Bibliographic record
Abstract
21世纪的竞争不再是企业和企业之间的竞争，而是供应链和供应链之间的竞争。供应链的整合与创新不但可以帮助企业降低成本、缩短提前期、提高反应速度，而且还能支持企业提高创新能力、重塑流程与商业模式、提供新的价值主张，以及建立独特的竞争优势。众多研究及实践表明，供应链是企业实现转型升级的关键路径。目前，我国企业的供应链管理的总体水平还处于初级阶段，而数字化新时代对企业打造优质供应链提出了新的要求。正基于此，本书由中欧国际工商学院教授与研究团队通过实地考察与调研，为读者精选出来自零售、流通、技术/大数据服务等产业的八个典型案例，期冀行业从业者能从这些供应链与商业模式创新实践中得到一些有价值的经验和启示。本书每篇案例后还配有业界专家点评，解密其中的商业规则，引领读者拓展思路。
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 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".