Stress episode in aviation: the case of China
Bibliographic record
Abstract
Purpose The purpose of this paper is to investigate the impact of role stressors on job stress among airline employees in mainland China. More specifically, the aggravating effects of shift work and the mitigating effects of decision latitude are explored to facilitate strategies of intervention aimed at reducing job stress. Design/methodology/approach Data are collected using a field survey in Mandarin from 485 airline employees, including pilots, flight attendants, and service employees in five major cities in mainland China. Findings The findings demonstrate that role overload and role conflict have significant positive effects on job stress. Furthermore, both shift work and its interference with non‐work activities significantly elevated the impact of role overload on job stress. Findings also reveal that decision latitude mitigated the detrimental effect of role overload on job stress for employees working on fixed shift, but not for employees working on rotating shift. Research limitations/implications This is a cross‐sectional study using perceptual measures. Practical implications The findings suggest that aviation managers in China need to focus not only on decision latitude but also on job and organizational design to mitigate the impact of job demands on stress. While decision latitude works to ease demands among those who work on fixed shifts, it does not work in the same way for those working on rotating shifts. Originality/value This paper corroborates the cross‐cultural applicability of stress theory by demonstrating the detrimental role of rotating shift on stress while at the same time calling attention to some cultural shaping of the findings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".