The effects of personality, deviant behavior, and employee engagement on frontline employees' organizational commitment
Bibliographic record
Abstract
This study aims to analyze the effect of personality on organizational commitment mediated and moderated by deviant behavior and employee engagement. The study was conducted at PT. Smartfren Telecom, Tbk in Malang City, involving 105 respondents of frontline employees and the collected data were proceed using Partial Least Square (PLS) analysis. The finding shows that personality did not affect the enhancement of employee's organizational commitment directly. Instead, personality was able to indirectly affect organizational commitment through engagement and a good personality will decrease deviant behavior. While deviant behavior itself did not influence organizational commitment, neither mediate nor moderate the relationship between personality and organizational commitment. Meanwhile, employee engagement was able to mediate the influence of personality toward the organizational commitment, but not to moderate the relationship between the two variables. The study places deviant behavior, and employee engagement were used as the mediating and moderating variables on the effect of personality on the organizational commitment of frontline employees. The highlight of this study is that deviant behavior was not able to act as both the mediating and moderating variable on the influence of personality on organizational commitment.
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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".