Investigating Green Finance as a Mediator in the Relationship between Predictors and Environmental Sustainability

Main Article Content

Raghvendra
Prof. (Dr.) Trilochan Sharma
Dr. Saurabh Verma
Mahima Karki
Bipin Chauhan
Vignesh Awasthi

Abstract

The study aims to explore the mediating role of green finance in the relationship between its key predictors—regulatory environment, financial institutions, investor demand, technological innovation, public awareness, and education—and the implementation of green finance management practices and their impact on environmental sustainability. By examining these relationships, the research seeks to highlight the significant influence of green finance on promoting sustainable environmental practices. The findings of this investigation are expected to contribute to the advancement of green projects, thereby enhancing environmental sustainability in the long run.

Article Details

How to Cite
Raghvendra, Sharma, T., Verma, S., Karki, M., Chauhan, B., & Awasthi, V. (2024). Investigating Green Finance as a Mediator in the Relationship between Predictors and Environmental Sustainability. CINEFORUM, 84–101. Retrieved from https://revistadecineforum.com/index.php/cf/article/view/154
Section
Conference Paper

References

Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6), 716–723.

Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246.

Bollen, K. A., & Long, J. S. (1993). Testing structural equation models. Sage.

Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models. Sage, 136–162.

Chen, S. & Xie, G. (2023). Assessing the linkage among green finance, technology, and education expenditure: evidence from G7 economies. Environmental Science and Pollution Research, 30(1), 50332-50345.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2013). Multivariate data analysis (7th ed.). Pearson.

Han, Y., Tan, S., Zhu, C. and Liu, Y. (2023). Research on the emission reduction effects of carbon trading mechanism on power industry: plant-level evidence from China. International Journal of Climate Change Strategies and Management, 15(2), 212-231.

He J, Iqbal W, Fangli Su (2023). Nexus between renewable energy investment, green finance, and sustainable development: role of industrial structure and technical innovations. Renewable Energy, 210(5), 715-724.

Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.

Khan, KI., Nasir, A., Rashid, T. (2022). Green practices: a solution for environmental deregulation and the future of energy efficiency in the post-COVID-19 era. Front Energy Res, 10(1), 1-14.

Marsh, H. W., Balla, J. R., & McDonald, R. P. (1996). Goodness-of-fit indexes in confirmatory factor analysis: The effect of sample size. Psychological Bulletin, 103(3), 391–410.

Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461–464.

Steiger, J. H. (1990). Structural model evaluation and modification: An interval estimation approach. Multivariate Behavioral Research, 25(2), 173–180.

Tang, W-Q, Meng B, Li-Bo, W. (2020). The impact of regulatory and financial discrimination on China’s low-carbon development: considering firm heterogeneity. Advances in Climate Change Research, 11(2), 72-84.