Developing Competitive Advantage through Ethical and SR Practices: The Case of SME in Australia and Malaysia
Bibliographic record
Abstract
This study contributes to existing research by exploring the prevailing attitudes towards ethics and socially responsible considerations among Australian and Malaysian SME owners. Based on interviews conducted with 20 entrepreneurs from Australia and Malaysia who operated in the manufacturing and service sectors, a content analysis of the data revealed three clusters of ethical behaviours: (1) concern for ethical practices; (2) maintenance of honesty and integrity; and (3) taking responsibility and being accountable. The socially responsible behaviours that the respondents perceived to be important were grouped in four clusters: (1) responsibility towards society; (2) responsibility towards staff; (3) responsibility towards customers; and (4) responsibility towards entrepreneurship. The results showed that both Australian and Malaysian business owners considered and exercised ethical and socially responsible practices in their businesses. The study concludes by proposing a framework for empirically testing the links that ethical and social responsibility practices have with a firm’s competitive advantage.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".