Developing Small and Medium Enterprises (SMEs) in a Transitional Economy-from Theory to Practice: An Operational Model for Vietnamese SMEs
Bibliographic record
Abstract
This paper examines the factors contributing to the growth of SMEs by using a conceptual framework derived from the concept of resource; cluster; networking; and institutional theories. The Vietnamese experience suggests that institutional weakness and lack of proper coordination between policy making, implementation and market conditions has made the support regime ineffective. Literature review indicates that Vietnamese government has mainly focused on increase the number of SMEs rather than improving the performance of SMEs and strengthening the business competitiveness. This must be facilitated by the critical entrepreneurial role of the state. Furthermore, this paper argues that no adopted model from one country to another country would be suitable without consideration. It is vital to address the issues of external business environment, market environment, and social culture. The paper then recommends that the evolving relationship between the state’s entrepreneurial role and market factors are parts of the success picture. More importantly, support policies may be invalidated by the unbalance relationship between the state and market. Unfortunately, such important relationship has not thoroughly been identified by the Vietnamese government.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| 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".