No place like home? The embeddedness of innovation in a regional economy
Bibliographic record
Abstract
Two views have come to dominate the debate on the globalization of innovation in the emerging knowledge-based economy. The first contends that globalization reduces the significance of the home base as the primary site for innovation, as firms increasingly source and apply their innovations on a global basis. The second view as articulated in the innovation systems approach contends that the institutionally embedded nature of the innovation process, which is a central feature of the new economy, demands a continued, and even accentuated, role for the local context. In this article, we seek to contribute to the debate by evaluating the extent to which the institutional context and local setting play an important role in determining the innovative behaviour of manufacturing firms in Ontario, Canada. Specifically, we compare the practices of 242 indigenous and multinational establishments with respect to in-house technological capabilities, innovative processes, external sources of innovative ideas, and the nature and the extent of innovative inter-firm practices. Our findings indicate that indigenous firms are more likely to perform innovative activities locally and are more embedded in the Ontario economy than their multinational counterparts, as they exhibit higher R&D intensity, have a larger proportion of scientific, technical and managerial employees, adopt innovative inter-firm practices more extensively, and are more likely to source innovative ideas from local customers. The multinational establishments, in contrast, tend to exhibit lower R&D intensity, are more reliant on their inhouse marketing units, and continue to rely on their parent companies as a primary source for innovative ideas. These results suggest that local context still exerts a significant influence on the nature and extent of innovative activities in the knowledge-based economy.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".