Individual and organizational learning from inter‐firm knowledge sharing: A framework integrating inter‐firm and intra‐firm knowledge sharing and learning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Literature has highlighted but not explored links between knowledge sharing and learning at inter‐firm and intra‐firm levels. Using the single case of an aviation refuelling company as the basis for our research methodology and collecting data through 34 semi‐structured interviews, we develop a framework that integrates knowledge sharing and learning at inter‐firm and intra‐firm levels. We show that intra‐firm knowledge sharing capabilities facilitate the diffusion of inter‐firm learning within organizations. Moreover, inter‐firm trust manifests in different forms that affect individual and organizational learning. The purpose of collaboration determines what a firm learns or discards. The findings are important for organizations facing a shortage of skills. © 2018 ASAC. Published by John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it