Evidence map›Paper›PMID 40479424›Full record

ArticleJournal of the knowledge economy2022

Evolution of Knowledge Structure in an Emerging Field Based on a Triple Helix Model: the Case of Smart Factory.

Dong Liu, Yu Peng Zhu

Abstract read
In one paragraph

Article in Journal of the knowledge economy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

2 authors.

Dong LiuInterdisciplinary Graduate Programs of Global Business, Yeungnam University, Gyeongsan-si, South Korea.ORCID 0000-0003-2902-8536
Yu Peng ZhuSchool of Journalism and Communication, Chongqing University, No.55 Daxuecheng South Rd., Gaoxinqu, Chongqing, 401331 China.ORCID 0000-0003-0544-3911

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As an important emerging field of science and technology, smart factories have received attention from academia, industry, and the government. Currently, although some scholars have examined the research trends in the field of smart factories, we have not found any research on the analysis of the knowledge output of relevant organizations among smart factories. An urgent problem is whether cooperation between organizations with different characteristics will affect the overall development of intelligent factories. This study aimed to perform a comprehensive analysis of the knowledge content and structure of a smart factory and the characteristics of its knowledge production structure. We also evaluated whether the triple helix structure was stable, and whether the research topics of different issues were similar. The triple helix model was used to study three aspects of the knowledge structure of a smart factory: university, government, and industry. Furthermore, the research contents of different organizations were analyzed in detail using network analysis. It was found that research funding at the national level leads to a knowledge spillover effect. After 2015, a triple helix knowledge structure was formed in the field of smart factories, which maintained a certain stability until 2020. The output of triple helix cooperation research has a significant impact. University research focuses more extensively and intensively on technology, government research on macro aspects, and Industry 5.0 has become a hotspot in industry research. The government needs to provide new platforms to integrate and promote the development of smart factories.

Indexed as

Industry 4.0Industry 5.0Knowledge managementSmart factoryTriple helix

Identifiers

PMID40479424
PMCPMC9535226

What OpenQuestion holds

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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.