Leading Change at Michelin's Shanghai Factory (B)
Bibliographic record
Abstract
这是关于变革管理的系列案例。它探讨一个来自海外、有文化与语言差异的厂长白乐涵怎样在上海的工厂实施变革。作为全球最老牌的轮胎公司，米其林拥有着最广为人知的轮胎品牌形象，在技术创新方面亦享有盛誉。2001年，米其林与中国最大的轮胎制造商上海轮胎合资成立了上海米其林回力，然而合资之后，上海米其林的业绩却成为所有米其林工厂中业绩最差的厂之一，工厂内部普遍存在对外籍管理层的信任危机，随后的停产裁员又为这样的矛盾雪上加霜。为此，米其林总部派遣具有丰富军事管理经验的白乐涵担任厂长以挽救危机。本系列共两个案例，B 案例描述白乐涵怎样在2008年7月到2011年末这期间改善业绩。在短短两年的时间内，工厂各项业绩指标有了大幅提升，质量达到亚洲最好，甚至超越美国的部分工厂。白乐涵究竟采取了什么方法力挽狂澜？如何赢回员工的信任？如何建立起高效人性化的管理团队？如何提高员工改善绩效的积极性？白乐涵的思路和方法，值得深思。
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.007 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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".