Evidence map›Paper›PMID 39700215›Full record

ArticlePloS one2024

Analysis of bottleneck technology identification and development characteristics in the electronic manufacturing industry.

Lei Zhou

Abstract read
In one paragraph

Article in PloS one, 2024. 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
–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

0 citing papers in PubMed.

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.

Lei ZhouBeijing Institute of Science and Technology Information, Beijing Academy of Science and Technology, Beijing, China.ORCID 0000-0003-2971-3138

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In 2018, US government imposed a ban on Chinese electronics firm ZTE, prohibiting it from procuring chip products from American companies for a duration of seven years. Subsequently, ZTE experienced a shutdown. The concept of "bottleneck technology" gained prominence in diverse media outlets. Chinese government acknowledged the importance of identifying pertinent bottleneck technologies in specific sectors, particularly in electronic manufacturing. It underscored the significance of promptly analyzing the evolutionary traits of these technologies within the industry and engaging in research and development endeavors to safeguard national technological security. To address this issue, the study initially extracted pertinent industry enterprises from the Orbis database. Subsequently, it utilized the technical codes associated with the patent data of these enterprises to establish a social network, pinpoint key technologies, and compute the technical share metrics for these pivotal technology codes. Numerous technologies are exclusively controlled by a limited number of enterprises, leading to the identification of bottleneck technologies. This, in turn, enables the determination of critical paths to reveal the developmental history and distinctive features of these bottlenecks. The research indicates that the electronic manufacturing industry faces various bottleneck technologies, which extend beyond chips to include production equipment, materials, processes, and inspection devices. Numerous technologies have a significant developmental background, necessitating substantial technological development to achieve parity. However, in swiftly advancing technological domains, China possesses the capability to make advancements at an accelerated rate.

Indexed as

ElectronicsManufacturing IndustryChinaHumansIndustryTechnology

Identifiers

PMID39700215
PMCPMC11658525

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.