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Can Agriculture-Related Enterprises’ Green Technological Innovation Ride the “Digital Inclusive Finance” Wave?

Ning Gu et al.

Economics: The Open Access, Open Assessment E-journal2025https://doi.org/10.1515/econ-2025-0174article
ABDC B
Weight
0.54

What the paper says

This article systematically examines how digital inclusive finance drives green technological innovation in agriculture-related enterprises. The findings reveal three key insights. First, digital inclusive finance fosters both the “quantity expansion” and “quality enhancement” of green technological innovation in agriculture-related enterprises. Second, this effect operates through three mechanisms: improving financial accessibility, reducing information asymmetry, and stimulating innovation vitality. Third, the impact of digital inclusive finance is heterogeneous – its driving effect is more pronounced in non-state-owned enterprises, highly digitally transformed firms, businesses in non-heavily polluting industries, and enterprises located in eastern China. In summary, this article uncovers an important channel through which digital inclusive finance promotes green technological innovation in agriculture-related enterprises and provides empirical evidence for relevant policy formulation.

9 citations

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Cite this paper

https://doi.org/https://doi.org/10.1515/econ-2025-0174

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@article{ning2025,
  title        = {{Can Agriculture-Related Enterprises’ Green Technological Innovation Ride the “Digital Inclusive Finance” Wave?}},
  author       = {Ning Gu et al.},
  journal      = {Economics: The Open Access, Open Assessment E-journal},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1515/econ-2025-0174},
}

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Can Agriculture-Related Enterprises’ Green Technological Innovation Ride the “Digital Inclusive Finance” Wave?

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Evidence weight

0.54

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.52 × 0.4 = 0.21
M · momentum0.72 × 0.15 = 0.11
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.