An investigation on how TQM influences employee performance: A case study of banking industry
Bibliographic record
Abstract
This paper presents an empirical investigation to study the relationship between employee performance and TQM.The proposed study of this paper designs two questionnaires for TQM and performance measurement and distributes them among some employees who worked for one of Iranian banks in city of Semnan, Iran.The result of Kolmogorov-Smirnov test confirms that all data are normally distributed and the study uses Pearson correlation to investigate the relationship between various components of the survey.The result of the implementation of Pearson correlation ratio indicates that there was a positive and meaningful relationship between employee performance and TQM components (r=4.6223,P-value=0.000).In addition, there are some positive and meaningful relationships between TQM components and employee performance.The highest correlation belongs to relationship between employee performance and feedback (r=4.6223,P-value=0.000)followed by training and development (r = 0.441, Pvalue = 0.000) and communication (r = 4.2861, P-value = 0.000).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".