Evidence map›Paper›PMID 31557224›Full record

ArticlePloS one2019

Spatial-temporal variation characteristics and evolution of the global industrial robot trade: A complex network analysis.

Yaya Li, Yongtao Peng, Jianqiang Luo, Yihan Cheng, Eleonora Veglianti

Abstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

5 authors.

Yaya LiSchool of Finance & Economics, Jiangsu University, Zhenjiang, Jiangsu, P.R. China.ORCID 0000-0002-1921-8478
Yongtao PengSchool of Management, Jiangsu University, Zhenjiang, Jiangsu, P.R. China.
Jianqiang LuoSchool of Management, Jiangsu University, Zhenjiang, Jiangsu, P.R. China.
Yihan ChengSchool of Finance & Economics, Jiangsu University, Zhenjiang, Jiangsu, P.R. China.
Eleonora VegliantiDepartment of Economics, University of Uninettuno, Roma, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Industrial robots are a strategic future technology and an important part of the development of artificial intelligence, and they are a necessary means for the intelligent transformation of manufacturing industry. Based on global industrial robot trade data from 1998 to 2017, this paper applies the dynamic complex network analysis method to reveal the spatial and temporal variation characteristics and trade status evolution of the global industrial robot trade network. The results show that the global industrial robot network density has steadily increased, and the industrial robot trade has been characterized by 'diversification'. The number of major industrial robot exporters in the world is increasing, and the import market is increasingly diversified. The export market structure is relatively tight, the centrality of the global industrial robot trade network shows a downward trend, and the dissimilarity of the 'core-edge' clusters decreases year by year. The trade status of 'catch-up' countries represented by China has rapidly increased. However, Japan, Germany, and Italy are still in the central position of the industrial robot trade. Moreover, trade of the 'catch-up' countries' is dominated by imports, and exports of industrial robot products are insufficient. Finally, policy suggestions are provided according to the results.

Indexed as

Spatio-Temporal AnalysisArtificial IntelligenceChinaCommerceGermanyItalyJapanRobotics

Identifiers

PMID31557224
PMCPMC6762107

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.