The effect of total quality management on the financial performance by moderating organizational culture
Bibliographic record
Abstract
This study aims to learn the effect of the Total Quality Management dimensions, Top Management Support, Customer Focus, Process Management, Employees Participation, Employees' Empowerment, and Continuous Improvement, on financial performance by moderating organizational culture. The study population includes nine transport companies listed on the Amman Stock Exchange until the end of 2019. Alia Company and Royal Jordanian Airlines were excluded since its financial data formed extreme values when compared with the values of the rest of the companies. The study uses Multiple Linear Regression to test the hypotheses. The study found a statistically significant effect at the level of significance (α < 0.05) for both top management support, customer focus, employees’ participation and empowerment, by moderating the organizational culture on financial performance measured by return on asset for the Jordanian transport companies listed on the Amman Stock Exchange. In light of the statistical results, the study presented several recommendations, the most important of which was to increase the top management interest in cultivating a profound organizational culture towards learning, development, mastering performance and improving the quality of its services to attract customers, and distinguish the organization from other organizations, in a way that reflects positively on developing its financial performance.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".