Despite great academic interest in global green supply chain management (GSCM) practices, its effectiveness for environmental management systems (EMS) and market competitiveness during COVID-19 remains untapped. Existing literature suggests that a fundamental link between GSCM, EMS, and market competitiveness is missing, as supply management is critical to maintain market competitiveness. To fill this gap in the literature, this study examines whether environmental management systems influence the link between GSCM practice and market competitiveness in China. We also propose the articulating role of big data analytics and artificial intelligence (BDA-AI) and environmental visibility toward these associations in the context of the COVID-19 pandemic. We evaluated the proposed model using regression-based structural equation modeling (SEM) with primary data (n = 330). This result provides empirical evidence of the impact of GSCM on EMS and market competitiveness. Moreover, the results show that the BDA-AI and the environmental visibility enhanced the positive relationship between GSCM-EMS and EMS and market competitiveness in China. Recent research shows that supply chain professionals, policymakers, managers, and researchers are turning to formal EMS, BDA-AI, and environmental visibility to help their organizations achieve the competitiveness that the market indicates they need.

We propose a vector error correction model to explore the causal correlation between green finance, economic growth, and renewable energy consumption from both short- and long-run perspectives to empirically evaluate the efficacy of green finance policies. Based on time-series data from 2000 to 2020, we use the unit root test method to examine time-varying trends and cointegration for time-series data. We find that renewable energy consumption has a negative relationship with emissions but green finance is positively correlated with economic growth. Green finance is the driving factor behind the increasing utilization of renewable energy in China. CO ₂ emissions per unit of GDP decreased by 1.077% for every 1% increase in green finance development. Although the share of renewable energy consumption increased by 1%, CO ₂ emissions per unit of GDP decreased by 0.55%. Therefore, green finance is significant in decreasing CO ₂ emissions; it has a negative impact on CO ₂ emissions and the renewable energy sector and must be addressed by financial policy, stability, and long-run sustainability. We categorized green finance, which refers to carbon finance innovations such as trusteeship, to improve market demand and eventually develop industries to expand the number of emission-control industries.

Despite great academic interest in global green supply chain management (GSCM) practices, its effectiveness for environmental management systems (EMS) and market competitiveness during COVID-19 remains untapped. Existing literature suggests that a fundamental link between GSCM, EMS and market competitiveness is missing, as supply management is critical to maintain market competitiveness. To fill this gap in the literature, this study examines whether environmental management systems influence the link between GSCM practice and market competitiveness. We also propose the articulating role of big data analytics and artificial intelligence (BDA-AI) and environmental visibility towards these associations in the context of the Covid-19 pandemic. We evaluated the proposed model using regression-based structural equation modeling (SEM) with primary data (n = 330). This result provides empirical evidence of the impact of GSCM on EMS and market competitiveness. Moreover, the results show that the BDA-AI and the environmental visibility enhanced the positive relationship between GSCM-EMS and EMS and market competitiveness. Recent research shows that supply chain professionals, policy makers, managers and researchers are turning to formal EMS, BDA-AI and environmental visibility to help their organizations achieve the competitiveness that the market indicates they need.