Strategic SCM’s Mediating Effect on the Sustainable Operations: Multinational Perspective
Bibliographic record
Abstract
Abstract Background and Purpose: The comparative cross-sectional study examines the strategic supply chain management’s mediating effect on the sustainable operations through environmental and social sustainability within the businesses operating in Canada, Iran and Turkey to attain global perspective. Methodology: Over 200 small businesses in each country are included through combining purposive sampling, referrals, networking, and connections. For quantitative data analysis, the Smart partial least square structural equation modeling (SmartPLS-SEM) is employed. Results: Results showed that there is statistically significant positive mediating role of strategic supply chain on the sustainable operations (environmental and social sustainable) performances in all three selected economies. Findings further confirmed that within the multinational perspective, the SCM factors have higher significant positive impact within Canada in contrast to Iran and Turkey. Conclusion: This study offers a new theoretical contribution by examining the mediating role of strategic supply chain from multinational perspective to enhance existing body of knowledge. Furthermore, it offers a practical contribution by providing the strategic research framework to facilitate managers in improving the small businesses’ performance in sustaining operations.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".