Self-interested Knowledge Sharing Behavior: Examination of Role Overload
Bibliographic record
Abstract
Encouraging knowledge sharing is crucial for organizational success; however, employees are reluctant to share knowledge because it decreases their strategic advantage. It is essential for us to understand the different ways in which employees share knowledge (i.e., self-interested knowledge sharing behavior). Drawing from the stressor-emotion model of Counterproductive Work Behavior, we examine the indirect effect of role overload on two self-interested knowledge-sharing behaviors (i.e., knowledge hiding and manipulation) via negative affect. In a time-separated field study (n= 161), our analysis reveals that role overload is positively related to negative affect. Also, negative affect was positively associated with both self-interested knowledge sharing behaviors (i.e., knowledge hiding and knowledge manipulation). Finally, our analysis found that negative affect fully mediates the relationship between role overload and (a) knowledge hiding and partially mediates the relationship between role overload and (c) knowledge manipulating.
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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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".