Eternal Asia: From a Supply Chain Service Provider to a Supply Chain Ecosystem Leader
Bibliographic record
Abstract
怡亚通是一家在供应链服务领域摸爬滚打多年的企业,凭借对供应链大刀阔斧的改革与持之以恒的创新试验,怡亚通的体系越发展越庞大,涵盖的业务也越来越繁多。它致力于打造一条完善的端到端供应链,并将每个供应链环节发散为独立的垂直业务子平台,使得自身升级为“平台的平台”。 本案例将聚焦怡亚通在发展过程中所直面的三个关键问题:第一,怡亚通如何通过技术对传统供应链服务进行改造?第二,如何进行供应链整合与服务创新?这些供应链整合与创新如何为客户创造价值?第三,怡亚通的服务生态系统庞大全面,如何管理这些星罗棋布的子平台使其保持形散而神不散?如何进行不同业务模块的协调,保持庞大体系的灵活性?通过以上问题,本案例展示了怡亚通供应链服务创新实践的详细步骤,引导学员理解传统供应链服务模式转型升级的策略、工具、挑战及解决方案。
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.153 |
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; both teacher heads agree on what is shown here.
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".