Sustainable Growth in SMEs: A Review from the Malaysian Perspective
Bibliographic record
Abstract
The importance of Small and Medium Enterprises (SMEs) contributions to the nations’ economies in the world is an undebatable fact. The same applies to Malaysia with 98.5% of the total business establishments being SMEs; contributing to 65.3% of total employment and 36.3% of GDP. Supports from the Government are never fading with huge allocations of budget every year but yet registering high failure rate. Sustainable growth of SMEs is long overdue. The awareness of the importance of sustainable growth of SMEs has resulted in the presence of various definitions and concepts of sustainable growth. This paper seeks to explore the literature on long-term and sustainable growth for SMEs and the enhanced knowledge on this area willbe aguidance to the policy makers, supporting agencies, advisors, entrepreneurs and academicians to seriously develop an all-encompassing model for sustainable growth of SMEs. This paper suggests an integrated sustainable growth model of SMEs with four dimensions of the economic factors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".