Evidence map›Paper›PMID 39994301›Full record

ArticleScientific reports2025

Research on digital infrastructure construction empowering new quality productivity.

Lu Yao, Aoyu Li, Erwang Yan

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. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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.

Lu YaoSchool of Economics and Management, Taiyuan Normal University, Jinzhong, China.
Aoyu LiSchool of Software, Taiyuan University of Technology, Jinzhong, China.
Erwang YanSchool of Economics and Management, Taiyuan Normal University, Jinzhong, China. 1290101578@qq.com.

Funding

Carbon Emission Trading Provincial-Ministerial Collaborative Innovation Center 2022 Open Topic: Research on the Path of "Dual Carbon" Goal and China's Economic Restructuring and Development 22CICETS-YB012
6 · The paper itself

Abstract

Against the backdrop of enhancing digital infrastructure to accelerate the development of new quality productivity, this study uses data from 276 prefecture-level cities in China between 2011 and 2020 to construct a static panel model and empirically examine the impact of digital infrastructure on new quality productivity. The baseline regression results indicate that digital infrastructure significantly promotes new quality productivity and remains robust after a series of stability and endogeneity tests. Heterogeneity analyses reveal that the strength of the positive effect varies across cities of different sizes, administrative levels, and geographical regions. Further mechanism tests show that digital infrastructure catalyzes new quality productivity by fostering technological innovation, improving factor allocation efficiency, and upgrading industrial structures. In addition, spatial spillover analyses suggest that digital infrastructure exerts a positive spillover effect on new quality productivity in adjacent regions, thereby benefiting regional development. These findings provide theoretical foundations and empirical insights for addressing key bottlenecks in leveraging digital infrastructure to drive the expansion of new quality productivity.

Indexed as

Digital infrastructureFactor allocation efficiencyIndustrial structure upgradingNew quality productivityTechnological innovation

Identifiers

PMID39994301
PMCPMC11850791

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.