Fair East Publishers: E-Journals
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Designing comprehensive workforce safety frameworks for high-risk environments: A strategic approach
No full textHigh-risk industries such as oil and gas, construction, and manufacturing face significant challenges in safeguarding their workforce due to the inherent dangers of their operations. This paper presents a strategic approach to designing comprehensive workforce safety frameworks that address both personal and process safety. Personal safety focuses on the use of personal protective equipment (PPE), behavior-based safety programs, and training, while process safety aims to manage operational risks such as equipment malfunctions and hazardous materials. The interdependency of these two safety pillars is essential in reducing workplace accidents and ensuring a safer operational environment. Challenges in implementing safety frameworks, such as complex operations, human factors, and technological and regulatory barriers, are also discussed. To overcome these challenges, the paper proposes a series of strategic solutions, including risk assessment, technology integration, continuous improvement, and stakeholder collaboration. By adopting these recommendations, industries can develop customized safety frameworks that protect their workforce and enhance operational efficiency.
Keywords: High-Risk Industries, Workforce Safety, Personal Safety, Process Safety, Risk Assessment, Safety Frameworks
The intersection of green marketing and sustainable supply chain practices in FMCG SMEs
No full textAs sustainability increasingly shapes consumer behavior and corporate strategies, Fast-Moving Consumer Goods (FMCG) small and medium-sized enterprises (SMEs) are adopting green marketing and sustainable supply chain practices to gain a competitive edge. This review explores the intersection of these two critical areas, demonstrating how their integration can drive both business growth and environmental responsibility. Green marketing, which focuses on promoting eco-friendly products and sustainable business practices, has become a key tool for FMCG SMEs to differentiate themselves in a crowded marketplace. By adopting strategies such as eco-friendly packaging, ethical sourcing, and transparency in communicating sustainability efforts, SMEs can build stronger consumer trust, foster brand loyalty, and meet the growing demand for environmentally conscious products. Simultaneously, sustainable supply chain practices ensure that the production, distribution, and logistics processes align with environmental and social goals. These practices include reducing carbon emissions, minimizing waste, and working closely with suppliers to ensure ethical sourcing of materials. The synergy between green marketing and sustainable supply chains creates a feedback loop where operational sustainability supports marketing efforts, and consumer demand for green products encourages further sustainability improvements. This review also examines the challenges FMCG SMEs face in aligning these strategies, such as cost barriers, regulatory compliance, and supply chain complexity. Through case studies and industry examples, it highlights how innovative technology and stakeholder collaboration can help overcome these challenges. Ultimately, this study underscores that integrating green marketing and sustainable supply chain practices is not only essential for addressing environmental concerns but also for enhancing competitive positioning, customer satisfaction, and long-term market success in the FMCG sector. Recommendations for SMEs on how to effectively align their marketing and supply chain sustainability efforts are also provided.
Keywords: Green Marketing, Supply Chain, FMCG SMEs, Review
A model for VAT standardization in Nigeria: Enhancing collection and compliance
No full textThis paper explores a proposed model for the standardization of Value-Added Tax (VAT) in Nigeria, aiming to enhance both collection efficiency and compliance. VAT is a significant revenue source for Nigeria; however, inefficiencies in its collection and compliance present challenges to economic development. The study addresses these issues by proposing a comprehensive model that integrates global best practices with local context. The proposed model includes the uniform application of VAT rates across sectors, standardized invoicing and documentation procedures, and the adoption of advanced technological solutions for VAT monitoring and reporting. By standardizing VAT procedures and leveraging technology, the model seeks to reduce discrepancies and errors, streamline compliance, and enhance transparency. The methodology involves a thorough review of existing literature, comparative analysis of VAT systems in other countries, and case studies of past VAT standardization attempts in Nigeria. The study uses qualitative and quantitative data to evaluate the effectiveness of the proposed model and its potential impact on VAT collection and compliance. The findings indicate that implementing the model could significantly improve VAT collection efficiency and compliance rates, contributing to a more robust and transparent tax system. The paper concludes with recommendations for policymakers on adopting and refining the proposed model, along with suggestions for further research to address ongoing challenges in VAT administration.
Keywords: Model, VAT, Standardization, Nigeria, Enhancing Collection, Compliance
Difficulties in the application of activity-based costing method in businesses in Vietnam
No full textThe ABC method improves upon the traditional costing (TDC) method, but its implementation presents significant challenges for manufacturing cost accountants in Vietnam, necessitating an investigation to identify practical solutions. To achieve this objective, the study was conducted with the participation of 106 participants, including accountants, chief accountants, and business managers from various enterprises in Binh Duong province, Vietnam. The findings show that the ABC method brings many limitations to its implementation. In particular, Vietnamese enterprises encounter several significant challenges in implementing the ABC method. A major obstacle is the lack of human resources with in-depth expertise. Additionally, many businesses, particularly small and medium-sized enterprises, face substantial initial investment costs for staff training, software acquisition, and information management system enhancements. In addition, collecting and managing detailed data on activities and costs is also challenging due to the absence of standardized information management processes. Moreover, fluctuations and market risks in the developing Vietnamese economy can affect cost forecasting and planning, further reducing the effectiveness of the ABC method. The method also requires continuous data updates and detailed activity analysis, which can be complicated and time-consuming, particularly for businesses with complex processes. Furthermore, some enterprises are resistant to change, favoring traditional cost management methods and failing to recognize the benefits of the ABC method, leading to suboptimal implementation. To overcome these challenges, businesses must prepare by training staff, investing in technology, and securing leadership support for effective ABC implementation.
