DETERMINANTS OF PROPENSITY VS. INTENSITY OF INNOVATION CO-OPERATION FOR SMEs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
For small and medium-sized enterprises (SMEs), innovation co-operation represents a promising avenue to get around limitations and increase their innovation capacity. But under which conditions are firms more susceptible to engage in such ventures? The purpose of this research paper is to further our understanding of the factors contributing to innovation co-operation for manufacturing SMEs from the firm’s perspective. Following an online and telephone survey with SME managers ([Formula: see text]), we studied the presence or absence of innovation co-operation. We subsequently investigated the intensity of innovation co-operation with market partners (clients, competitors, consultants, and suppliers) and research partners (laboratories, post-secondary education institutions, technology transfer centers, and universities), addressing gaps in a literature dominated by binary analysis. Our empirical analyses suggest that innovation co-operation is promoted by several key determinants. However, it highlights there are many important differences in the determinants of propensity vs. intensity of innovation co-operation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it