How, Why, and When High-Involvement Work Systems Are Related to OCB: A Multilevel Examination of the Mediating Role of POS and of the Moderating Role of Organizational Structures
Bibliographic record
Abstract
Drawing on signaling and social exchange theories, we proposed and tested a multilevel model of antecedents of organizational citizenship behavior (OCB). More specifically, this article examines how, why, and when high-involvement work systems (HIWS) are related to employee and team citizenship behaviors. Using a sample of 568 respondents in 46 teams, our results indicate that HIWS are directly and indirectly related to team-level OCB through the team perceived organizational support (POS) climate. Structure was found to act as a significant internal contextual factor. More specifically, we found that decentralization and formalization foster the positive link between HIWS and POS, while the indirect relationship between HIWS and team-level OCB through POS was weaker when the degree of formalization was low, and stronger when this structure element was high. Finally, consistent with Ehrhart and Naumann’s group norms theory of OCB, team-level OCB was positively related to employee OCB, regardless of whether task interdependence is high or low. This study contributes to the understanding of processes and contextual conditions through which teams and employee citizenship behavior are related to HIWS.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".