From concept to reality: leveraging green innovation and supply chain management for sustainable corporate performance.

The aim of this study is to examine the potential effects that Industry 4.0, often known as the Fourth Industrial Revolution, and its accompanying technology improvements may have on SCMP and SC performance. Industry 4.0 impacts both the methods and productivity of supply chain management. Therefore, this study conceptualizes and develops an operational framework backed by SEM to examine the impact of Industry 4.0 on S.C. performance. This study employs a structural equation model (SEM) to estimate variables in India between September 2021 and March 2022 owing to the many advantages of the SEM over other estimators. The research shows that by implementing Industry 4.0-enabled technologies, businesses can improve SCM performance significantly through a holistic strategy that emphasizes supply chain integration, information sharing, and transparency. First, the results indicate that the supply chain management practices influence the Industry 4.0 technologies adoption. Second, the results revealed that Industry 4.0 technologies significantly positively affect supply chain performance measures. Finally, Industry 4.0 technologies mediated the relations between supply chain management practices and supply chain performance measures. Moreover, these technologies allow for huge performance improvements within individual supply chain processes such as procurement, production, inventory management and retailing by enabling process integration, digitization and automation, and bringing about novel analytical capabilities.

Understanding the role of green finance and innovation in achieving the sustainability paradigm: application of system GMM approach.

THe central challenge facing China's sustainable development is how to strike a balance between economic growth and environmental conservation. In China's ongoing economic revolution, green finance is more important than ever. The study empirically examined how green finance and innovation affect carbon emissions using panel data from 30 Chinese provinces gathered between 2010 and 2020. The empirical analysis is undertaken to utilize a series of methods to investigate the impact of green finance on carbon emissions. The findings show that increased green finance, innovation, and industrial structure reduce carbon output. Moreover, carbon emissions increase with increasing trade openness and economic growth. In order to achieve sustainable development goals through economic and environmental sustainability, it has been discovered that green finance can foster green technology innovation and green business.

Does green finance and ICT matter for sustainable development: role of government expenditure and renewable energy investment.

Green financing and renewable energy growth are commonly influenced by public expenditure on health and R&D; however, data supporting this claim is scarce, especially in the 65 countries that are part of the Belt and Road Initiative (BRI). The study applied Augmented Mean Group (AMG) analysis on panel data from 2005 to 2018 for BRI nations to look at the interplay between R&D and health budgets, GDP growth, FDI, carbon emissions, green finance, and renewable energy deployment. This study uses the two models for green finance and renewable energy development. In the light of the first model, economic growth, public expenditures on health and R&D, and foreign direct investment cause to increase the level of green finance in BRI economies, while the emissions cause to reduce the level of green finance. Similarly, renewable energy development uses another explained variable by this study and found the positive contribution of growth, public expenditures, and FDI inflows to renewable energy development. In contrast, environmental pollution decreases the level of renewable energy development. In order to obtain the desired level of green finance and renewable energy development, policies are suggested by the study.

A study on the association of rs7950273 polymorphism in the PDGFD with ischaemic stroke in the Chinese Han population.

BACKGROUND: The association between the platelet-derived growth factor D (PDGFD) gene and atherosclerosis has been widely proven, whereas the relationship between the PDGFD gene and ischaemic stroke remains unconfirmed. AIM: A case-control study was performed to further evaluate the association of the C → G mutation of rs7950273 in the PDGFD gene with ischaemic stroke (IS) in a Chinese Han population. SUBJECTS AND METHODS: This study recruited 3033 cases and 2807 controls from general hospitals in the southern, central and northern areas of China. The MGB probe and Taqman 7900HT Sequence Detection System were applied for genotyping. RESULTS: Genotype was not significantly associated with ischaemic stroke in total. After adjustment for gender, age, BMI, hypertension, diabetes mellitus and smoking, the CG and GG genotypes were still not associated with ischaemic stroke (p = 0.892 and p = 0.582 for CG and GG, respectively). CONCLUSION: This study suggests that the polymorphism of rs7950273 in the PDGFD gene is not associated with ischaemic stroke in the Chinese Han population. Further studies on the gene-gene and gene-environment interactions for the PDGFD gene and ischaemic stroke are needed.