Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2026 Jan 7;16(1):4800.
doi: 10.1038/s41598-026-35019-1.

Sci-Tech finance efficiency promotes the construction of a modernized industrial system evidence from double machine learning

Renquan Huang  1   2 , Xiao Liu  3   4 , Jing Tian  1   2 , Chenbo Liu  1   2 , Shuyan Wang  5 , Qingyun Zhang  1   2
Affiliations

Sci-Tech finance efficiency promotes the construction of a modernized industrial system evidence from double machine learning

Renquan Huang et al. Sci Rep. .

Abstract

Promoting a virtuous cycle among science, technology, finance, and industry is essential for advancing a modernized industrial system. Using provincial panel data from China spanning 2010-2023, this study applies a Double Machine Learning framework to investigate the causal impact of Sci-Tech finance efficiency (STFE) on the construction of a modernized industrial system(CMIS) and to uncover its internal mechanisms. The empirical results demonstrate that higher STFE significantly promotes industrial modernization by enhancing structural upgrading and innovation capacity. Mechanism analysis further reveals that STFE accelerates the transformation of scientific and technological achievements, strengthens the integration between digital technologies and the real economy, and optimizes the allocation of key production factors-including capital, talent, and technology. These mechanisms collectively foster the coordinated upgrading of industrial systems. Moreover, the heterogeneity analysis shows that the positive impact of STFE is more pronounced in regions with stronger economic foundations, higher degrees of marketization, and lower fiscal constraints, highlighting regional disparities in policy effectiveness. Overall, this study extends the theoretical understanding of the finance-technology-industry nexus under the DML framework and provides actionable insights for promoting regional coordination and differentiated policy design in the process of industrial modernization.

Keywords: Double machine learning; Modernized industrial system; Sci-Tech finance efficiency; Transformation of scientific and technological achievements.

PubMed Disclaimer

Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests. Ethical approval and consent to participate: This study uses aggregated, publicly available province-level panel data (2010–2023) compiled from official statistical yearbooks and research databases. It does not involve human participants, human biological materials, or the collection, processing, or analysis of any personally identifiable information. Therefore, ethics approval and informed consent are not required. This determination is consistent with the Measures for the Ethical Review of Life Science and Medical Research Involving Humans (National Health Commission of the People’s Republic of China, 2023), which govern ethical review requirements for research involving human participants. In addition, the academic ethics review body of the School of Economics and Finance, Xi’an International Studies University, has confirmed that this study falls outside the scope of human-subject research and issued a formal waiver of ethics approval.

Figures

Fig. 1
Fig. 1
Theoretical framework of STFE driving the construction of modernized industrial system.
See this image and copyright information in PMC

References

    1. Na, H., Li, D. & Jiang, A. Sci-tech finance empowers high-tech industry quality improvement and efficiency enhancement(In Chinese). Theor. Pract. Fin. Econ., 1–8, https://link.cnki.net/urlid/43.1057.F.20250826.1855.002 (2025).
    1. Chengming, L., Feiyan, L., Yinhe, L. & Zeyu, W. Low-carbon strategy, entrepreneurial activity, and industrial structure change: evidence from a quasi-natural experiment. J. Clean. Prod.427, 139183. 10.1016/j.jclepro.2023.139183 (2023). - DOI
    1. Fischer, B., Meissner, D., Boschma, R. & Vonortas, N. Global value chains and regional systems of innovation: towards a critical juncture? Technol. Forecast. Soc. Change. 201, 123245. 10.1016/j.techfore.2024.123245 (2024). - DOI
    1. Han, Q. & Deng, C. Evaluating the development of china’s modern industrial system. Financ Res. Lett.74, 106676. 10.1016/j.frl.2024.106676 (2025). - DOI
    1. R, M. Strategic thinking, target and paths for the construction of the modern industrial system(In Chinese). China Ind. Econ.09, 24–40. 10.19581/j.cnki.ciejournal.2018.09.012 (2018). - DOI

LinkOut - more resources