The Impacts of Total Quality Management, Human Resource Management, and Agility in Business on Firms Financial Performance: Moderating Role of Emerging Business Competition
Bibliographic record
Abstract
The current study explores the nexus of total quality management, human resource management, Agility in business, and firms’ financial performance. The current study's objective also investigates the moderating impact of emerging business competition among the nexus of total quality management, human resource management, Agility in business, and the firm's financial performance. The primary data has been gathered by using questionnaires from Chinese organizations' employees, while smart-PLS has been executed for analysis. The results exposed that total quality management, human resource management, and Agility in business positively associate with firms’ financial performance. The output also shows that the emerging business competition moderated among the nexus of total quality management, human resource management, and firms’ financial performance. These outcomes are suitable for the regulation-making authorities who want to develop quality and human management policies that could increase the firm performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".