Evidence map›Paper›PMID 40078775›Full record

ArticleFrontiers in public health2025

Examining how fiscal policies influence innovation in TCM enterprises: the role of R&D investment and executives with pharmaceutical backgrounds.

Dan Guo, Liwen Qi, Xiaoting Song

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Dan GuoShanghai International College of Intellectual Property, Tongji University, Shanghai, China.
Liwen QiShanghai International College of Intellectual Property, Tongji University, Shanghai, China.
Xiaoting SongShanghai International College of Intellectual Property, Tongji University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Innovation is crucial to realize the modernization and industrialization of traditional Chinese medicine (TCM), so its incentive methods and influence mechanisms are worth exploring. Based on externality theory and imprinting theory, this paper demonstrates the significance of external support and internal resources in the innovation of TCM enterprises. Methods: This study adopts a sample of listed TCM enterprises in China during 2007-2023 to examine the impacts and differences between innovation subsidies and tax incentives on TCM enterprise innovation. Innovation in TCM enterprises is deconstructed into five dimensions, including innovation quantity (InNum), innovation quality (InQua), substantive innovation (SubIn), strategic innovation (StrIn), and inheritance innovation (InhIn). Results: It is found that the incentive effect of innovation subsidies on other dimensions of innovation in TCM firms is generally stronger than that of tax incentives, except for strategic innovation. Heterogeneity analysis indicates that the promoting effect of tax incentives is more significant in the southern TCM production region. Moreover, R&D investment mediates the relationship between innovation subsidies and innovation of TCM enterprises. Furthermore, executives with pharmaceutical backgrounds (EPB) strengthen the impact of innovation subsidies on innovation in various dimensions of TCM enterprises, while EPB only strengthens the impact of tax incentives on innovation quality and substantive innovation. Discussion: The findings provide new insights for government and TCM enterprises to promote innovation.

Indexed as

InventionsInvestmentsMedicine, Chinese TraditionalResearchChinaHumansTaxesenterprise innovationexecutives with pharmaceutical backgroundsinnovation subsidiestax incentivestraditional Chinese medicine

Identifiers

PMID40078775
PMCPMC11897503

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.