The association between interpersonal conflict, turnover intention and knowledge hiding: The mediating role of employee cynicism and moderating role of emotional intelligence
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
Academia is prone to incivility and interpersonal conflict like any other workplace environment, although incivility in academia is manifested in behaviors such as undermining colleagues’ professional standing, intelligence and authority; reprobating other’s accomplishments; and hiding knowledge from other faculty members. The autonomy, independence, academic freedom, and tenure in academia lead to a working environment (culture) with different “rules of engagement”, governed by the faculty members themselves. This study examines the impact of employee cynicism on faculty’s interpersonal conflict as a source of stress, which leads to undesirable organizational behaviors, namely higher turnover intention and knowledge hiding behavior; furthermore, the role of faculty’s emotional intelligence as a moderator on the relationship between interpersonal conflict among faculty members and turnover intention has been investigated as a second objective of this study. The study uses a quantitative method of research and analysis, by collecting data from 200 faculty members in private higher education institutions. The study’s hypotheses were tested by Smart PLS3 (SEM) to conclude that: 1) interpersonal conflict directly influences turnover intention and knowledge hiding behavior; 2) employee cynicism has no mediating effect in the relationship between interpersonal conflict, and turnover intention or knowledge hiding behavior; 3) Faculty’s emotional intelligence moderates the relationship between interpersonal conflict and turnover intention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 it