Internal Control and Crisis Management: Insights from State- and Privately-Owned Enterprises in Ghana
Bibliographic record
Abstract
The paper examines the level of adherence to internal control measures and the relationship between internal controls and crisis management. Internal control, an essential tool for crisis management, has received less attention from scholars and practitioners in Ghana. The authors employed a survey and cumulative percentage research approach. Twenty enterprises from five sectors, namely: transport, service, energy, financial, and manufacturing, with 120 respondents from both state- and privately-owned enterprises in Ghana, were used in this study. The results indicate that less than a quarter of the respondents agree that both state- and privately-owned enterprises perform excellently in adhering to the 2013 COSO internal control model. However, the performance of privately-owned enterprises is better than that of state-owned ones. The study also finds a weak positive correlation between internal controls and crisis management in both state- and privately-owned enterprises in Ghana. The study recommends internal controls to be taken seriously with special attention on board members and management’s appointment, which should be based on their competence rather than political and other social ties. The authors conclude that an effective internal control system is crucial for overcoming a crisis in organizations.
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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) | 0.000 | 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) | 0.002 | 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".