UNDERSTANDING THE SPECIFIC CHARACTERISTICS AND DETERMINANTS OF OPEN INNOVATION IN SMALL AND MEDIUM-SIZED ENTERPRISES: A SYSTEMATIC LITERATURE REVIEW
Bibliographic record
Abstract
Open Innovation (OI) assumes that businesses combine external and internal ideas as the primary means to accelerate internal innovation or access the market to commercialise their technologies. In the last decade, research interest has increased towards understanding OI in small and medium-sized enterprises (SMEs). Given the fast pace with which the literature has been developing in this area, there is a strong need to revisit the literature to investigate nuances, ambiguities and differences of opinion. This paper aims to systematically review OI in SMEs and survey the current state of his characteristics and determinants. 130 papers published in peer-reviewed journals are analysed. Findings suggest OI in SME differs considerably from OI in a large business, in terms of characteristics and determinants. The originality of the paper is rooted in the conceptual framework that illustrates how characteristics and determinants of OI in SME relate to each other in terms of input-output.
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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 | 0.009 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.025 | 0.024 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".