How the pandemic has changed innovation collaboration in SMEs, as illustrated by four co-innovation projects
Bibliographic record
Abstract
The recent health crisis has particularly affected small- and medium-sized enterprises (SMEs). Some have had to temporarily close their doors. Others chose to innovate by developing new products to take advantage of the situation and survive. However, innovation is a risky strategy, so there are many failures. Innovation collaboration is one way of limiting these failures and increasing the chances of project success. Nevertheless, little is known about SMEs’ innovation collaboration practices in the context of a crisis, and even before the pandemic, and further research is needed. This study aims to understand the innovation process and the collaboration practices adopted by SMEs for their product innovation projects to cope with the pandemic, by comparing their pre-pandemic practices with those implemented at the start of the pandemic. Based on four successful product innovation projects in two different SMEs, our results show that, at the start of the pandemic, collaborations included a larger number of partners, involved in more stages of the innovation process, in order to accelerate the new product development and commercialization, rapidly provide the necessary resources and response to customer needs.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".