Sculpting Dynamic Intelligence in E-Commerce Vendor-Customer Relations with Advanced Big Data Analytics Integration

This study examines how sophisticated big data analytics may improve customization, engagement, and operational efficiency in e-commerce vendor-customer relationships. The study focuses on intelligent e-commerce systems using artificial intelligence, machine learning, and predictive analytics to enhance consumer experiences. The paper synthesizes literature on big data applications, problems, and possibilities in e-commerce using secondary data. Big data offers hyper-personalization, real-time client interaction, and operational improvements, but it also raises data privacy, algorithmic bias, and infrastructure scalability problems. The report also suggests that augmented reality, virtual reality, and blockchain will shape customer interaction. Policy implications call for stronger regulatory frameworks that balance innovation, ethics, privacy, and openness. To maximize big data\u27s potential, firms must invest in IT infrastructure, fill talent gaps, and promote ethical data use. This study concludes that data-driven tactics are crucial to creating intelligent and adaptable e-commerce connections, which affect digital market development, trust, and competitiveness

Resilient Supply Chains: Strategies for Managing Disruptions in a Globalized Economy

This paper investigates methods for creating robust supply chains in a worldwide economy in light of growing disruptions. The primary goals were to evaluate supply chain resilience through integrating sustainable practices, investigate the impact of new technology, and explore solutions for diversification. A thorough analysis of case studies and literature regarding methodology was carried out, emphasizing secondary data sources from government publications, business reports, and scholarly journals. Significant research indicates that diversifying suppliers, production sites, and logistical routes can reduce the risks associated with localized interruptions. Proactive risk management requires enhanced visibility, predictive analytics, and operational efficiency, which may be achieved by integrating technologies like AI, IoT, blockchain, and cloud computing. Furthermore, integrating sustainability through ethical, sustainable sourcing, and resource-efficient methods reduces environmental and societal dangers and improves brand reputation and economic viability. The policy implications emphasize the need for frameworks that foster technology innovation, sustainability, and stakeholder collaboration. By implementing these tactics and resolving related issues, companies can construct flexible supply networks to sustain operations and competitiveness amidst fluctuations in the worldwide market

Effective Change Management Strategies: Lessons Learned from Successful Organizational Transformations

The study looks into successful organizational transformations\u27 effective change management techniques to extract important lessons for directing following change projects. The study uses a qualitative methodology to examine several case studies and secondary data sources to find recurring themes and patterns in various transformation scenarios. Key conclusions emphasize how crucial it is for change initiatives to be driven by strategy alignment, stakeholder participation, adaptive leadership, effective communication, and ongoing evaluation. The policy implications highlight the need to develop leadership skills, support regulatory frameworks that encourage evidence-based change management approaches, and cultivate organizational cultures that are open to change. Organizations may handle complexity, spur innovation, and achieve sustainable growth in the face of uncertainty and change by incorporating these findings into their change management strategies. This study offers insightful advice for practitioners and policymakers looking to improve their capacity for change and prosper in today\u27s fast-paced business environment

Cybersecurity in International Trade Agreements: A New Paradigm for Economic Diplomacy

This research shows that cybersecurity in international trade agreements is essential to contemporary economic diplomacy. Cybersecurity is crucial for trade infrastructure, intellectual property, and digital supply chains as global commerce digitizes. This research evaluates how trade agreements might improve cybersecurity and digital commerce. The qualitative research uses secondary data to analyze trade agreements, including the USMCA and CPTPP, policy frameworks, and multilateral activities. Significant results show that cybersecurity is now a strategic concern in international commerce, with trade agreements assisting in standardization, collaboration, and confidence. The paper also highlights geopolitical conflicts, regulatory differences, and the digital divide as barriers to cybersecurity integration into trade frameworks. The policy implications underscore the need for collaborative global cybersecurity rules, capacity-building for underdeveloped states, and enforcement procedures in trade agreements to ensure their implementation. This study adds to the increasing information on cybersecurity and international commerce, providing policymakers with meaningful ideas to manage the digital economy and promote economic diplomacy

Implementing AI in SAP GTS for Symmetric Trade Analytics and Compliance

SAP Global Trade Services (GTS) uses AI to improve symmetric trade analytics and compliance management. The main goal is to examine how machine learning, natural language processing, and predictive analytics may enhance global trade compliance accuracy, flexibility, and efficiency. Secondary data, including peer-reviewed academic publications, industry reports, and case studies, is analyzed to assess SAP GTS AI integration. Significant results show that AI automates risk assessments, detects abnormalities, and adapts to real-time regulatory changes, improving compliance. AI\u27s symmetric trade analytics gives enterprises data-driven insights across numerous trade operations, boosting decision-making and lowering compliance risks. Data quality, model interpretability, and data security still hinder AI adoption. The paper emphasizes robust data governance frameworks, explainable AI models, and safe data management to address these restrictions. Regulatory organizations should adopt AI audits, transparency, and data protection norms to guarantee responsible AI usage in global trade compliance. SAP GTS may become a strategic, AI-powered tool that improves trade efficiency, reduces compliance risks, and helps firms navigate international trade rules by tackling these difficulties and policy concerns

Unveiling the Potential of PPP Theory: A Practical Approach to Short-Term BDT-USD Exchange Rate Forecasting in Bangladesh

