Evidence map›Paper›PMID 41360965›Full record

ArticleScientific reports2025

Unraveling how digital transformation affects innovation capability in China's smart manufacturing enterprises.

Danping Qiu, Jiajun Qiu

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Danping QiuSchool of Management, Guangzhou College of Commerce, Guangzhou, 511363, Guangdong, China.
Jiajun QiuSchool of Foreign Languages, Guangzhou City University of Technology, Guangzhou, 510800, Guangdong, China. 1148553095@qq.com.

Funding

China's Guangdong Provincial Education Science Planning Project 2024JKDY059Guangdong Province Key Construction Discipline Research Capacity Enhancement Project 2024ZDJS079
6 · The paper itself

Abstract

In the digital economy, digital transformation has become a crucial driver of innovative capability in smart manufacturing businesses. This study examines the influence of digital transformation on innovation capabilities and its underlying processes within publicly traded smart manufacturing companies in China. Utilizing data from Chinese listed companies spanning 1999-2023, we construct a digital transformation index via text mining. Employing fixed-effects regression models to control for industry, year, and regional heterogeneity, and supplemented by multiple robustness strategies-including substituting the dependent variable with citation count for patent applications, lagged regression, omitted variable control, and placebo tests-we analyze the data. The findings demonstrate that digital transformation significantly enhances the innovative capacity of smart manufacturing enterprises, a result robust to rigorous testing. Additionally, mediation effect analyses indicate that digital transformation indirectly fosters innovation by alleviating financing constraints. Furthermore, heterogeneity analysis reveals that this innovation effect is more pronounced in Eastern regions, non-state-owned enterprises, and technology-intensive sectors, underscoring the moderating role of regional resources, ownership structure, and technological infrastructure. This study provides micro-level empirical evidence on the role of digital transformation in advancing manufacturing innovation and offers strategic insights for policymakers regarding digital infrastructure deployment and tailored guidance for enterprise transformation.

Indexed as

Digital transformationFinancing constraintsInnovation capabilitySmart manufacturing enterprises

Identifiers

PMID41360965
PMCPMC12816726

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.