Transformational Leadership and Organisational Citizenship Behaviour: A Moderated Mediation Model of Leader‐Member‐Exchange and Subordinates' Gender
Bibliographic record
Abstract
Transformational leadership (TL) enhances follower Organizational Citizenship Behavior (OCB) as mediated by leader‐member exchange (LMX). However, the strength of the positive associations among TL, LMX and OCB is subject to significant variability. Accordingly, we draw on several theories (self‐identity, role congruency, self‐concept, and social exchange) to propose that followers' gender moderates the relationships between all three of these variables. We argue differences in societal expectations and/or underlying motivation combine to make leadership of lesser importance to OCB among females than males. Using 202 supervisor‐subordinate dyads from Taiwan, a moderated mediation model of TL‐LMX‐OCB, with subordinate gender as a moderator, was tested. As hypothesised, each of the positive associations among TL, LMX and OCB were weaker for females than for males, thus accounting for some of the variability in the strength of the associations typically observed. Relatedly, although LMX fully mediated the TL‐OCB relationship in the entire sample, this effect was not observed among female subordinates. Further research is required to assess the degree to which these findings apply beyond the Confucian Asian societal cluster.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".