The Negative and Positive Aspects of Employees’ Innovative Behavior: Role of Goals of Employees and Supervisors
Bibliographic record
Abstract
We aim to examine the negative (relationship conflict) and positive (in-role job performance) outcomes of employees' innovative behavior and explore the moderation effect of employees' goal content and supervisors' achievement goal orientation in these relationships. Data from 218 employees and their immediate supervisors were collected in companies in China and results show that employees' innovative behaviors are positively related to their relationship conflict and in-role job performance, and employees' extrinsic goals and supervisors' performance goal moderate these relationships. Specifically, employees' innovative behaviors were significantly and positively related to relationship conflict when either employees have high extrinsic goals or supervisor have high performance goals or both; and when supervisor have low level of performance goals, employees' innovative behaviors were significantly and positively related to their in-role job performance. We contribute in showing when there are positive and negative outcomes of employees' innovative behaviors and document the effect of moderating factors that may strengthen these benefits and lower the conflicts.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".