Evidence map›Paper›PMID 36711307›Full record

ArticleHeliyon2023

Digital economy, spatial spillover and industrial green innovation efficiency: Empirical evidence from China.

Guangqin Li, Xiaoge Li, Lingzhi Huo

Abstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 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.

Guangqin LiSchool of International Trade and Economics, Anhui University of Finance and Economics, Bengbu, Anhui 233030, China.
Xiaoge LiSchool of International Trade and Economics, Anhui University of Finance and Economics, Bengbu, Anhui 233030, China.
Lingzhi HuoSchool of Economics and Finance, Chongqing University of Technology, Chongqing 400054, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The digital economy is pushing more efficient and greener production and innovation processes, as well as quickening the mobility of production factors, which would have a critical impact on improving industrial green innovation efficiency. Based on the panel data of 30 Chinese provinces from 2005 to 2019, this study established a comprehensive index system to assess the level of provincial digital economy development, and adopted the SBM-DEA model including non-expected output to evaluate industrial green innovation efficiency, then adopted the

Indexed as

Green innovation efficiencyIndustrial green innovationSpatial spillover effectsThe digital economy

Identifiers

PMID36711307
PMCPMC9876823

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.