Exploring the effect of perceived fun at work on hospitality employees’ behaviors in and out of work
Bibliographic record
Abstract
Purpose The purpose of this study is to draw on positive psychology literature and the affective spillover theory to gain a comprehensive understanding of the effects of perceived workplace fun (WF) on hospitality employees’ behaviors in and out of work. Design/methodology/approach Multirater data were collected via surveys from 247 hospitality employees and their direct supervisors and spouses. Data were analyzed using the AMOS and Macro processes in SPSS. Findings The results revealed that employees’ positive affect at work mediates the relationship between perceived WF and both employees’ organizational citizenship behaviors (OCBs) and family-related social behaviors (i.e. engagement in social activities outside work with their spouses). Personal attitudes toward fun at work moderate the indirect association between perceived WF and the study outcomes (OCBs and family-related social behaviors). Social implications By fostering a workplace environment that prioritizes the perception of enjoyment, organizations can effectively stimulate greater employee engagement in OCBs and promote positive social interactions beyond the workplace. It underscores the significance of an enjoyable environment that benefits employees, organizations and society. Originality/value This study extends the existing research on the relationship between WF and employees’ behaviors in and out of work and provides new insights into the underlying mechanisms that influence this relationship.
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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 | 0.003 | 0.012 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".