The role of organizational commitment in the relationship between human resource management practices and competitive advantage in Jordanian private universities
Bibliographic record
Abstract
Human Resource Management (HRM) has the capacity of influencing the organizational behavior of the employees, thereby ensuring the achievement of the competitive advantage. This study proposes to assess the relationship between human resources (HR) practices and competitive advantage. It is also intended to test organizational commitment as a mediator, between HR practices and competitive advantage among the employees of the private universities in Jordan. The data were gathered from 232 individuals employed at ten private universities located in Jordan. PLS, SEM was performed on the data, using the SmartPLS 3 software. HRM practices result in a statistically significant variation in competitive advantage. Relationship of HRM practices and competitive advantage was partially mediated by organizational commitment. HRM practices resulted in a statistically significant variation in and organizational commitment. Our findings contribute to the existing body of literature of how organizational commitment can mediate the relationships among the HR practices adopted by organizations and competitive advantage. Jordanian private universities should improvise extra attention over HR practices that contribute positively toward the performance of employees.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".