Perceived organizational politics, organizational disidentification and counterproductive work behaviour: moderating role of external crisis threats to work
Bibliographic record
Abstract
Purpose The purpose of this study is to unpack the relationship between employees’ perceptions of organizational politics and their counterproductive work behaviour, by postulating a mediating role of organizational disidentification and a moderating role of perceived external crisis threats to work. Design/methodology/approach The empirical assessment of the hypotheses relies on survey data collected among employees who work in a large banking organization. Findings Perceptions that organizational decision-making is marked by self-serving behaviour increase the probability that employees seek to cause harm to their employer, because they feel embarrassed by their organizational membership. This mediating role of organizational disidentification is especially prominent when they ruminate about the negative impact of external crises on their work. Practical implications This study details an important danger for employees who feel upset with dysfunctional politics: They psychologically distance themselves from their employer, which then prompts them to formulate counterproductive responses that likely make it more difficult to take on the problem in a credible manner. This detrimental dynamic is particularly risky if an external crisis negatively interferes with their work functioning. Originality/value This study adds to prior research by detailing an unexplored but relevant mechanism (organizational disidentification) and moderator (external crisis threats) by which perceived organizational politics translates into enhanced counterproductive work behaviour.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".