How does digital-green policy synergy affect substantive and strategic green technology innovation? Evidence from China

Jianfeng Jiang et al.

International Review of Economics & Finance2026https://doi.org/10.1016/j.iref.2026.104969article
AJG 2ABDC A
Weight
0.37

Abstract

The synergistic development of digitalization and greening, a crucial strategic arrangement for high-quality development in critical development phase, enhances the optimal allocation of innovation resources. Therefore, utilizing panel data from 285 Chinese prefecture-level cities from 2010 to 2023, this study employs the double machine learning method to investigate how digital-green policy synergy affects substantive and strategic green technology innovation. The study findings indicate that: compared to non-pilot cities, digital-green policy synergy significantly promotes substantive green technology innovation while inhibiting strategic green technology innovation, and these results remain robust to various robustness tests. Heterogeneity analyses reveal a significant spatial differentiation in the effects of digital-green policy synergy. For substantive green technology innovation, non-transportation hub cities and cities with positive net migration exhibit stronger positive effects; for strategic green technology innovation, the inhibitory effects are more pronounced in non-resource-based cities, non-transportation hub cities, and cities with positive net migration. Drawing on the Porter Hypothesis and information asymmetry theory, we identify industrial structure and talent recruitment intensity as two key channels linking digital-green policy synergy to substantive and strategic green technology innovation. These findings provide novel evidence for the differentiated innovation effects arising from the integrated development of digitalization and greening.

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https://doi.org/https://doi.org/10.1016/j.iref.2026.104969

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@article{jianfeng2026,
  title        = {{How does digital-green policy synergy affect substantive and strategic green technology innovation? Evidence from China}},
  author       = {Jianfeng Jiang et al.},
  journal      = {International Review of Economics & Finance},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1016/j.iref.2026.104969},
}

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Evidence weight

0.37

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

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
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.