Which types of firm use collaborative innovative spaces?
Bibliographic record
Abstract
Collaborative innovation spaces (CIS) can bring together multiple actors to enhance creativity, collaboration and knowledge exchange, sometimes leading to innovation. In this paper, we suggest that CIS can be categorized into three broad types (internal to the firm, external and virtual) and that each type is related to innovation processes, knowledge‐sourcing and geographic context in specific ways. Our results, based on an original firm‐level survey, reveal that there is heterogeneity with respect to firm attributes and innovation activities associated with different types of CIS. In particular, whilst innovation is associated with the use of CIS in general, radical and technological innovations are more strongly associated with internal CIS, whereas smaller firms tend to use virtual CIS. External CIS, whilst not associated with technological innovation, are associated with high‐tech firms. CIS use does not vary across geographic context. These results emphasize the importance of in‐person, internal, CIS for radical and technological innovation and the need to distinguish between different types of CIS in order to understand how each is associated with different types of innovation, knowledge‐sourcing and firm.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".