Technology Transfer Channels and Innovation Efficiency: Empirical Evidence From Chinese Manufacturing Industries
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
This article analyzes the effects of three channels of technology transfer—global value chain participation (GVCP), foreign technology import (FTI), and domestic technology purchase (DTP)—on innovation efficiency by using 11 years of data from Chinese manufacturing industries. Empirical results show FTI and GVCP significantly facilitate innovation efficiency, whereas DTP decreases it. Further, absorptive capacity (AC) positively moderates the relationship between FTI and innovation efficiency. Moreover, in the high-tech industry, we find that GVCP positively affects innovation efficiency, and AC positively moderates the effect of GVCP on innovation efficiency. This finding is informative from a strategic perspective as firms can make strategic decisions in the selection of technology transfer channels. In addition, firms may also absorb and apply external technologies while developing AC to improve enterprises' ability according to their own organizational and strategic contexts in order to achieve and maintain competitive advantages. This finding provides convincing empirical evidence on the relationship between technology transfer channels and innovation efficiency and valuable lessons to other developing countries for the selection of technology transfer channels.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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