Bibliographic record
Abstract
在淘宝、京东等巨头逐渐成为电商流量中心的趋势下，电商领域是否还会出现其他机会？云集、拼多多等成立3～4年便上市的企业给出了破局思路——社交电商。本案例介绍了社交电商领域代表性企业之一云集的发展历程和商业模式。 云集于2015年5月上线，2019年5月登陆纳斯达克，积累了近千万正式会员（即店主）和2,000多万买家。社交裂变、S2b2c模式、精选供应链等，成为云集快速增长的关键词。但在快速增长的同时，云集也遭到许多质疑，特别是其激进的拉新方式。对此，云集果断而又快速地对其商业模式进行了调整。在肖尚略看来，目前云集在各方面已完全合法合规。虽然未来仍存在着风险，但云集的商业模式还在不断调整。例如，2018年10月，肖尚略提出“会员电商”的转型方向，云集是否具备转型会员电商的条件？还有没有其他发展方向？
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".