The paper’s main goal is to investigate and contrast the impacts of foreign direct investment (FDI) inflows on environmental protection in various Asian locations. In order to achieve this end, the validity of the Halo/Haven pollution hypothesis is examined using a panel data framework for the annual data of 32 Asian economies over the period of 2000–2019. While the sign of squared Gross Domestic Product (GDP) per capita is not statistically significant for low- and lower-middle-income group of Asian economies, which does not confirm the existence of EKC hypothesis in these countries, the main results showed that the Environmental Kuznets Curve (EKC) hypothesis exists in high- and upper-middle-income group of Asian nations. In the group of Asian nations with high- and upper-medium-incomes, there is the Halo hypothesis; in the group of nations with low- and lower-middle-incomes, there is the Haven pollution hypothesis. Important practical policies recommended by this research include promoting green finance methods, creating digital economic mechanisms, and revising laws and policies that encourage FDI in order to enhance their ability to attract foreign investors in the post-Corona era.
This paper aims to develop a conceptual framework for Green Supply Chain Management (GSCM) that takes into account the effect of GSCM drivers on implementing GSCM practices in Vietnam FDI companies. This study has considered organizational commitment, social network, and government support as GSCM driver factors and proposed a structural model of the relationships between GSCM drivers and GSCM practices in Vietnam FDI companies. The empirical analysis used data from 192 questionnaires which used a comprehensive, valid, and reliable tool (SPSS 26 and SmartPLS 3.0 software) to evaluate rigorous statistical tests including convergence validity, discriminatory validity, reliability, and Average Variance Extracted (AVE) to analyze and verify the gathered data and develop the hypothesis. The result of path analysis shows that GSCM driver factors constitute a structured system with different degrees of influence on GSCM drivers and GSCM practices. Organizational commitment and government support has a positive relationship with both GSCM drivers and GSCM practices, while social network only has a positive relationship on GSCM drivers. As a result, the testing of the relationship between GSCM drivers and GSCM practices has been verified and supported. The findings of this study can help managers and decision-makers to push the implementation of GSCM practices in FDI companies.
The study aims to investigate the critical factors that could significantlt impact in the online teaching quality for economics students in Vietnam by employ the PLS-SEM. Four critical factors in a new construct to study online teaching quality for economics students are proposed including characteristics of students, online teaching technology, characteristics of lecturers, online course content. Based on a survey of 705 students in four economics universities in Vietnam, the Structural Equation Modeling was carried out to study the reationship between latent variables based on the scale of psychological properties that measured the dimesions of online teaching quality. The relationship between latent variables is done through the Structural Equation Modeling. The research applied both SPSS 26.0 and PLS-SEM 3.0 software, in order to analyze and verify the gathered data, then proposed a hypothesis model. The results reveal that all proposed factors are positively related to the online teaching quality, in which online course content has the most impact on teaching online quality, followed by characteristics of lecturers, characteristics of students, and finally, online teaching technology. The results of the relationship between critical factors and online teaching quality has been verified and supported. The findings will be an important indication for university managers and researchers when improving the quality of online teaching in Vietnam based on student priorities.
Received: 25 March 2022 / Accepted: 25 June 2022 / Published: 5 July 2022
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