Keywords: Difficulty, Activity-Based Costing Method, Businesses, Vietna
Advancing AML tactical approaches with data analytics: Transformative strategies for improving regulatory compliance in banks
No full textThe growing complexity of financial crimes necessitates advanced Anti-Money Laundering (AML) strategies that leverage data analytics to improve regulatory compliance in banks. As traditional AML methods face challenges in detecting sophisticated money laundering schemes, data analytics offers transformative solutions by enabling real-time monitoring, enhanced risk detection, and predictive analysis. This review explores the integration of data analytics in AML systems and its impact on regulatory compliance, focusing on strategies that banks can adopt to mitigate risks and adhere to evolving regulations. Data analytics empowers financial institutions to analyze vast amounts of transactional data, identifying suspicious patterns and anomalies with greater precision. Machine learning algorithms and artificial intelligence (AI) further enhance these capabilities by automating risk assessments, reducing false positives, and improving decision-making processes. Through predictive analytics, banks can anticipate emerging threats, adapting their AML strategies proactively to counter new money laundering techniques. A key advantage of data-driven AML approaches is the ability to streamline compliance processes. By automating Know Your Customer (KYC) procedures and cross-referencing data from multiple sources, banks can efficiently verify customer identities and monitor for unusual behavior. Additionally, the adoption of data analytics improves reporting accuracy, ensuring compliance with stringent regulatory frameworks such as the Financial Action Task Force (FATF) and the Bank Secrecy Act (BSA). This review highlights the transformative role of data analytics in enhancing AML efforts, emphasizing the importance of real-time data integration, predictive modeling, and automation. The shift from reactive to proactive AML approaches not only strengthens regulatory compliance but also fosters a culture of vigilance and risk management within banks. As financial institutions continue to embrace digital transformation, leveraging data analytics for AML will be crucial in combating financial crimes and maintaining compliance in an increasingly complex regulatory environment.
Keywords: Anti-Money Laundering (AML), Data Analytics, Regulatory Compliance, Banks, Financial Crime, Machine Learning, Artificial Intelligence, Know Your Customer (KYC), Predictive Analytics, Risk Management
Leveraging AI for financial risk management in oil and gas safety investments.
No full textIn the oil and gas industry, managing financial risk associated with safety investments is critical, particularly in high-risk operations. This concept paper explores the potential of leveraging artificial intelligence (AI) tools to analyze safety data and inform financial decisions, thereby ensuring effective resource allocation towards risk reduction. The integration of AI into financial risk management can transform traditional approaches, enabling organizations to proactively address safety concerns while optimizing investment strategies. The proposed framework utilizes machine learning algorithms to analyze vast datasets from various sources, including historical safety incidents, operational performance metrics, and regulatory compliance reports. By identifying patterns and correlations within this data, AI can forecast potential risks and assess the effectiveness of existing safety measures. This predictive capability empowers decision-makers to allocate resources strategically, prioritizing investments in areas that significantly impact safety outcomes and operational resilience. Furthermore, AI tools facilitate scenario analysis, enabling organizations to evaluate the financial implications of different safety investment strategies. By simulating various risk scenarios and their potential impacts on financial performance, companies can make informed decisions that balance safety with cost efficiency. This approach not only enhances the financial viability of safety investments but also fosters a culture of proactive risk management within the organization. The paper also discusses the challenges and limitations of implementing AI in financial risk management, including data quality issues and the need for organizational change to adopt AI-driven methodologies. Additionally, ethical considerations surrounding AI decision-making processes are addressed, emphasizing the importance of transparency and accountability in utilizing AI for safety investments. In conclusion, leveraging AI for financial risk management in safety investments presents a transformative opportunity for the oil and gas sector. By harnessing the power of data-driven insights, companies can enhance their risk reduction strategies, ensuring the safety of operations while optimizing financial performance.
