When degree of integration mediates level of acquired ownership and post-acquisition innovation performance: evidence from cross-border technological acquisitions
Bibliographic record
Abstract
Purpose The purpose of this study is to test a model for cross-border technological acquisitions (CBTAs) focusing on the level of ownership acquired in the target firm and the acquiring firm's post-acquisition innovation performance (PAIP), with the degree of integration as a mediator, based on the dynamic capability perspective of the resource-based view. This study further concludes the role of the country-of-origin effect (COE) (when emerging economies' acquiring firms purchase technological resources from developed economies' target firms) on the success of the acquiring firms in CBTAs. Design/methodology/approach Data on CBTAs initiated by 542 acquiring firms was quantified from four high technology industries from 1995 to 2015 for the empirical investigation of the research hypotheses. Hierarchical fixed year effect negative binomial regression technique was used to analyze the proposed model for the success of CBTAs. Findings The analysis of the CBTAs confirmed that acquiring firms who opt for a higher level of acquired ownership strategy increase the degree of integration of the target firm's technological resource stock. The level of acquired ownership improves the PAIP of the acquiring firms; however, the degree of integration positively accelerates the relationship between the acquired ownership and the PAIP. Considering the COE, acquiring firms that initiated CBTAs from emerging economies to purchase technological resources from developed economies' targets have firm-specific technological capability holes to execute the integration, which negatively impacts the emerging economies acquiring firm's PAIP. Originality/value This study contributes to the CBTAs literature by exploring the enabling role of the degree of integration between the level of acquired ownership and the PAIP of the acquiring firms. Further, this study put forward empirics on the COE of the acquiring firms for their integrative capability to integrate the target firm's resource stock and subsequent innovation performance.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.002 | 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 teacher head, 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".