The Effect of Successful Value-Based Management on Decision-Making Effectiveness, Business Value Creation, Corporate Competency, and Corporate Sustainability Based on the Perceptions of Accounting Directors of Thai Listed Companies
Bibliographic record
Abstract
The aim of this study is to examine the impact of VBM success on the corporate sustainability of Thai listed firms. The effects of successful VBM on decision-making effectiveness, business value creation, and corporate competency are also investigated. Both contingency theory and the relevant literature are utilized to aid in effectively comprehending the consequences of successful VBM. Thai listed companies were selected as the sample for this study, and data collected from 101 accounting directors through questionnaires were used as the research instrument. PLS-SEM was employed to test the hypothesized relationships. The results found that successful VBM has a considerable impact on company sustainability, owing primarily to indirect effects through mediating variables, such as business value generation and corporate competence, rather than direct effects, which are not significant. As a result, it is possible to conclude that good VBM implementation will increase business sustainability through processes or mediating variables, rather than directly affecting it. In addition, the success of VBM significantly improves the business value creation and corporate competency. Lastly, effective decision-making, the creation of company value, and corporate competency all significantly enhance corporate sustainability. Contributions from management and theoretical perspectives are openly provided. Recommendations, conclusions, and future study directions are also highlighted and discussed herein.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.011 |
| 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 | 0.003 | 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".