Freshippo: A New Species in Chinese Retail (B)– Data-Driven Core Competencies
Bibliographic record
Abstract
这个(A)、(B)系列案例主要呈现盒马在零售市场如何利用大数据资源、借助新技术打破传统线上、线下边界，创造新的零售商业模式。与硅谷式的“从0到1，再从1到n”精益创业的思路不同，盒马在“1”尚未形成时，就开始了模式的复制。这个系列案例的特别之处在于，它包含两个逐层递进的90分钟教学计划，不仅可以帮助同学理解商业模式蓝图的9个模块及其之间的契合度、联动关系，还可以帮助同学理解数据和新技术能如何驱动商业模式创新。更进一步，它还能激发同学去思考，如何以战略的视角去捕捉商业模式的创新点。甚至，它还能启发同学去辩证地思考在创业时是否要遵循硅谷式的从0到1，再从1到n的创业思路及客户开发模型。 案例(B)主要描写盒马商业模式成立背后的数据和技术驱动因素。盒马之所以能跨越线上线下零售边界，就在于整合应用了移动互联网、云计算、大数据和人工智能等技术，实现了兼容“全渠道超市”和“移动电商”的新零售模式，并由此实现了消费者和门店随时随地、线上线下的互动。
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 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".