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Record W7132402400

How the Lead-acid Battery Leader Tianneng Coped with Alternative Technologies

2024· other· W7132402400 on OpenAlexaff
Meng 芮萌, 陈炳亮

Bibliographic record

VenueCEIBS Institutional Repository · 2024
Typeother
Language
Field
Topic
Canadian institutionsCentre Casa
Fundersnot available
KeywordsBattery (electricity)Power (physics)Work (physics)Government (linguistics)Key (lock)
DOInot available

Abstract

fetched live from OpenAlex

天能电池集团股份有限公司(以下简称“天能股份”或“天能”)原本是一家亏损的村办企业,张天任于1988年接手,第二年就实现扭亏为盈。但之后由于下游市场需求快速萎缩,加上市场竞争激烈,张天任有了很强的危机感。 1998年,张天任决定对天能的业务进行全面转型,他瞄准了新兴的电动两轮车专用蓄电池。但同行都认为这一做法“不靠谱”,因为电动两轮车作为一个新兴事物,发展前景并不明确,而且对蓄电池的安全性和稳定性要求高,需投入很多资源进行技术突破。天能聘请专家不断改进产品,并成功研发出了一款新产品,其性能表现大幅领先同行,获得了电动两轮车厂商的大量订单。随着电动两轮车迎来大发展,中国成为全球最大的生产、消费和出口国,天能也跟随客户的成长而不断壮大。 由于铅酸电池平均1.5-2年就需要更换一次,存量替换的市场需求远远超过新车配套市场。近年来,天能在全国建立了一个经销商体系,直接招募了3000多家经销商,由他们去覆盖约定区域内的五金配件店以及修理店等终端门店,目前数量达到了40万家,形成了辐射全国的电池更换服务网络,渠道体系已成为公司的重要优势之一。 但是,在电动两轮车这一市场上,锂电池已显示出替代铅酸电池的迹象。锂电池在一辆两轮车的生命周期中更换可能性不大,天能的业务遭遇了严重挑战,需要为未来寻找新的增长空间。当前天能主要面临四大选择:一是继续发力铅酸电池,抢占剩余的市场份额;二是抢占铅酸电池的其他应用场景,如汽车的启动启停电源;三是发力替代电池技术,生产两轮车应用的锂电池;四是抓住电池应用增长最快的储能领域出现的机会。站在当下的十字路口,张天任应该带领天能跑向何方?

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.456
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0020.017
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0000.021

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 head0.026
GPT teacher head0.238
Teacher spread0.212 · 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; both teacher heads agree on what is shown here.

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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