Evidence map›Paper›PMID 36452959›Full record

ArticleFrontiers in public health2022

Research on the evolution of the Chinese urban biomedicine innovation network pattern: An analysis using multispatial scales.

Zhimin Ren, Jiaao Yu, Liping Qiu, Xuya Hong, Shaobin Wei, Haiyan Zhou, Xiao Hu, Xiaolei Zhang, Wei Zhang, Isaac Akpemah Bathuure and 5 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 21% 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

4 citing papers in PubMed, 3 citations in OpenAlex.

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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

15 authors at 8 institutions in 2 countries.

Zhimin RenSchool of MBA, Zhejiang Gongshang University, Hangzhou, China.
Jiaao YuLondon College of Communication, University of the Arts London, London, United Kingdom.
Liping QiuGlobal Value Chain Research Center, Zhejiang Gongshang University, Hangzhou, China.
Xuya HongGlobal Value Chain Research Center, Zhejiang Gongshang University, Hangzhou, China.
Shaobin WeiInstitute of Digital Economy and Green Development, Chifeng University, Chifeng, China.
Haiyan ZhouInstitute of Digital Economy and Green Development, Chifeng University, Chifeng, China.
Xiao HuCash Crop Workstation, Shangcheng Bureau of Agriculture and Rural Affairs, Xinyang, China.
Xiaolei ZhangSchool of Economics and Management, Chifeng University, Chifeng, China.
Wei ZhangAcademic Affairs Office, Xing'an Vocational and Technical College, Ulanhot, China.
Isaac Akpemah BathuureGlobal Value Chain Research Center, Zhejiang Gongshang University, Hangzhou, China.
Qican YangSchool of MBA, Zhejiang Gongshang University, Hangzhou, China.
Ning SuSchool of MBA, Zhejiang Gongshang University, Hangzhou, China.
Wei LeeSchool of Urban and Regional Science, East China Normal University, Shanghai, China.
Xiaoping WangCollege of Business Administration, Ningbo University of Finance and Economics, Ningbo, China.
Hao HuSchool of Economics, Shanghai University, Shanghai, China.
Zhejiang Gongshang University · CNChifeng University · CNEast China Normal University · CNJiaxing Vocational Technical College · CNMinistry of Agriculture and Rural Affairs · CNNingbo University · CNShanghai University · CNUniversity of the Arts London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper addresses the spatial pattern of urban biomedicine innovation networks by separately using four scales, i.e., the national scale, interregional scale, urban agglomeration scale, and provincial scale, on the basis of Chinese biomedicine patent data from the incoPat global patent database (GPD) (2001-2020) and using the method of social network analysis (SNA). Through the research, it is found that (1) on the national scale, the Chinese biomedicine innovation network becomes denser from west to the east as its complexity continuously increases. Its spatial structure takes the form of a radial network pattern with Beijing and Shanghai as its centers. The COVID-19 pandemic has not had an obvious negative impact on this network at present. (2) On the interregional scale, the strength of interregional network ties is greater than that of intraregional network ties. The eastern, central and western biomedicine innovation networks appear to be heterogeneous networks with regional central cities as the cores. (3) At the urban agglomeration scale, the strength of intraurban-agglomeration network ties is greater than that of interurban-agglomeration network ties. The three major urban agglomerations have formed radial spatial patterns with central cities as the hubs. (4) At the provincial scale, the intraprovincial networks have poor connectivity and low internal ties strength, which manifest as core-periphery structures with the provincial capitals as centers. Our research conclusion helps to clarify the current accumulation of technology and offer guidance for the development of China's biomedicine industry.

Indexed as

COVID-19PandemicsAsian PeopleChinaHealth OccupationsHumansbiomedicineChinamultiscalenetwork patternpatent cooperationurban innovation network

Identifiers

PMID36452959
PMCPMC9702537
OpenAlexW4309011641

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.