Evidence map›Paper›PMID 37490503›Full record

ArticlePloS one2023

How innovation funding leads enterprises to engage in research and development: Small and medium enterprises' perspective.

Hui Sun, Xiaocong Yang, Xuan Tang, Fei Peng

Expression of concernAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It carries an expression of concern. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Hui SunSchool of Economics and Statistics, Guangzhou University, Guangzhou, Guangdong, 510006, China.
Xiaocong YangSchool of Public Administration, Guangzhou University, Guangzhou, Guangdong, 510006, China.ORCID 0000-0002-3534-6170
Xuan TangSchool of Management and Director of International Office, Guangzhou University, Guangzhou, Guangdong, 510006, China.
Fei PengSchool of International Economics and Trade, Shanghai Lixin University of Accounting and Finance, Shanghai, 201209, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Technology-based small and medium enterprises (SMEs) are the driving force behind China's economic and technological development. However, these enterprises often face challenges in financing their research and development (R&D) activities due to limited financing opportunities. Previous research has primarily focused on the resource attributes of government innovation subsidies, which serve as a crucial funding source for these SMEs. This paper aims to explore the impact of government innovation subsidies on firms from a novel perspective, considering the signaling characteristics of these subsidies. The theoretical foundation of this study lies in the asymmetric information theory and the signaling mechanism through which government subsidies send signals about enterprises. The study uses enterprise data from 2012 to 2019 to investigate the effect of government subsidies on the R&D investment of enterprises listed on the SMEs Board in Chinese stock market. The results reveal a significantly positive effect of government subsidies on the R&D investment of SME Board-listed enterprises and verify the mediating role of financing constraints in this effect. The extent to which government subsidies influence the R&D investment of SME Board-listed enterprises is associated with the enterprises' ownership characteristics, debt ratios, and times interest earned ratios. This study contributes to the literature on the SMEs Board market and may provide the Chinese government insights into developing industry policies that maximize the effectiveness of government subsidies.

Indexed as

Financing, GovernmentGovernmentIndustryInventionsResearchChinaIncomeInformation Theory

Identifiers

PMID37490503
PMCPMC10368280

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.