Mergers, Acquisitions and Corporate Performance: The Balanced Scorecard Approach
Bibliographic record
Abstract
The broad objective of this paper is to evaluate the impact of mergers and acquisitions on corporate performance, using the five dimensions of financial performance, learning and growth, customer satisfaction, internal business process and environment. An ex-post study approach was used to extract pre- and post- merger information of selected banks in Nigeria, however, five banks formed the sample for the study. The data set consists of 11 years from (2000 – 2010), with five years pre and five years post analysis. Consequently, data obtained was then analysed using descriptive statistics and the paired t- test of differences as the problem under examination is a pre- and post- effect. The study finds a significant impact of mergers and acquisitions on the financial performance, customer satisfaction and learning and growth. However, the observed impact was not statistically significant in the environmental and internal business process performances (p>0.05). Against the backdrop of the findings, the study recommends the establishment of an environmental management and audit system, which will take cognisance of environmental management issues and also research and development initiatives should be planned, in other to achieve the best possible utilisation of organisations internal business processes.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".