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Record W7132469245

SAIC Maxus: Pioneering the C2B Model in China's Auto Industry in the Digital Era

2021· other· W7132469245 on OpenAlexaff
Yue 方跃, 钱文颖

Bibliographic record

VenueCEIBS Institutional Repository · 2021
Typeother
Language
Field
Topic
Canadian institutionsCentre Casa
Fundersnot available
KeywordsAuto industryDigital eraIndustry 4.0Industrial RevolutionHistory of computing
DOInot available

Abstract

fetched live from OpenAlex

本案例深入探讨了一个普适性问题:中国制造业企业的传统模式主要是以产品为中心,通过扩大产能、扩大经销商渠道实现利益获取。随着中国经济增速的放缓,这种模式不仅带来了生产过剩、市场饱和的问题,同时也无法满足消费者的个性化需求。数字化时代,传统制造业企业需要转变模式、转型升级,那么如何起步呢? 上汽大通是一家中国的汽车制造厂商,成立于2011年。它从2016年开始探索C2B(Customer to Business)模式,从以产品为中心转变为以用户为中心,从大规模标准化生产变成了个性化智能定制。但要实现这一转变,不仅仅需要模式创新,还需要对汽车厂商进行全流程的数字化改造。 在市场尚无成功先例的情况下,上汽大通是如何从0开始摸索出C2B模式的?上汽大通的C2B模式对传统的汽车价值链进行了哪些数字化改造?在未来的发展中,上汽大通C2B模式还面临哪些挑战呢?

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.756
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0010.003
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0040.013
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.239
Teacher spread0.224 · 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 designSimulation or modeling
Domainnot available
GenreEmpirical

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
Published2021
Admission routes1
Has abstractyes

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