https://inter-publishing.com/index.php/ijbde <div> <p style="text-align: justify;"><strong>International Journal of Business Diplomacy and Economy</strong> (IJBDE) - ISSN <a href="https://portal.issn.org/resource/ISSN/2833-7468" target="_blank" rel="noopener">2833-7468</a> is an international journal devoted entirely to fostering/understanding issues interconnecting diplomacy and economy. Journal collaborates and seeks with economic-related issues, economic diplomacy was/is often neglected. There have been huge changes in the field of diplomacy (globalization, regionalization, internet, social networks, new entrants in the international fields, e.g. NGOs, MNCs, etc.), belying the stereotype that diplomacy is old-fashioned. One constant has always been at the core of diplomacy – economy.</p> </div> en-US [email protected] (Editor In Chief) [email protected] (Managing Editor) Tue, 12 Mar 2024 03:55:12 +0000 OJS 3.3.0.15 http://blogs.law.harvard.edu/tech/rss 60 https://inter-publishing.com/index.php/ijbde/article/view/3471 <p>The study delves into the application of data science and emerging technologies in the detection and surveillance of counterfeit currency, a burgeoning challenge with significant implications for the global financial system. With counterfeiters employing increasingly sophisticated methods to circumvent traditional detection mechanisms, this research emphasizes the integration of advanced data analytics, machine learning models, and pattern recognition algorithms to enhance the efficacy of counterfeit detection operations. Utilizing a comprehensive dataset derived from financial transactions, law enforcement reports, and social media analytics, the study showcases the superiority of data-driven approaches over conventional methods in identifying and mitigating the circulation of counterfeit notes. Through a detailed examination of the methodologies employed, including data preprocessing and the application of machine learning techniques, this research highlights key findings that demonstrate the potential of technologies such as blockchain and AI in revolutionizing the fight against counterfeit currency. The study also discusses the implications of these findings for policymakers, financial institutions, and law enforcement agencies, underscoring the importance of collaboration, technological innovation, and the exploration of new data sources. Furthermore, the research addresses the challenges and limitations encountered, including data accessibility and ethical considerations, while proposing areas for future investigation to overcome these hurdles and advance the field of counterfeit currency detection. This study contributes to the development of more sophisticated, efficient, and adaptive surveillance and detection systems, offering a promising outlook for enhancing the integrity of global financial systems in the face of evolving counterfeiting threats.</p> Md Sajadul Alam, Sazzad Hossain, Anjuman Ara, Abu Shaker Copyright (c) 2024 Md Sajadul Alam, Sazzad Hossain, Anjuman Ara, Abu Shaker https://creativecommons.org/licenses/by/4.0 https://inter-publishing.com/index.php/ijbde/article/view/3471 Wed, 13 Mar 2024 00:00:00 +0000 https://inter-publishing.com/index.php/ijbde/article/view/3472 <p>This paper explores the integration of predictive analytics into strategic workforce planning, highlighting the transformative impact of artificial intelligence (AI) and machine learning advancements. With a focus on the energy and telecommunications sectors, the study examines the incorporation of predictive models into HR systems and processes, underlining the strategic benefits for long-term business planning. The evolving nature of work, including remote work paradigms and the gig economy, underscores the necessity for adaptable workforce strategies. The research anticipates a significant role for predictive analytics in shaping future organizational competencies and competitive advantages across various industries. The study concludes with the potential for cross-industry application of predictive analytics, suggesting an expansive future for data-driven strategic planning in navigating the complexities of the modern workforce.</p> Md Atiqur Rahaman, Md Hasanujamman Bari Copyright (c) 2024 Md Atiqur Rahaman, Md Hasanujamman Bari https://creativecommons.org/licenses/by/4.0 https://inter-publishing.com/index.php/ijbde/article/view/3472 Wed, 13 Mar 2024 00:00:00 +0000