Analyzing the Determinants of Crisis Management in Vietnamese State-Owned Enterprises During Economic Shocks: Evidence from Civil Servants in the COVID-19 Pandemic
Bibliographic record
Abstract
Crisis management can be essential in enhancing the working of state-owned enterprises.In global economic conditions, the operation of enterprises is developed in an insecure environment.The management of the crisis can be considered as a specific method of the stateowned enterprises in order to prevent and dominate proceedings that may endanger or impede the further existence of the enterprises.By systematizing theoretical issues and providing empirical evidence, the paper clarifies the influence of factors affecting crisis management at state-owned enterprises in the context of exogenous shocks like the COVID-19 pandemic.The paper uses the Exploratory Factor Analysis and the Analytic Hierarchy Process (AHP) technique to identify the influence of the factors on crisis management in state-owned enterprises with 259 civil servants.The findings show that the policy dimension is the most important factor that contributes 40% toward the overall crisis management, followed by the leadership traits and skills dimension (23%).Besides, this study proposes some recommendations to enhance the crisis management of state-owned enterprises in the context of exogenous shocks in Vietnam.
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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 | 0.001 | 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".