Sleep-deprived and emotionally exhausted: depleted resources as inhibitors of creativity at work
Bibliographic record
Abstract
Purpose Within the theoretical frameworks of conservation of resources and job demands-resources (JD-R), the study aims to examine how sleep deficit could be negatively related to creativity at work by depleting critical resources of creativity. Design/methodology/approach The survey data were collected from 368 individuals nested in 40 teams at a call center. The authors conducted multilevel analysis to test the proposed hypotheses to account for the hierarchical nature of the data while simultaneously estimating the effect of predictors at different levels on individual-level outcomes and maintaining the predictors' level of analysis. Findings Through the data, the study presents how the depletion of resource, that is, emotional exhaustion, functions as a mediating mechanism that connects sleep deficit to creativity at work. Further, the study presents that higher job demands can worsen the negative effects of resource depletion on creativity at work because they further deplete resources needed for creative behaviors. Specifically, when sleep-deprived, those working in a high-task-interdependence climate are likely to experience emotional exhaustion more severely than do those in a low-task-interdependence climate. Also, the relationship between emotional exhaustion and creativity is more negative for managers than for non-managers because of managers' higher job demands. Practical implications By presenting sleep deficit-linked inhibitors of creativity at work, the authors highlight the importance of securing sufficient sleep and affective resources when designing jobs and HR practices in organizations. Originality/value This paper addresses the call for attention to examining the mechanisms through which sleep deficit affects employee creative behavior.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".