Impact of lean supply chain practices on competitive advantage in the private hospital sector in Sri Lanka
Bibliographic record
Abstract
Lean Practices have been implemented by private hospitals to get counterproductive solutions for reducing costs and gaining a competitive advantage. This research aims to examine the significance of lean practices on competitive advantage in the Sri Lankan private hospital sector to fill the knowledge gap. This research used a quantitative approach in which primary data was collected through a questionnaire-based survey and an analysis was conducted using structural equation modeling using the SmartPLS software. The research reveals the level of impact of lean practices, 5S, Kaizen, Kanban, and Just in Time in achieving a competitive advantage in the private hospital sector. Studies have demonstrated a significant impact of adopting the Just in Time approach in comparison to other established lean practices within the Sri Lankan private hospital sector, highlighting its unique and valuable contribution for health services. Researchers demonstrated when comparing Just in Time with other chosen lean practices for the study from the perspective of supply chain professionals, Just in Time contributes significantly to the competitive advantage of the Sri Lankan private hospital sector.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".