Breaking the flow: how do workplace hazing and co-worker bullying disrupt employee knowledge sharing?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose Employees’ failure to share knowledge ruins organizational performance and innovation worldwide. Drawing on the job demands-resources (JD-R) model, the present study aims to explore how workplace hazing (WH) and co-worker bullying affect knowledge sharing (KS) via workplace alienation and fear-based silence (FBS) – an unexplored serial mechanism. In addition, it examines friendship prevalence (FPP) as a moderator in the association between FBS and KS. Design/methodology/approach A time-lagged study on 319 IT industry employees from Northern India, using partial least squares structural equation modeling to test hypothesized relationships. Findings The findings reveal that WH and co-worker bullying lead to workplace alienation among employees. Furthermore, results confirm workplace alienation and FBS as serial mediators. However, FPP does not moderate the association between FBS and KS. Practical implications The authors' findings suggest that expecting employees to engage in positive voluntary behaviors, such as KS, without tackling the challenges that deplete the work environment’s social capital may be quixotic. Thus, managers must give close and thoughtful attention to preventing and remedying WH and co-worker bullying to encourage employees’ voluntary behaviors, such as KS. Originality/value Past research has underscored the importance of an encouraging work environment in the knowledge creation and exchange process; hence, by administering the theoretical framework of the JD-R model, this study meaningfully contributes to the extant literature on hostile workplace conditions, namely, WH and co-worker bullying in influencing employees’ KS. Further, the results elucidate the dynamics of the sequential role of work alienation and FBS, offering constructive awareness to practitioners’ organizations.
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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 | 0.003 | 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it