Funding Access and Innovation in Small Businesses
Bibliographic record
Abstract
The study examined the extent to which lack of access to external funding constitutes a barrier to innovation for small businesses operating in traditional industries. The findings indicate that, these businesses do not view lack of access to funding as a barrier to innovation for any of the four types of innovation: product, process, marketing, or organizational. However, for most of the innovations they promoted, the levels of innovation were relatively low, and which naturally entails relatively low risk to businesses. The findings also indicate that, there is a relationship between product and marketing levels of innovation and lack of access to external funding. The study’s contribution lies in its focus on small businesses operating in traditional industries—businesses which though, essential to economic growth, have garnered less separate attention in the innovation sphere. The study points to a vicious circle in which these businesses do not promote innovation at high levels that would advance their own competitive advantage and require external funding. Because this funding is not within their reach, they continue promoting low-level innovation, and so on and so forth. The study may practically contribute by assisting policymakers as they draw plans dedicated to supporting innovation in small businesses.
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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 | 0.004 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".