Our paper examines the relationship between State Bank of Vietnam's implementation of monetary policies, Foreign direct investment inflows, and the country's move toward a circular economy. By using the PLS-SEM method with 330 observations, the study demonstrated that the positive impacts of the State Bank of Vietnam's monetary policies will aid in promoting Vietnam's transition to the circular economy, either when the State Bank offers a contractionary or expansionary or sustainable monetary policy. Moreover, when a country receives foreign direct investment, it tends to encourage companies' ability to create green, environmentally friendly products. Foreign direct investment inflows also stimulate a country to the transition to circular economy. Our research highlights the regulatory factor of Foreign Direct Investment capital that will increase 0.204 and 0.07 levels of impact between stable and expansionary monetary policy on the shift to circular economy. The results of this study contribute new factors in the theory of circular economy as well as policy implications for the State Bank of Vietnam, thereby aiding in the State Bank's development of an appropriate monetary policy to encourage foreign direct investment and the transition to the circular economy.

This study examines AI-powered predictive analytics in digital marketing, analyzing customer behavior and personalization impacts. Through a quantitative analysis of 207 respondents, the research reveals a gap between AI tool adoption (30% regular usage) and their demonstrated effectiveness, with recommendation systems showing high consumer relevance despite low conversion rates. Statistical analysis demonstrates strong correlations between customer experience and digital shopping behavior, with interconnections between personalized content quality and prediction accuracy. The study identifies distinct clusters in user behavior patterns, highlighting the relationship between AI trust indicators and traditional shopping patterns. These findings provide valuable insights for organizations seeking to optimize their digital marketing strategies through AI implementation while addressing the current challenges in adoption and effectiveness.

Anti-money laundering (AML) plays a vital role in safeguarding economic stability, enhancing social security, and promoting social equity. This study examines the impact of green finance performance on the effectiveness of AML measures, based on a sample of Asian countries. Using the Generalized Least Squares (GLS) and Two-Stage Least Squares (2SLS) methods, the results reveal that government-issued green bonds are negatively associated with AML effectiveness. Moreover, higher levels of corruption appear to undermine AML effectiveness, highlighting the urgent need for robust and collaborative policy measures to align sustainable development goals with effective AML frameworks. These findings remain consistent across additional robustness tests. The study suggests that governments should strengthen anti-corruption measures and integrate AML standards into the assessment and regulation of green finance performance.