The reciprocal relationship between affective organizational commitment and role overload: When autonomy need satisfaction meets the individual self‐concept
Bibliographic record
Abstract
This study examines the mediating role of autonomy need satisfaction in the reciprocal relationship between affective organizational commitment ( AOC ) and role overload over time, and the moderating role of the individual self‐concept. Using panel data collected at two points in time from 263 employees working for different organizations across various industries in China, we found that autonomy need satisfaction mediated a positive relationship from AOC to role overload over time. In contrast, the reciprocal sequential relationship from role overload to AOC through autonomy need satisfaction was non‐significant. Finally, the employees’ individual self‐concept acted as a moderator such that the relationship from autonomy need satisfaction to role overload over time was stronger (vs. weaker) when employees’ individual self‐concept was high (vs. low). We discuss the implications of these findings for future research on employee commitment, autonomy need satisfaction, and role overload. Practitioner points Autonomy need satisfaction was related to increased role overload over time. Affective organizational commitment was indirectly related to increased role overload through autonomy need satisfaction. The relationship from autonomy need satisfaction to role overload was stronger when the individual self‐concept was high. Employees’ sense of individuation is a central aspect of how role overload develops.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".