model for small and medium enterprises to foster economic resilience
Get PDFSmall and Medium Enterprises (SMEs) are vital contributors to economic growth, job creation, and innovation, yet they face persistent challenges in maintaining resilience amidst dynamic and uncertain environments. This paper proposes an integrated model that combines taxation, financial controls, and risk management as a comprehensive framework to enhance SME resilience. Theoretical insights are provided on the interdependencies of these elements, highlighting how their integration can optimize resource utilization, ensure regulatory compliance, and mitigate risks. Practical applications of the model are explored, emphasizing its scalability and adaptability to diverse economic contexts. The role of government policies, private sector initiatives, and technological advancements in supporting SMEs is discussed, with actionable recommendations for stakeholders to facilitate implementation. By adopting this holistic approach, SMEs can achieve operational efficiency, financial stability, and long-term sustainability, ultimately strengthening their contributions to global economic resilience.
Keywords: SME Resilience, Tax Compliance, Financial Controls, Risk Management, Economic Sustainability, Integrated Model
Advancing real-time decision-making frameworks using interactive dashboards for crisis and emergency management
Get PDFEffective crisis and emergency management heavily relies on timely and accurate decision-making to mitigate impacts and ensure public safety. Traditional decision-making processes often struggle with the rapid flow of information and the need for real-time responses. This paper explores the potential of interactive dashboards in advancing real-time decision-making frameworks, emphasizing their role in crisis and emergency management. Interactive dashboards, powered by advanced data analytics, provide a centralized platform for visualizing complex data streams, enabling decision-makers to quickly assess critical situations. These dashboards integrate real-time data from various sources, including social media, sensor networks, and emergency response systems, offering a comprehensive view of ongoing incidents. The study highlights the benefits of interactive dashboards in enhancing situational awareness, improving resource allocation, and streamlining communication during emergencies. Through intuitive visualizations, decision-makers can rapidly identify hotspots, track resource deployment, and evaluate the effectiveness of response strategies. Furthermore, the integration of predictive analytics within these dashboards allows for proactive decision-making, anticipating potential developments and facilitating preventative measures. The paper also examines key challenges in implementing interactive dashboards, such as data integration complexities, the need for real-time data processing, and user adaptability. It discusses strategies for overcoming these challenges, including the use of cloud computing, machine learning algorithms, and scalable data architectures. Case studies from disaster response operations demonstrate the practical applications and impact of interactive dashboards, showing how they can significantly improve decision-making speed and accuracy. In conclusion, interactive dashboards represent a powerful tool for advancing real-time decision-making in crisis and emergency management. By consolidating diverse data sources and enabling dynamic, actionable insights, they support more effective responses to crises, reduce risks, and save lives. This paper advocates for the broader adoption of interactive dashboard technologies to enhance crisis preparedness and response frameworks..
Keywords: Real-Time Decision-Making, Interactive Dashboards, Crisis Management, Emergency Response, Situational Awareness, Predictive Analytics, Data Integration, Decision Support Systems, Resource Allocation, Cloud Computing
Digital transformation in public sector services: Enhancing productivity and accountability through scalable software solutions
Get PDFDigital transformation in public sector services is crucial for enhancing productivity and accountability, ensuring efficient service delivery to citizens. This process involves integrating scalable software solutions that streamline operations, improve data management, and facilitate communication among various stakeholders. Key areas of focus include cloud computing, data analytics, and automation technologies, which empower public agencies to optimize workflows and respond promptly to citizen needs. Cloud computing offers the flexibility and scalability necessary for managing large volumes of data and applications, enabling real-time access to information. By leveraging data analytics, public sector organizations can gain insights into service usage patterns, citizen feedback, and operational efficiency, allowing for data-driven decision-making. Furthermore, automation technologies, including robotic process automation (RPA), can significantly reduce manual tasks, freeing up resources for more strategic initiatives. Implementing scalable software solutions not only enhances productivity but also fosters greater transparency and accountability within public sector services. These solutions facilitate tracking and reporting mechanisms, enabling stakeholders to monitor performance metrics and service outcomes. Citizens benefit from improved access to information and services, leading to increased trust in government institutions. Moreover, digital transformation in the public sector encourages collaboration among agencies through integrated platforms that share data and resources. This collaborative approach promotes inter-agency partnerships and enhances the effectiveness of service delivery, ensuring that public sector organizations can address complex societal challenges more effectively. Challenges such as resistance to change, cybersecurity risks, and the need for continuous training must be addressed to maximize the benefits of digital transformation. Developing a culture of innovation and adaptability within public sector organizations is essential for overcoming these barriers and ensuring the successful implementation of scalable software solutions. In conclusion, embracing digital transformation through scalable software solutions positions public sector services to enhance productivity, accountability, and citizen engagement. This strategic shift not only improves operational efficiency but also reinforces the role of government as a responsive and accountable entity in the digital age.
