Sources of Synergy Realization in Mergers and Acquisitions: Empirical Evidence from Non-Serial Acquirers in Europe
Bibliographic record
Abstract
We empirically investigate the sources, magnitude, and timing of synergy realization for 293 M&As by non-serial listed acquirers in Europe during 1997–2005. In contrast to much of the existing literature, we find that the shareholders of non-serial acquirers gain significantly upon deal announcement. Next, we unravel the various sources of M&A value creation, in particular operating synergies resulting either from revenue enhancement or from savings on operating costs and investments, and financial synergies. Compared to its non-combining industry peers, the median combined sample firm reports a 4.92% larger sales growth rate by the third post-deal year. Operating costs relative to sales are reduced by an extra 1.53% over this same window. In leverage-increasing acquisitions, the median combined firm realizes a persistent 6.09% rise in its long-term debt ratio. Finally, our multivariate regression results point out that non-serial acquirers with a larger market-to-book ratio achieve more extensive operating synergies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".