Exploring the Relationships among Sustainable Manufacturing Practices, Business Performance and Competitive Advantage: Perspectives from a Developing Economy
Bibliographic record
Abstract
This study aims to empirically test the relationships among the adoption of sustainability practices, businessperformance and competitive advantage in Caribbean manufacturing firms. Seven dimensions of sustainablemanufacturing practices are conceptualized and tested against measures of business performance andcompetitive advantage. Three hypothesized relationships are tested using the partial least squares structuralequation modeling (PLS-SEM) technique. The results show a negative relationship between the adoption ofsustainability practices and business performance. We also find that there is no significant relationship betweenthe adoption of sustainability practices and competitive advantage. However, we observe a significant positiverelationship between competitive advantage and business performance. Based on these findings, manufacturingfirms in developing regions, such as the Caribbean, are advised to pursue sustainability strategy implementationwith some vigor, but should base their choices on strategies that will enhance sustainability through improvedresource productivity, while improving business performance and 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".