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 main purpose of this paper is to explore how green supply chain management (GSCM) and its evaluative factors have affected green supply chain management practice and performance in industrial zone. This study proposes a structural equation model of the relationships among four factors: internal awareness (IA); suppliers’ pressure (SP); customers’ awareness (CA); and regulations pressure (RP) and their effect on GSCM practice (PA) and GSCM performance (PE). We used a survey questionnaire to elicit perceptions/opinions about GSCM from three level of managers of 322 companies in Bac Ninh Province’s industrial zones, Vietnam. PLS-SEM 3.0 software was applied to analyze and verify the gathered data, and the proposed hypothesis model. The results of path analysis show that internal awareness and customers’ awareness are positively related to the GSCM practice and GSCM performance. However, suppliers’ pressure and regulations pressure just impacted on GSCM practice. As a result, the testing of the relationship between GSCM practice and GSCM performance has been verified and supported. The findings of this study can help manager of companies in industrial zone understand the structure of GSCM, associate with the green supply chain management practice and green supply chain management performance, and be successful in green management organizations.

This paper aims to investigate FDI attractive factors, which are important to formulate policies to attract Korean direct investment into Vietnam. Based on the literature review and the results of interview with 27 Korean investors in Vietnam, we determined the model of variables attracting Korea’s FDI into Vietnam. It is used to assess the impact of attractive factors belonging to three groups of variables to support investment decision; they are macroeconomics variables (including market size factor, labor cost factor, and market openness factor), policies variables (including monetary policy factor and tax rate gap factor), and microeconomics variables (geographic advantage factor representative by location). This research also utilized a relatively new quantitative research method based on the Autoregressive Distributed Lag model (ARDL) with the time data chain from 1995 to 2017 of Korean FDI into Vietnam. It analyzes long-term relationships between dependent variables and independent variables. The result of this study indicates that there are three positive factors (low wages, trade openness and government policy) explaining the FDI flows in the long term. The result also shows that incentive tax policy has had a positive impact on Korean FDI, which has satisfied the aim of seeking efficiency of Korean investors.