This study explores the viability of the PPP (Purchasing Power Parity) theory in predicting short-term exchange rate movements in Bangladesh. We aim to construct a forecast model, exclusively based on PPP theory, to accurately estimate the 30, 60, and 90-day forward exchange rates of BDT-USD (Bangladeshi Taka - US Dollar) with minimal error. Drawing from approximately 9 years of monthly data, we utilize monthly nominal CPI values from Bangladesh and the USA to compute six inflation differentials across various periods (30, 60, 90, 120, 150, and 180 days). To determine the lagged impact of inflation on exchange rates, we employ a straightforward correlation matrix with associated p-values. Among these sets, the one exhibiting the highest correlation (along with the lowest p-value) with the percentage change in the 30-day forward rate is identified as the very variable having the highest impact on the next 30-day forward rate. This process is repeated for the 60 and 90-day forward rates, leading to three distinct equations for forecasting each duration. Finally, error-adjustment variables are incorporated in these equations. Our model relies on five readily available data points to forecast forward exchange rates. Results indicate that this model accurately forecasts the 30-day forward exchange rate with a ±0.58% error margin and 98.84% accuracy, with statistical robustness at a 5% significance level across the sample period. However, the performance diminishes when forecasting 60 and 90-day forward exchange rates. This study underscores the effectiveness of PPP theory in predicting up to 30 days of forward exchange rates in Bangladesh, highlighting its practical applicability in economics and finance

Sovereign Wealth Funds in the UAE, Egypt, and Kuwait

The UAE, Egypt, and Kuwait sponsor SWFs. Decision-making in the SWFs of these countries is made by the Board of Directors and management or operating committees or teams. While internal politics and geopolitics inevitably influence SWFs, the government’s direct participation in decision-making could cause concern for host countries. SWFs in the three countries are regulated under domestic law through their legal mandate and supervision by the designated government authority. The Santiago Principles and IFSWF comprise the international regulatory framework for SWFs. However, compliance is voluntary and there are no sanctions for erring members. Compliance is limited in the three countries, especially in the area of disclosure because of the close involvement in the SWFs by the ruling family in the UAE and Kuwait and the Prime Minister in Egypt. SWFs in the three countries are growing and assuming more important roles. With their expanding roles, they have to increasingly address domestic and international expectations to function more effectively. A starting point is better compliance with the Santiago Principles, which is a matter of interest in the global market. Creating a regional chapter of IFSWF can facilitate context-specific standards and compliance. Regulatory reforms can also improve the domestic investment climate to make SWFs more effective at fulfilling their purpose

Pathways from the (semi) Periphery: Early Assessment of EU Mercosur Trade Agreement in Principle: Environmental and Development Aspects

In the current international and domestic context, imagining a more complex bilateral trade agreement is more accessible than between the European Union (E.U.) and Mercosur (the South American International Trading Bloc). The tensions between these major trading blocs only aggravate international trade and economic relations. Consequently, the World Trade Organization (WTO) is bracing for its most significant challenge since its establishment in 1994. Between the E.U. and Mercosur\u27s complex trade agreement and the WTO\u27s challenge, the post-COVID-19 international legal environment has become even more complicated.   The aims of this paper are: (1) to analyze the importance of the E.U.–Mercosur agreement within the current institutional trade framework; (2) to present some of the most controversial dilemmas posed by the present agreement; and (3) to evaluate the extent to which the agreement may support or hinder more sustainable and inclusive development among both trade partners. This study will focus on Brazil due to its geography, population size, and historical efforts to bring the nation closer to the international periphery and its radical turn to authoritarian populism. Additionally, Brazil\u27s Amazon Rainforest\u27s global necessity is essential for this study

Bank Disclosure Practices in Bangladesh: Exploring the Impact of Corporate Attributes

Disclosure is necessary so that interested parties can make wise decisions. The study aims to establish the level of disclosure and whether different corporate attributes influence it. Each sample bank\u27s disclosure score was calculated using the unweighted disclosure index. Throughout five years, spanning 2016 to 2020, the necessary data were collected from sample banks\u27 annual reports, and several statistical tools were employed to illustrate the study\u27s conclusions. The study\u27s findings report that the average level of disclosure is satisfactory. The ANOVA test was used to establish whether there was a significant difference in the disclosure levels, and the results show a substantial difference in this case. Multiple regression analysis was performed to investigate the effect of various corporate attributes on disclosure levels. The study\u27s consequences showed that although these variables had significant values higher than 0.05, ROE, EPS, CAR, and log number of employees had no significant influence on disclosure levels. However, at the 0.05 significance level, log total assets demonstrate 0.055 significant levels, indicating that LTA considerably influences disclosure levels

Should the Federal Reserve Issue a Digital Currency as Virtual Legal Tender? An Econo-legal Analysis Based on China’s Master Plan for De-dollarization

Mainstream discussion on whether the Federal Reserve should issue a central bank digital currency (CBDC) as virtual legal tender focuses on five aspects related to the American domestic environment -- efficiency, privacy, safety and security, financial inclusion and exclusion, and impact on the current economic systems and monetary policies. This article takes a new and broader perspective on this critical issue by investigating how China, being the arch-international competitor of the US, has formulated a well-designed and structured master plan supported by various econo-legal strategies to pursue the objective of de-dollarization through the utilization of a China-currency-based CBDC with “controllable anonymity” and different multicurrency exchange and settlement platforms. Given the reality that de-dollarization will inevitably weaken the ubiquitous platform of international trade and payment of the US dollar (USD), can the Federal Reserve use the same tool, a USD-based CBDC, to counteract or even reverse the declining trend of the American currency’s versatility and far-reaching capability? This article recommends that the Federal Reserve can slow down the de-dollarization movement by issuing a CBDC at both the wholesale and retail levels, emphasizing the control of the former while having more cooperation with private banks for the latter