Keywords: Digital Transformation, Public Sector Services, Productivity, Accountability, Scalable Software Solutions, Cloud Computing, Data Analytics, Automation Technologies, Citizen Engagement
Examining intersectionality of social identities in Birim Central Municipality in the Eastern Region of Ghana
Get PDFThe aim of this current review is to provide a detailed analysis of literature on the intersectionality of social identities and their impact on family dynamics, relationships, and support systems in Birim Central Municipality, Eastern Region of Ghana. The objective of the research is to investigate how overlapping social identities such as gender, ethnicity, religion, and socioeconomic status shape the experiences of families within the municipality. Google scholar, Scopus (Elsevier) and Science Direct (Elsevier), were a few of the databases used for the review. The findings reveal that the intersection of social identities creates both challenges and opportunities for families. Gender roles, ethnic norms, religious beliefs, and economic conditions interact to influence household responsibilities, access to resources, and decision-making processes. Families from marginalized ethnic and socioeconomic groups often face greater obstacles in securing support, while traditional gender norms continue to shape household dynamics, especially in lower-income families. Religious beliefs also play a significant role in shaping family values and practices, contributing to both cohesion and tension in some households. In conclusion, the intersectionality of social identities plays a critical role in shaping family dynamics in Birim Central Municipality. Policies and programs aimed at supporting families must consider these overlapping factors to ensure equity and inclusivity. To support family cohesion and social fairness in the Birim Central Municipality, the study recommends focused interventions that cater for the unique needs of families impacted by the confluence of gender, ethnicity, religion, and socioeconomic position.
Keywords: Family Dynamics, Relationships and Support Systems, Social Identities
Leveraging technology and artificial intelligence to revolutionize French language proficiency: A comprehensive framework for modern curriculum design
Get PDFThe integration of technology and artificial intelligence (AI) in language education has the potential to revolutionize how French is taught and learned in the modern era. This paper explores a comprehensive framework for modernizing the French language curriculum, emphasizing the transformative role of AI-driven tools in enhancing learner engagement, accessibility, and fluency. It examines advancements such as adaptive learning systems, AI-powered tutors, speech recognition, and gamification, highlighting their ability to personalize instruction and foster immersive learning experiences. Key features of a technology-driven curriculum, including alignment with CEFR standards and inclusivity for diverse learners, are discussed. The paper also addresses challenges such as cost, infrastructure limitations, and ethical concerns related to data privacy and the role of human educators. Recommendations focus on teacher training, infrastructure investment, and collaborative policy development to ensure the successful implementation of AI-enhanced curricula. By leveraging AI's potential while maintaining ethical standards, this approach aims to make French language education more efficient, interactive, and inclusive, meeting the demands of a globalized world.
Keywords: Artificial Intelligence, French Language Education, Technology-Driven Curriculum, Adaptive Learning Systems, Immersive Learning, Educational Innovation
Advancing predictive analytics models for supply chain optimization in global trade systems
Get PDFGlobal trade systems are becoming increasingly complex due to interconnected markets, fluctuating demand, geopolitical uncertainties, and sustainability concerns. Predictive analytics offers transformative potential in optimizing supply chain operations by leveraging data-driven insights for proactive decision-making. This explores the advancements in predictive analytics models tailored for global trade systems, emphasizing their role in enhancing supply chain efficiency, resilience, and agility. By integrating machine learning algorithms, big data analytics, and real-time data feeds, these models enable accurate forecasting of demand, inventory levels, and transportation routes. Key innovations include the incorporation of artificial intelligence (AI) for pattern recognition, predictive maintenance of assets, and dynamic route optimization. The use of ensemble modeling and deep learning enhances the predictive accuracy, while adaptive algorithms accommodate evolving market trends and disruptions. The review also highlights the challenges of data silos, scalability, and model interpretability, which hinder the full potential of predictive analytics in global supply chains. Ethical considerations such as data privacy and fairness in AI-driven decision-making are addressed to ensure responsible model implementation. Case studies from various industries demonstrate how advanced predictive models mitigate risks, reduce costs, and improve sustainability by optimizing resource utilization and reducing carbon footprints. Emerging trends, such as the integration of blockchain for transparent data sharing and IoT for real-time monitoring, further enrich the predictive capabilities. This underscores the critical need for collaborative frameworks between stakeholders, continuous innovation, and investment in analytical capabilities to future-proof supply chains. By advancing predictive analytics, global trade systems can achieve a new paradigm of efficiency and resilience in a volatile and competitive landscape.
