Bibliographic record
Abstract
本案例讲述了一家在企业云服务（Software as a Service，SaaS）赛道的创业公司从0到1的创立过程。ONES的产品是专门给软件开发人员使用的一套项目管理工具。这是企业级软件领域众多赛道中（如薪酬管理、客户管理、资源管理等）的一个细分垂直赛道，也是一个蓝海市场。ONES从产品策略、定价策略、收购策略等方面做出自己的判断和决策。ONES的创始人王颖奇是一名连续创业者，之前曾创立过一家互联网B2C的公司。 案例首先介绍了国内企业级软件行业现状，紧接着描述了王颖奇的个人成长和第一次创业的经历，为第二次创业作铺垫；接下来讲述了王颖奇创立ONES找方向、天使融资、制定产品策略、确立服务模式和收费标准的过程，为分析B2B创业的关键点提供内容；随后介绍了ONES的三次收购，为讨论初创公司是否应该收购提供材料。 案例结尾探讨的是现在ONES走过了从0到1的阶段，接下来应当如何持续增长？在拓展海外市场方面将面临哪些挑战？如何应对这些挑战？这些问题对于在企业服务赛道的创业公司具有普适性的借鉴价值，因为软件出海和其他行业（比如制造业）出海有所不同，不同于在海外建立供应链，企业级软件的出海需要更多考虑海外客户公司的文化、管理等“软”性层面的内容。另外，新创企业出海也不同于以往大多数企业在发展成熟后才向海外拓展。通过案例中王颖奇对自己两次创业的反思，还可以探讨有关连续创业者的特点、创业学习反思等问题。
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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.017 | 0.025 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".