Bibliographic record
Abstract
在颠覆式创新理论的影响下，创业企业在进入传统行业进行数字化创新创业时，大都直接瞄准行业的痛点问题，利用先进技术推出创新解决方案，从不被行业既存者注意的低端市场起步，试图逐步向主流市场渗透直至颠覆既存者。然而，历史数据表明，通过颠覆式创新成功颠覆传统行业的创业企业很少，大部分创业企业都遭到了既存者的强烈抵制，甚至夭折在创业的路上。那么，除了颠覆式创新，创业企业还能通过什么样的创新战略在传统行业获得成功？众安的案例给出了另一种答案。在创业的8年间，众安践行了与传统保险不一样的价值主张：向用户提供风险保障服务，而不是提供只有出险后才能用上的保险产品。通过产品和服务创新，众安不仅开拓了自己的生存空间，也为行业带来了增量市场；同时，众安还通过科技输出赋能其他企业以打造共享价值的生态。由此，众安走出了一条与传统保险共存的发展路径。2021年10月，众安又发布了数字保险生态立方计划，意欲开拓具有更大行业跨度的生态。至此，众安CEO姜兴面临着一个战略抉择：众安的生态版图如何延伸？众安是应该继续采取与传统保险共存的创新战略，还是应该启动它对传统保险行业的颠覆之旅？
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.000 |
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".