How spatial proximity facilitates distant search – a social capital perspective on local open innovation
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
Distant search has evolved from the open innovation literature as an efficient mechanism to access external knowledge from heterogeneous fields of expertise. Despite its popularity and proven benefits, companies face multiple barriers to benefitting from distant search. In this study, we explore a local open innovation approach in which the spatial distance between solution-seeking firms and problem solvers was deliberately reduced to combine the benefits of distant search with those of spatial proximity. We studied eight local open innovation events and found that spatial proximity supports the implementation of open innovation, overcoming challenges of initiating organisational change towards openness, establishing trusting relationships for knowledge exchange, and successfully applying the external knowledge. By identifying social capital as the key success factor in local open innovation, our study contributes to the theoretical foundations of open innovation by showing how the dimensions of social capital enable key actions in each process phase.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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