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<p>Carbon finance, as a financial tool for adapting to and mitigating global climate change, can guide enterprises to help develop digital green technological innovation and ultimately realize the transition to a low-carbon economy. This paper selects relevant control variables and applies the spatial econometric model to analyze the impact of carbon financial trading policy on enterprises’ green technological innovation, and examines the different impacts of the policy on the number of green invention-based patent applications and the number of green utility model patent applications, respectively. To examine the heterogeneity of regions and enterprise size, the samples were further grouped. Finally, a gray correlation model is used to study the main drivers of the intrinsic interactions among the three systems of digital technology innovation, carbon finance, and industrial policy. Most of the gray correlations between technological innovation and carbon finance indicators are located between 0.5 and 0.7, and the average value of the correlations of all the indicators is higher than 0.60, with only four lower than 0.65, and the highest indicator is 0.666. It indicates that the correlation between carbon finance and digital green technological innovation among enterprises is high.</p>
</abstract>

Carbon finance, as a financial tool for adapting to and mitigating global climate change, can guide enterprises to help develop digital green technological innovation and ultimately realize the transition to a low-carbon economy. This paper selects relevant control variables and applies the spatial econometric model to analyze the impact of carbon financial trading policy on enterprises’ green technological innovation, and examines the different impacts of the policy on the number of green invention-based patent applications and the number of green utility model patent applications, respectively. To examine the heterogeneity of regions and enterprise size, the samples were further grouped. Finally, a gray correlation model is used to study the main drivers of the intrinsic interactions among the three systems of digital technology innovation, carbon finance, and industrial policy. Most of the gray correlations between technological innovation and carbon finance indicators are located between 0.5 and 0.7, and the average value of the correlations of all the indicators is higher than 0.60, with only four lower than 0.65, and the highest indicator is 0.666. It indicates that the correlation between carbon finance and digital green technological innovation among enterprises is high.

Analysis of the Impact of Carbon Finance on Digital Green Technology Innovation of Enterprises

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Carbon finance, as a financial tool for adapting to and mitigating global climate change, can guide enterprises to help develop digital green technological...

Analysis of the Impact of Carbon Finance on Digital Green Technology Innovation of Enterprises

Data publikacji: 29 lis 2023

Zakres stron: -

Otrzymano: 13 gru 2022

Przyjęty: 09 cze 2023

DOI: https://doi.org/10.2478/amns.2023.2.01307

Słowa kluczowe
Spatial econometric model, Carbon finance, Green technology innovation, Gray correlation, Industrial policy

© 2023 Shuai Zhao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Analysis of the Impact of Carbon Finance on Digital Green Technology Innovation of Enterprises

Data publikacji: 29 lis 2023

Zakres stron: -

Otrzymano: 13 gru 2022

Przyjęty: 09 cze 2023

DOI: https://doi.org/10.2478/amns.2023.2.01307

Słowa kluczoweSpatial econometric model, Carbon finance, Green technology innovation, Gray correlation, Industrial policy

© 2023 Shuai Zhao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Spatial econometric model, Carbon finance, Green technology innovation, Gray correlation, Industrial policy