Unraveling the Influence of CSR on M&A Decisions - The Effect of CSR on Target Choice and M&A Premiums
Bibliographic record
Abstract
This thesis examines the impact of Corporate Social Responsibility (CSR)\non Merger and Acquisition (M&A) decisions. Specifically, the study assesses\nhow CSR affects the selection of target companies and deal premiums. The\nanalysis is based on a dataset of 333 transactions involving acquirers based\nin the United States, Canada, and Western Europe. The findings reveal that\na higher CSR score for the acquiring company increases the likelihood of the\ntarget company having a higher CSR score, suggesting that the target’s CSR\npractices significantly influence the selection process. Additionally, the analysis\nreveals that the CSR score of the target company notably impacts the deal\npremium. Furthermore, when assessing the individual pillar score’s effect on\nthe deal premium, it is found that only the governance pillar has a significant\neffect on the deal premium.\nKeywords:
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".