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Record W7132210949

Global Technology: How a Chinese Startup Competed with International Giants

2024· other· W7132210949 on OpenAlexaff
Yan 龚焱, 蔺亚男

Bibliographic record

VenueCEIBS Institutional Repository · 2024
Typeother
Language
Field
Topic
Canadian institutionsCentre Casa
Fundersnot available
KeywordsChinaGovernment (linguistics)GlobalizationFeature (linguistics)
DOInot available

Abstract

fetched live from OpenAlex

本案例讲述了一家初创公司,也是汽车制造业上游供应商——格陆博所处的垄断型市场环境及创立过程。这是众多以国产替代为目标的技术企业的一个缩影。在汽车线控底盘领域,一方面技术门槛高,另一方面博世、大陆等国际巨头占据90%以上的市场份额。在被庞然大物占领的市场中,格陆博占据了自己的滩头阵地并生存下来。 案例首先介绍了行业背景,包括线控底盘领域的相关政策、技术发展、市场规模以及竞争格局,特别是几个主要的海外巨头的历史和业务,为格陆博进入该市场做环境铺垫。然后描述创始人刘兆勇的工作经历和创业动机,说明他选择这一领域、做国产替代、与海外巨头抢夺市场的缘由和背景。紧接着讲述格陆博如何一步步打磨产品并获得客户信任,实现从0到1的跨越。最后提出格陆博当前所面临的挑战:如何进一步与国际巨头竞争?

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.055
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0130.011
Scholarly communication0.0140.010
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0170.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.244
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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