Evidence map›Paper›PMID 35936265›Full record

ArticleFrontiers in psychology2022

The impact of intellectual property protection on the development of digital economy and regional entrepreneurial activity: Evidence from small and medium enterprises.

Hong Chen

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychology, 2022. 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
2.0field-weighted citation impact, top 12% of its field
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, 8 citations in OpenAlex.

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

1 author at 1 institution in 1 country.

Hong ChenShanghai International College of Intellectual Property, Tongji University, Shanghai, China.
Tongji University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Substantial intellectual property management (IPM) is vital in retaining competitive advantage and managing outbound open innovation (OI), which may enhance an organization's commercialization and entrepreneurial performance. Thus, the objective of this study was to develop an understanding of the impact of intellectual property protection on the development of the digital economy, regional entrepreneurial activity, and explore how IPM can enhance the entrepreneurial performance (EP) through open innovation (OI) and commercialization performance (CP) in the context of small and medium enterprises (SMEs) in Mainland China. Our study also shows how open innovation model constraints (OIMC) and information communication technology (ICT) enhance the performance. Using the organizational performance theory, we developed our research framework and collected usable data from 530 respondents from the management of SMEs in Mainland China. Data analyses were performed using SPSS, and structural equation modeling was performed using Amos 24 to test the hypothesis. Our results highlighted the significant effect of IPM on OI, CP, and EP. This study suggests various conclusions, stressing the mediating function of CP in improving EP and the direct and indirect effects of OI and CP on EP. This study also emphasizes that business managers need to ensure collaboration among SMEs since it is the best strategy to use each other's resources, including OI ideas, to improve the EP, and it should be done utilizing ICT.

Indexed as

commercialization performanceentrepreneurial performanceinformation communication technologyintellectual propertyopen innovation

Identifiers

PMID35936265
PMCPMC9355399
OpenAlexW4286561071

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.