Post-operating performance of construction mergers and acquisitions of the United States of America
Bibliographic record
Abstract
A previous study assessed stock market returns (ex ante expectations), and this study examines the actual operating performance (ex post-operating performances) of the mergers and acquisitions (M&A) observed during the past two decades (1980-2002) in the construction industry in the United States of America. Utilizing various statistical tools and longitudinal data analysis modeling techniques, three hypotheses were tested. First, the level of synergistic gains, measured as operating cash flow returns, was not improved significantly after firm integration. Second, regarding the management wealth maximization hypothesis, the size of firms dramatically increased after the integration of the firms, and the operating performance was slightly improved compared with that before the event. Research outcomes also indicated that the previous research findings concerning stock market returns on M&A were consistent with the long-term operating performance, and thus supported the market efficiency hypothesis. Lastly, M&A guidelines for the construction industry are presented based on the research outcomes from both stock market return and operating performance analysis. Key words: mergers and acquisitions, diversification strategy, operating performance.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".