Plant location, ISO 9000 certifications and quality management practices
Bibliographic record
Abstract
Purpose The main purpose of this study is to examine the impact of the country in which a manufacturing plant is located on its ability to achieve one or more of the ISO certifications, and the extent to which six other quality management practices have been implemented. It also examines the impact of achieving world class manufacturing status (WCM) on product quality. Product quality was measured by finished‐product first‐pass yield, scrap and rework costs, and warranty costs as percentages of sales. Design/methodology/approach The analyses are based on empirical data collected from more than 2900 manufacturing plants in the USA Canada, and Mexico. Findings The results show that there are significant differences in the plants' efforts to achieve quality certifications. Significant differences were also found in the extent to which six other quality management techniques are implemented. More important, our results show that there are significant differences in product quality performance among plants with different levels of progress toward achieving WCM status. Originality/value The findings of this study have many implications for both academic and practitioners who are interested in studying the impact of ISO 9000 and Quality Management practices.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".