Is supervisory communication more important than co-worker communication for employees’ engagement behavior in China? A moderated mediation analysis
Bibliographic record
Abstract
BACKGROUND: Past research has demonstrated connections between emotional intelligence and organizational citizenship behavior. However, how they are connected has been rarely explored, especially from a communication perspective. OBJECTIVES: This study considered the mixed role of co-worker communication satisfaction and supervisory communication satisfaction in the relationship between emotional intelligence and organizational citizenship behavior. METHODS: Based on a two-wave survey of 230 employees in China, we conducted a moderated mediation analysis using the PROCESS Macro in SPSS. RESULTS: We found that co-worker communication satisfaction (CCS) was a mediator in the relationship between emotional intelligence (EI) and organizational citizenship behavior (OCB). On top of that, the relationship between CCS and OCB became more significant when supervisory communication satisfaction (SCS) was at a high level. In contrast, that relationship became non-significant when SCS was at a low level. CONCLUSIONS: These findings extends the pathway research between EI and OCB, primarily through the lens of communication. Also, this work verifies the different values of types of communication satisfaction as resources. It extends the Conservation of Resources Theory in the Chinese context by integrating cultural traits with employee behaviors.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".