Economic gains around mergers and acquisitions in the construction industry of the United States of America
Bibliographic record
Abstract
As waves of mergers and acquisitions (M&A) have swept over American industrial business organizations, construction firms have been caught in the middle of the resulting turbulence. Nonetheless, no research has investigated these significant events in the construction industry. Built upon the financial theories and methodology, the overall success level of construction M&A transactions was assessed. The research findings, which were drawn from an analysis of 171 construction M&A transactions, indicate that the performance of construction M&A was positive at an insignificant level, as measured by equity market returns. Whereas the relationship between the type of diversification strategy and performance indicates that while the related diversification strategy has been slightly favored by both theories and empirical research findings over unrelated diversification, no significant performance difference was observed between two diversification strategies.Key words: mergers and acquisitions, diversification strategy, equity market returns.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".