Abstract
Enhancing the energy transition of the Chinese economy toward digitalization gained high importance in realizing SDG-7 and SDG-17. For this, the role of modern financial institutions in China and their efficient financial support is highly needed. While the rise of the digital economy is a promising new trend, its potential impact on financial institutions and financial support is unproven. For this, this research intended to study how financial institutions assure financial support for China’s energy transition toward digitalization. To attain this purpose, DEA analysis and Markov chain techniques are applied to the Chinese data from 2011 to 2021. The results estimated that the transition of the Chinese economy toward digitalization significantly depends upon the digital services of financial institutions and extended digital financial support. The extent of the digital energy transition in China can enhance economic sustainability. The role of Chinese financial institutions accounted for 29.86% of the total effect in transiting China’s digital economy. In comparison, the part of digital financial services is found to be significant, with a score of 19.77%. The Markov chain estimates revealed that the digitalization of financial institutions is 86.1%, and financial support is 28.6% important for the digital energy transition of China. The Markov chain result caused a digital energy transition of 28.2% in China from 2011 to 2021. The findings highlighted that China still warrants more prudent and active efforts for financial and economic digitalization, for which the primary research also presents multiple policy recommendations.
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The data that support the findings of this study are openly available on request.
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Conceptualization, methodology, and writing—original draft: Xiyan Zhang; data curation, visualization, and editing: Na Chen.
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Zhang, X., Chen, N. Does financial institutions assure financial support in a digital economy for energy transition? Empirical evidences from Markov chain and DEA technique. Environ Sci Pollut Res 30, 63825–63838 (2023). https://doi.org/10.1007/s11356-023-26807-7
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DOI: https://doi.org/10.1007/s11356-023-26807-7