L’évolution du modèle d’affaires des <i>start-up</i> par la numérisation : quel lien avec leur trajectoire de croissance ?
Bibliographic record
Abstract
La croissance des start-up représente un indicateur important permettant d’appréhender leur réussite. L’objectif de cet article est de comprendre les trajectoires de croissance de ces entreprises en lien avec l’évolution de leur modèle d’affaires, entraînée par la numérisation. Il s’appuie sur une étude de cas multiples menée auprès de quatorze start-up françaises et se concentre sur la représentation que donnent leurs dirigeants aux thématiques étudiées. Les résultats montrent que les start-up peuvent suivre deux trajectoires de croissance différentes. Ils apportent de nouveaux éléments sur leur cycle de vie en lien avec ces trajectoires. Enfin, l’article identifie trois reconfigurations possibles du modèle d’affaires des start-up grâce à la numérisation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 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".