Problems and Issues in Corporate Restructuring in the State-Owned Construction Sector in Vietnam: The Case of VINACONEX
Bibliographic record
Abstract
The study of corporate restructuring in state-owned enterprises has been a hot topic in the academic world. However, little study has been done in investigating the corporate restructuring in state-owned enterprises in Vietnam. This study is devoted to exploring the problems and issues of corporate restructuring in a specific construction company in Vietnam. This study aims to investigate what problems and issues arise in the corporate restructuring of a construction company. A typical five-level Likert item questionnaire was designed for the data collection. Data from 398 respondents show that the company’s restructuring decision was determined by the company’s internal and external factors. VINACONEX needs to pay more attention to management training for managers and to carrying out technological innovation. From the findings, we propose some solutions to deal with problems arising from the restructuring of VINACONEX. The results of the study provide more evidence for the theories about corporate restructuring and contribute to the growing knowledge in strategic management by using a specific Vietnamese case. In this study, we also draw some limitations and recommendations for future research.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| 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".