We Know the Practice! Experience-based Antecedents of Cross-border Diffusion of Foreign Innovation
Bibliographic record
Abstract
In spite of longstanding academic interest regarding the diffusion of innovations, scholars have paid little attention to such diffusion across national borders. The diffusion of innovation is triggered on the basis of proven efficiency and understandability. In order for the practice to be transferable, objectification of the focal practice by using symbols is required on the transmitting side, a process that also requires interpretation on the part of the recipient. We consider a situation where prior performance is to a large extent proven in a foreign country, but understanding of the focal practice is relatively limited compared with domestic diffusion. In this case, understandability of the focal practice can be significantly limited since it becomes harder to interpret the objectified contents of the practice due to limited information and institutional distance between originating and adopting countries. We examine the mitigating influence of experience-based factors of individual organizations � specifically at the upper echelon level � on this barrier to cross- border diffusion of a foreign-born innovation. Results of Six Sigma diffusion among the largest 200 Korean firms provide general support for our hypotheses.
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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 | 0.003 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".