How high involvement work systems reduce employee time theft: the role of psychological empowerment and organizational identification
Bibliographic record
Abstract
Purpose Time theft is a widespread and costly workplace deviant behavior. Based on social information processing theory, the authors build a multilevel model to explore when and how team-level high involvement work systems (HIWSs) could effectively reduce time theft behavior. Specifically, this study aims to propose that HIWSs relate to employee time theft through the mediating effect of psychological empowerment and the moderating role of team-level organizational identification. Design/methodology/approach Through a three-wave field survey, this study successfully collected data from 396 employees and their 87 direct supervisors working in different industries in an eastern province of China. Findings The results suggest that HIWSs reduce employee time theft via psychological empowerment, and team-level organizational identification strengthens the indirect effect. Originality/value This study contributes to the literature by introducing HIWSs as a human resource management-related antecedent of time theft. It also identifies psychological empowerment as a key mediator that links HIWSs to employee time theft and reveals the moderating role of organizational identification in the 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 | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".