Quality Management: An Index For Actual Practice And Managers Perception
Bibliographic record
Abstract
The reviewed literature indicates that TQM is a potential source of competitive advantage. Although the efficacy of quality management has been studied in detail, the link between quality practices and managers’ perceptions about TQM has received less attention. In this study, quality practices and managers’ perceptions were investigated to advance a much-needed theoretical base, including underlying assumptions. Specifically, an instrument was developed and applied at 20 retail/service and 10 manufacturing companies in a distinct region in Canada, to measure managers’ practices and perceptions on TQM dimensions. A quality index for each dimension allowed ranking and grouping of these dimensions. Additionally, case study research was conducted with a notable retailer of relevance to the region and Canada, and with a US manufacturing company noted for top-ranking on the top rated dimension-grouping, namely strategy, leadership and continuous improvement. The results suggest that studying managers’ perceptions and their practices can contribute significantly to understanding the potential advantages of TQM.
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".