Examining the Impact of Transformational Leadership, Organizational Citizenship Behaviors, and Organizational Performance: A Dual Perspective in the Public Sector
Bibliographic record
Abstract
The study utilizes a direct-indirect effects model to examine the connections among Transformational Leadership Behaviors (TLB), Organizational Citizenship Behaviors (OCB), and Organizational Performance (OP) within the public sector. TLB data were collected from leaders and followers, allowing for comparison between leader-perception and follower-perception models. A survey methodology involved 1,364 participants from U.S. county government executives and followers, analyzed using structural equation modeling. It aims to bridge gaps in the literature by integrating TLB, OCB, and organizational-level performance into one model, providing nuanced insights into their interactions. Findings support TLB’s positive impact on OCB and OP and OCB’s positive influence on OP. Differences in leader and follower perceptions highlight the need for comprehensive evaluation. The study addresses the limitations of prior research by considering both leader and follower perspectives, contributing to understanding leadership’s role in organizational performance. Practically, it suggests strategies for enhancing performance through TLB fostering, OCB encouragement, and creating supportive work environments. Its originality lies in its holistic examination of TLB, OCB, and OP, offering valuable insights into the public sector and organizational practices.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".