Keywords: AI, Financial Risk Management, Safety Investments, Oil and Gas, Predictive Analytics, Resource Allocation, Operational Resilience, Risk Reduction, Scenario Analysis
Harnessing data analytics for precision in HIVAIDS treatment, improving therapy distribution and patient monitoring
Get PDFThis paper explores the transformative role of data analytics in enhancing HIV/AIDS treatment, focusing on patient monitoring, optimizing therapy distribution, reducing medication errors, and improving treatment adherence. By harnessing real-time data from electronic health records, wearable devices, and predictive analytics, healthcare providers can personalize treatment plans, ensure timely antiretroviral therapy (ART) delivery, and mitigate risks related to non-adherence and medication errors. The paper also examines the broader global implications of data-driven HIV/AIDS care, highlighting future technologies such as artificial intelligence and machine learning that promise to further improve treatment precision. Ethical considerations, including data privacy and algorithmic bias, are also discussed to underscore the importance of equitable and secure healthcare delivery for HIV/AIDS patients.
Keywords: HIV/AIDS, Data Analytics, Antiretroviral Therapy (Art), Patient Monitoring, Treatment Adherence, Precision Medicin
Using Fintech innovations for predictive financial modeling in multi-cloud environments
No full textThis paper explores integrating fintech innovations and multi-cloud environments in predictive financial modeling. Fintech advancements, such as artificial intelligence, machine learning, and blockchain, drive significant improvements in financial forecasting, risk assessment, and decision-making. Meanwhile, multi-cloud architectures provide the flexibility, scalability, and resilience necessary to support these advanced fintech solutions. The paper discusses key technologies, challenges, and opportunities associated with integrating fintech in multi-cloud environments and examines future trends that could shape the financial services industry. Strategic implications for financial institutions are considered, highlighting the evolving role of fintech and multi-cloud in enhancing operational efficiency and competitiveness. By combining fintech with multi-cloud, financial institutions are better positioned to capitalize on real-time predictive analytics, ultimately transforming the future of financial services.
Keywords: Fintech Innovations, Predictive Financial Modelling, Multi-Cloud Environments, Artificial Intelligence, Financial Forecasting
Resolving cybersecurity disputes and protecting digital infrastructure With ADR
No full textThe increasing frequency and complexity of cybersecurity disputes pose significant challenges for organizations and governments alike. As cyber threats evolve, so does the necessity for effective conflict resolution mechanisms that can address the intricacies of digital infrastructure disputes. Alternative Dispute Resolution (ADR) strategies, including mediation, arbitration, and negotiation, offer innovative solutions to resolve cybersecurity conflicts efficiently and confidentially while minimizing disruption to critical operations. ADR mechanisms provide a framework for stakeholders to collaboratively address issues arising from data breaches, intellectual property theft, and contractual disputes related to cybersecurity services. Mediation, for example, enables affected parties to engage in constructive dialogue with the assistance of a neutral facilitator, fostering understanding and facilitating the development of tailored solutions. This approach is particularly beneficial in high-stakes situations where preserving relationships and reputations is paramount. Arbitration serves as another effective ADR strategy, allowing disputes to be resolved by an impartial third party with expertise in cybersecurity law and technology. This method offers a binding resolution that can expedite the enforcement of agreements and encourage compliance with cybersecurity standards. Furthermore, negotiation techniques can be utilized to establish clear protocols and responsibilities for cybersecurity practices, ultimately enhancing cooperation among stakeholders. However, the effectiveness of ADR in resolving cybersecurity disputes relies on the awareness and integration of legal and technological aspects into the process. Practitioners must be equipped with knowledge of cybersecurity frameworks, regulations, and best practices to navigate the complexities involved. Moreover, fostering a culture of collaboration and proactive communication among organizations can significantly reduce the occurrence of disputes and enhance overall digital security. This abstract emphasizes the role of ADR strategies in resolving cybersecurity disputes and protecting digital infrastructure. By leveraging these approaches, organizations can address conflicts efficiently while safeguarding sensitive information and maintaining operational integrity.
Keywords: Cybersecurity Disputes, Digital Infrastructure, Alternative Dispute Resolution (ADR), Mediation, Arbitration, Negotiation, Data Breaches, Conflict Resolution
Conceptual framework for optimizing client relationship management to enhance financial inclusion in developing economies
Get PDFFinancial inclusion is a critical driver of socio-economic development, particularly in developing economies where large population segments lack access to formal financial services. This paper proposes a conceptual framework for optimizing Client Relationship Management (CRM) to enhance financial inclusion, focusing on key pillars such as client segmentation, digital outreach, and feedback mechanisms. The framework integrates behavioral insights and localized strategies to address the unique challenges faced by underserved populations, including geographic inaccessibility, lack of trust, and limited financial literacy. By leveraging technology-driven CRM tools and community-based approaches, the framework aims to improve service delivery, foster trust, and empower clients to make informed financial decisions. The paper also outlines policy and operational recommendations, emphasizing the importance of stakeholder collaboration and an enabling regulatory environment for successful implementation. This holistic approach demonstrates how CRM can catalyze financial inclusion, contributing to poverty reduction, economic resilience, and equitable development.
Keywords: Financial Inclusion, Client Relationship Management (CRM), Digital Outreach, Behavioral Insights, Underserved Population