Modes of innovation in an emerging economy: a firm-level analysis from Mexico
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
Firms that combine both the science, technology, and innovation (STI) and learning-by-doing, learning-by-using, and learning-by-interacting (DUI) modes of innovation are more likely to attain innovation outcomes than those employing either mode separately. Different studies across Europe and Canada support this proposition to different extents. However, the core of these studies has been carried out in advanced economies, inadvertently neglecting other relevant innovation milieus. This study examines the nuances of such innovation strategy in an emerging economy context. We explore differences and potential limitations in the existent literature. The analysis covers 9 628 Mexican firms with 10 or more employees. The results of the logit regressions suggest that a combined STI and DUI innovation approach yields better results in terms of product innovation. Contrary to the existing literature, our results point out that in an emerging economy context, the weight of DUI mode of innovation is larger on product innovation than the STI mode. Finally, DUI mode has a greater impact on process innovation than STI mode as well as the combination of STI and DUI; thus, showing that the benefits of combining STI and DUI are limited only to product innovation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.019 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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