Exploration and exploitation of imported technology: their effects on indigenous 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
It is widely reported that the import of foreign technology can have two opposing effects on indigenous firms’ improvement of innovation capability: the substitutive effect, meaning the import of foreign technology curtails indigenous technological development and creates a reliance on foreign technology, and the complementary effect, meaning the import of foreign technology generates indigenous R&D effort and subsequently helps upgrade indigenous innovation capacity. Drawing from the knowledge-based view, we argue that there are two learning behaviors involved when importing foreign technology – exploitation and exploration. A focus on the exploitation of imported technology will generate a substitutive effect, while a focus on the exploration of imported technology will lead to a complementary effect. The two relationships are further moderated by indigenous firms’ export orientation and foreign equity involvement. Empirical analysis based on a 10-year panel data set from China supports most of the predictions.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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