Regards croisés sur l’agilité et l’innovation ouverte pour les PME de haute technologie
Bibliographic record
Abstract
Cet article se propose d’étudier la relation entre l’agilité et l’innovation ouverte au sein des PME de haute technologie. À visée exploratoire, il s’appuie sur l’étude de cas d’une PME spécialisée dans l’ingénierie, le conseil en informatique et l’innovation technologique. Nos résultats mettent en évidence une interconnexion dynamique entre les deux approches de l’agilité et de l’innovation ouverte, offrant une compréhension approfondie de leur influence mutuelle dans ce contexte. Ainsi, nous démontrons que les capacités de l’agilité peuvent stimuler et soutenir les pratiques d’innovation entrante et sortante, tout en soulignant que l’innovation ouverte contribue à les favoriser. Cependant, il est important de noter que ces capacités ne suffisent pas à surmonter toutes les barrières auxquelles la PME est confrontée dans le domaine de l’innovation ouverte.
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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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 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".