Keywords: Predictive Analytics, Models, Supply Chain Optimization, Global Trade Systems
Digital economic development in the context of globalization: Research in Vietnam
Get PDFThe Fourth Industrial Revolution marks a remarkable development in the use of data and technology in all activities of social life. The trend of digitalizing the economy and social activities is taking place very quickly in many countries. The digital economy has become an increasingly important contributor to the gross domestic product of countries, especially in the post-COVID-19 recovery process. The XIII Congress documents have set the target of the digital economy reaching 20% of GDP by 2025 and 30% by 2030. Vietnam's provinces and cities have also issued resolutions specifying the goals of digital transformation and digital economic development for their localities. Digital economic development is considered an optimal solution to realize the aspiration of developing a strong and prosperous Vietnam, becoming a developed country, following a socialist orientation. In recent times, our Party and State have had many policies and guidelines to encourage the development of the digital economy. Thanks to that, the digital economy has made impressive progress, making Vietnam the leading digital economy in the region. However, besides the achieved results, many problems are arising in the development of the digital economy in our country today..
Keywords: Development, Digital Economy, Globalizatio
Digital transformation in the energy sector: Comprehensive review of sustainability impacts and economic benefits
Get PDFThe energy sector is undergoing a profound transformation driven by the integration of digital technologies, which have become central to addressing sustainability challenges and unlocking economic opportunities. This review examines how digital transformation reshapes the energy industry, promoting sustainability through enhanced energy efficiency, renewable energy integration, carbon emission reductions, and circular economy practices. Technologies such as smart grids, IoT, blockchain, artificial intelligence, and digital twins are pivotal in achieving these objectives by enabling real-time monitoring, predictive analytics, and decentralized energy systems. From an economic perspective, digital transformation reduces operational costs, fosters market expansion, and empowers consumers through customized energy solutions and demand-side management. Emerging roles and upskilling initiatives within the energy workforce further contribute to economic growth. Case studies of successful implementations highlight best practices, including leveraging digital tools to optimize renewable energy production, streamline supply chains, and enhance energy distribution networks. However, the review also addresses barriers such as high implementation costs, cybersecurity risks, regulatory limitations, and organizational resistance to change. Overcoming these challenges requires strategic investments in digital infrastructure, policy support for innovation, and collaborative efforts between governments, energy companies, and technology providers. Future trends underscore the potential of emerging technologies like quantum computing, edge computing, and 5G to revolutionize energy systems further. Additionally, digital tools are identified as critical enablers in achieving global decarbonization goals and supporting net-zero initiatives. This review provides a comprehensive analysis of the sustainability impacts and economic benefits of digital transformation in the energy sector, offering actionable recommendations for stakeholders to leverage digital innovation as a catalyst for resilient, efficient, and sustainable energy systems.
Keywords: Digital Transformation, Energy Sector, Sustainability Impacts Economic Benefits
Developing inventory optimization frameworks to minimize economic loss in supply chain management
Get PDFInventory optimization is pivotal in mitigating economic losses and enhancing efficiency in supply chain management. This paper examines the challenges associated with traditional inventory practices, including inefficiencies, demand variability, and supply chain disruptions, which lead to substantial financial and operational setbacks. Building on theoretical foundations and insights from existing research, a comprehensive inventory optimization framework is proposed, integrating advanced technologies such as Artificial Intelligence (AI), the Internet of Things (IoT), and cloud-based systems. The framework emphasizes data-driven decision-making, real-time tracking, lean inventory management, and sustainability, offering scalable solutions for diverse industries. Practical recommendations for implementation include investments in advanced technologies, collaborative supply chain practices, and continuous performance monitoring. The proposed framework aims to reduce costs, improve operational resilience, and align inventory management with broader economic and environmental goals. By adopting this innovative approach, organizations can navigate the complexities of modern supply chains and achieve long-term success..
Keywords: Inventory Optimization, Supply Chain Management, Economic Losses, Advanced Technologies, Lean Inventory, Sustainability
Optimizing traffic management for public services during high-demand periods using cloud load balancers
Get PDFIn times of high demand, effective traffic management is essential for public service platforms to maintain reliable, continuous access for users. This paper explores the role of cloud load balancers as a solution for optimizing traffic distribution in public services during peak periods. By dynamically distributing network traffic across multiple servers, cloud load balancers enhance system scalability, flexibility, and response time, which are critical for minimizing service disruptions. The paper further discusses best practices for configuring load balancers, including geographic balancing and redundancy, and highlights the importance of integrating dynamic scaling and monitoring tools to adapt to sudden traffic surges. Additionally, the potential of artificial intelligence (AI) and predictive analytics in advancing cloud load balancing is considered, emphasizing their value for predictive scaling and automated traffic management. Key challenges, including data privacy and dependency on third-party infrastructure, are also addressed, with recommendations for enhancing load balancer deployment in public service applications. This paper concludes with strategic recommendations for public service providers to leverage cloud technology effectively, ensuring improved reliability, security, and cost-efficiency in service delivery.
Keywords: Cloud Load Balancers, Traffic Management, Public Service Platforms, Dynamic Scaling, Predictive Analytics, Service Reliability