SAIC Maxus: Pioneering the C2B Model in China's Auto Industry in the Digital Era
Bibliographic record
Abstract
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？
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".