Workplace bullying, distrust in top management and diminished ethical voice behaviour: buffering effects of resilience and innovation propensity
Bibliographic record
Abstract
Purpose This study aims to leverage conservation of resources theory to investigate how and when the experience of resource-depleting workplace bullying may turn employees away from ethical voice behaviour. It unpacks the bullying – ethical voice link by postulating a mediating role of distrust in top management and moderating roles of two complementary personal resources (resilience and innovation propensity). Design/methodology/approach The hypotheses were tested with survey data collected from employees who work in the computer industry in Canada. Findings The empirical results reveal that a key mechanism that underpins the translation of repeated harassment at work into a refusal to speak up about ethical issues is that employees criticize top management for not being trustworthy. Employees’ ability to bounce back from adversity, as well as their intrinsic drive to generate novel ideas, buffers this harmful effect. Practical implications For employees who feel upset about being bullied, this study pinpoints a notable risk that might undermine their capability to address such behaviours; that is, they stop caring about the ethical performance of their employing organization. This risk can be averted, however, to the extent that they have a strong ability to recover from difficult situations or have an intrinsic motivation to find innovative solutions to such situations. Originality/value This research details the harmful effect of employees’ exposure to workplace bullying on their interest in sharing their opinions about ethical matters, as explained by their beliefs that organizational authorities cannot be trusted. It also explicates how this process can be mitigated if employees have access to valuable personal resources.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".