The Relationship between Perceived Supervisor Support, Perceived Organizational Support, Organizational Commitment and Employee Turnover Intention
Bibliographic record
Abstract
This study aims to investigate the influence of perceived supervisor support, perceived organizational support and organizational commitment towards employees’ turnover intention. It has been discovered through previous literature that perceived supervisor support, perceived organizational support and organizational commitment are associated with employees’ turnover intention. This study collected data from 260 respondents selected from eight three-star hotels in Kota Kinabalu area. Each of the independent variables - perceived supervisor support, perceived organizational support and organizational commitment were regressed towards employees’ turnover intention (dependent variable). The findings show that there is a significant relationship between perceived supervisor support, perceived organizational support and organizational commitment towards employees’ turnover intention. This study suggests that more attention shall be given from the hotel management towards the employees to reduce the turnover intention. Apart from that, the study was able to gather some useful information for the hoteliers and managers pertaining to the respondents’ profile and what exactly the employees expect from the organization.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".