Multilevel Interaction Mechanisms Influencing Knowledge Integration in Innovation Projects Reflecting Elements of Entrepreneurial Culture
Bibliographic record
Abstract
Research objective: The paper explores the impact of interaction mechanisms on knowledge integration in Complex Products and Systems innovation projects, reflecting entrepreneurial cultures, by challenging prevailing knowledge-as-possession viewpoint discussions. Design: Semi-structured interviews from two case-study manufacturers and affiliated suppliers were used to collect data to be analysed with Template Analysis and cross-case analysis. Results and contribution: Results reveal diverse interaction mechanisms, spanning structural, processual, and behavioural types, and their effects, influence knowledge integration, mirroring entrepreneurial cultures. Our framework contributes by identifying minimally related phenomena that influence knowledge integration. Our suggestion to permeate structural and processual mechanisms with behavioural interactions facilitates conceptual integration, broadening the understanding of interaction mechanisms' impact on knowledge integration and providing a nuanced view of entrepreneurial cultures.
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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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".