Knowledge-sharing efforts and employee creative behavior: the invigorating roles of passion for work, time sufficiency and procedural justice
Bibliographic record
Abstract
Purpose Drawing from the conservation of resources theory, this study aims to investigate the relationship between employees’ knowledge-sharing efforts and creative behaviors; particularly, it addresses how this relationship may be invigorated by three resources that operate at individual (passion for work), job (time sufficiency) and organizational (procedural justice) levels. Design/methodology/approach Quantitative data were collected through a survey administered to employees in a banking organization in Mozambique. Findings The usefulness of knowledge-sharing efforts for stimulating creative behavior is greater when employees feel passionate about work, have sufficient time to complete their job tasks and perceive that organizational decision-making is fair. Practical implications The results inform organizations about the circumstances in which the application of employees’ collective knowledge bases, derived from their peer interactions, to the generation of novel solutions for problem situations is more likely to materialize. Originality/value By detailing the interactive routes by which knowledge-sharing efforts and distinct resources (passion for work, time sufficiency and procedural justice) promote employee creative behavior, this study extends prior research that has focused on the direct influences of these resources on knowledge sharing and creative work outcomes. It pinpoints the circumstances in which intra-organizational knowledge exchange can generate the greatest value, in terms of enhancing creativity.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".