How small companies capture value from their intellectual property: a qualitative study
Bibliographic record
Abstract
Innovative small companies often struggle to profit from their intellectual property (IP) due to various constraints, a challenge that remains under-researched. In our analysis of seven Canadian firms, we illuminate the ways these businesses maximize IP value. In doing so, we proposed a nuanced, resource-based view (RBV) framework. This framework reveals that small business managers first evaluate resource deficiencies for specific IPs. Following this, they pinpoint and implement compensating strategies linked to organizational resources, distinct IP forms, and networks. Consequently, small firms can harness the full potential of IP by adeptly evaluating resource gaps and applying appropriate compensatory measures. Moreover, this study underscores that the value that small firms derive from IP depends on their capability to resolve deficiencies with effective strategies. These insights not only advance our understanding of IP value capture processes in small firms but also offer actionable guidance for businesses and policymakers aiming to bolster innovative ecosystems.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".