Authentic leadership and employee expediency: a moderated mediation framework
Bibliographic record
Abstract
Purpose Based on self-verification theory, this study examines the impact of authentic leadership on employee expediency in China. Specifically, the authors investigate the mediating effects of self-verification striving on this relationship, as well as the moderating effects of leader–member exchange. Design/methodology/approach The authors surveyed 502 employees and their direct supervisors from 96 work units in one Chinese province and utilized multi-level path analysis to test a model of moderated mediation. Findings The study analysis results suggest that authentic leadership significantly contributes to reducing employee expediency in the surveyed Chinese companies. Self-verification striving mediates this relationship. Furthermore, leader–member exchange enhances the positive relationship between authentic leadership and self-verification striving. Research limitations/implications This study extends the understanding of antecedents of employee expediency and also extends previous research on the role of self-verification in shaping employee behaviors. The limitation is that the results are specific to China, and the study only relied on cross-sectional data. Practical implications The current study suggests that organizations should consider implementing training programs for their leaders to cultivate traits associated with authentic leadership. Furthermore, managers should actively promote employee engagement in discussions related to work objectives, methods and efficiency to assist them in their self-verification striving. They need to make efforts to enhance the climate of leader–member exchange, thereby reducing employee expediency. Originality/value This research identifies self-verification striving as key mediators that link authentic leadership to employee expediency and reveals the moderating role of leader–member exchange in the process.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".