The Impact of Human Resources Management on Employee Performance: Organizational Commitment Mediator Variable
Bibliographic record
Abstract
This study aims to examine the impact of the human resource management (HRM) policies on the organizational commitment and the performance of the employees at Jumhoruia bank in Libya. The study encompasses the policies factor as an independent variable and the factor of employee performance as a dependent variable. This study also intends to investigate the role of “organizational commitment” as a mediator variable between the polices of (HRM) and the performance of the employee, and to achieve these aims, the researchers have used the descriptive analytical method (quantitative) which represented using (CFA) in order to verify the structural truth of the study factors reaching to use (SEM-AMOS). The study is targeting all employees working in Jumhoruia bank, the headquarters and the branches in the capital city of Libya, Tripoli The study has concluded with many results, and one of the most important results is that, there is a positive relationship between the (HRM) and the employees’ performance. The study also found that there is an indirect positive effect to the (HRM) through the organizational commitment with a percentage higher than the direct impact. the researchers recommends that all policy makers of (HRM) should pay more concern on policies and practices related to the employees which results into developing the employees’ performance, also policy makers inside the bank should concentrate on emotional aspects of the employees which in turn result into a higher positive influence on their performance compared with the direct impact on their performances.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".