PERANAN CORPORATE STRATEGY DALAM KESUKSESAN-KEGAGALN MERGER & AKUISISI : SUATU TELAAH LITERATUR
Bibliographic record
Abstract
Most empirical studies and literature reviews documented that the final results of the wave \nof mergers and acquisitions in the United States, Canada, and European countries during the \ndecade of 1980s, 1990s and 2000s were always dissatisfactory. In fact, the extent of the failure is \nhigher than the success. \nHowever, a comprehensive investigation on the factors motivating the rise of mergers and \nacquisitions and the causes for success and failure is still rare. This paper reviews the \ncontribution of corporate strategy in success and failure of mergers and acquisitions during three \ndecades. Specifically, this paper reviews literatures with respect to the motives of corporate \nmergers and acquisitions actions and the trigger factors of their failures. \nThe result of the literature review shows that corporate strategy has a significant \ncontribution to the extent of the success and failure of corporate mergers and acquisitions. The \nreview finds that trigger factors of mergers and acquisitions failure are the ambiguous \ncommunications and cross-cultural gaps, inappropriate and insufficient integration and \ntransformation of new corporate culture, incompatible leadership style accustomed with a new \ncorporate climate, inappropriate corporate planning and internal consolidation, inappropriate \nanatomy of organizational internal factors, and erroneousness in choosing the partners and the \ntiming of mergers and acquisitions. To ensure the successful and sustainability of corporate \nmergers and acquisitions, therefore, top management and task force of mergers and acquisitions \nneed to accurately consider those internal and external organization factors.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.056 | 0.025 |
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".