Bibliographic record
Abstract
在巨头们鏖战的成熟市场，还有创业空间吗？新创企业如何进入并在其中立足？艾优用自己的实践回答了这个问题。 艾优是一家具有4年历史的消费品创业企业，它创业的与众不同之处在于，大部分创业企业在创业初期都只打造一个品牌，而它则陆续推出了分布在成熟市场不同赛道的7个品牌。切入每一个赛道，它都采取了颜值差异化战略。经过4年发展，2020年艾优年营收达12亿元，但它却将2025年的年营收目标设为100亿元。尽管艾优凭颜值差异化战略已取得了一定成果，但是消费者对颜值的偏好是感性易变的，它如何才能持续保持这种战略的竞争优势？要用这种战略在5年内实现超过8倍的增长，艾优将会遇到什么样的挑战？请同学站在艾优创始人和董事长曾瑞的角度来思考这些问题。
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.018 | 0.017 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.020 | 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".