Sleepy but creative? How affective commitment, knowledge sharing and organizational forgiveness mitigate the dysfunctional effect of insomnia on creative behaviors
Bibliographic record
Abstract
Purpose This study investigates how employees' experience of suffering from insomnia might reduce the likelihood that they perform creative activities, as well as how this negative relationship might be buffered by employees' access to resources at three levels: an individual resource (affective commitment), a relational resource (knowledge sharing with peers) and an organizational resource (climate of organizational forgiveness). Design/methodology/approach Quantitative data came from a survey of employees in the banking sector. Findings Insomnia reduces creativity, but this effect is weaker when employees feel a strong emotional bond to their organization, openly share knowledge with colleagues and believe that their organization forgives errors. Research limitations/implications The limitations of this research include its relatively narrow scope by focusing on one personal stressor only, its cross-sectional design, its reliance on subjective measures of insomnia and creativity and its single-industry, single-country design. Practical implications The findings indicate different, specific ways in which human resource managers can overcome the challenges associated with sleep-deprived employees who avoid productive work behaviors, including creativity. Originality/value This study adds to extant scholarship by specifying how employees' persistent sleep deprivation might steer them away from undertaking creative behaviors, with a particular focus on how several pertinent resources buffer this process.
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.
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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".