Intelectual capital Islamic work ethics and the performance of Bumiputera small and medium enterprises (SMES) experts views / Sakinah Mat Zin ...[et al.]
Bibliographic record
Abstract
Despite numerous efforts initiated by Malaysian government, Bumiputera entrepreneurs are still considered as incapable to compete with other groups in realizing business success. This study seeks to examine the intellectual capital (IC) and Islamic work ethics (IWE) that contribute to higher performance of SMEs among Bumiputera in Malaysia. In doing so, the measurement instruments are developed based on previous literature reviews and refined by expert validation. Informal interviews were held individually with 13 experts with the aims of gaining relevant and insightful information for IC, IWE and business performance cohesion. From a pilot study of 49 Bumiputera SME entrepreneurs, the findings indicate that intellectual capital components and Islamic work ethics are vital for performance management practices in the firm. Contribution/ Originality: Theoretically, this study generalizes intellectual capital and Islamic work ethics in SME setting and is a preliminary impetus for exploring Bumiputera intellectual capital, Islamic work ethics and business performance. Practically, it provides valuable references for entrepreneurs, giving a prioritized array of crucial resources that allows Bumiputera SMEs to sustain the competitive advantage.
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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 | 0.006 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".