Contraintes financières et innovation dans les PME
Bibliographic record
Abstract
L’objectif de ce travail consiste à étudier l’impact des contraintes financières sur le comportement innovant des petites et moyennes entreprises. Nous partons de la méthodologie de Fazzari, Hubbard et Petersen (1988) qui suppose que dans un contexte d’asymétrie d’information, la sensibilité de l’investissement à un indicateur de la richesse interne de l’entreprise implique l’existence de contraintes financières. Les résultats dégagés à partir d’un modèle Logit, mené sur un échantillon de 117 PME, montrent l’impact positif et significatif du cash-flow sur l’investissement innovant, ce qui implique une sensibilité de l’innovation aux ressources internes et confirme que les PME innovantes sont contraintes financièrement. D’autres investigations mettent en évidence une sensibilité plus importante pour les entreprises engagées dans des activités de recherche et développement, censées être plus exposées aux contraintes quant à l’accès au financement externe.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".