Factors influential to the acceptance of managerial accounting tools in Tra Vinh’s small and medium enterprises
Bibliographic record
Abstract
Managerial accounting tools are vital controlling techniques to businesses. Nevertheless, the acceptance of managerial accounting tools in business might challenge directors in Tra Vinh’s business environment. The current research employed multiple regression analyses to investigate the influence of the acceptance of managerial accounting tools in Tra Vinh’s enterprises. The empirical findings demonstrate the usefulness of managerial accounting tools, environmental uncertainty, the structure of corporate governance, organizational interdependence and organizational size have positive impacts on the acceptance of managerial accounting tools in business. The structure of corporate governance and the usefulness of managerial accounting tools are the two strongest factors determining the acceptance of managerial accounting tools in business. The current research will help directors in Tra Vinh’s enterprises establish efficient managerial accounting tools in business that are suitable to the usefulness of managerial accounting tools, environmental uncertainty, the structure of corporate governance, organizational interdependence, and organizational size, so that they can gain the best possible effectiveness.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".