The impact of technological similarity on overseas post-M&A innovation performance: based on the dynamic moderating role of resource dependence
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
Technology-sourcing overseas mergers and acquisitions (M&As) are crucial for firms seeking technological advancement, yet many struggle to integrate acquired technical knowledge effectively. This study examines Chinese firms’ technology-sourcing overseas M&As from 2008 to 2018, analysing how technological similarity between the acquirer and the target affects post-M&A innovation. Results disclose an inverted U-shaped relationship: moderate similarity enhances knowledge absorption, integration, and utilisation while reducing conflicts, but excessive similarity creates redundancy that hinders innovation. Asymmetric dependence and joint dependence weaken this effect, though their influence diminishes over time. This study provides evidence-based recommendations for Chinese firms on M&A target selection and post-M&A management.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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