The Relationship of Human Resource Practices (HRP) Constructs With Turnover Intention Among Employees in Sarawak, Malaysia
Bibliographic record
Abstract
Competition within the service industry is getting more intense due to privatisation and rising number of business entities creating toward competitiveness in the market. The banking sector is known as one of the service industries with a high rate of turnover in Malaysia. Some of the reason employees choose to leave an organisation are such as arduous and strenuous job environment as well as demanding workloads. When more and more employees leave the organization, it will cause unfavourable impacts on a bank’s performance and productivity. Previous literatures have revealed the relatedness of human resource practices (HRP) with turnover intention (TI). 283 questionnaires have been distributed to bank employees in Kuching, Malaysia. The collected data was analysed in the aspects of correlation and regression where the results show that HRP are negatively related to employee’s turnover intention. Results from the research demonstrated the importance for bank employers to further enhance its existing HRP to minimize employees' turnover intentions. Furthermore, implications as well as recommendation for future study are also provided by this research. This study extends the knowledge of the effectiveness of human resource practices by incorporating the various effects of human resources practices on turnover intention from the employee perspective. This study also recommended few strategies for enhancement of present HRP to lower bank employees’ intention to quit the job.
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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 | 0.001 |
| 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 | 0.000 |
| 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".