A Conceptual Examination of the Relationship between E-Leadership and Disengagement from Knowledge Sharing: A Moderated Mediated Theoretical Model
Bibliographic record
Abstract
Purpose: The purpose of this conceptual paper is to develop a theoretical model to explain the relationship between e-leadership and disengagement from knowledge sharing. The current study employs the Job Demands-Resources theory (JD-R) and Adaptive Cost theory to illuminate a potential drawback of practicing e-leadership. Methodology: A comprehensive review of the existing literature on e-leadership and knowledge sharing was conducted. The synthesis of these diverse research domains led to the development of a conceptual framework that illustrates the proposed relationship between e-leadership behaviors and the tendency of individuals to disengage from knowledge-sharing activities in virtual environments. Findings. The theoretical model presented in this paper suggests that leadership in the virtual environment has the potential to cause adverse outcomes such as leader stress, which could ultimately lead them to disengage from knowledge-sharing activities in the organization. Unique contribution to theory, practice, and policy. The proposed theoretical model contributes to a deeper understanding of the complex dynamics between e-leadership and knowledge-sharing disengagement in virtual settings. By recognizing the key factors that influence disengagement, organizations can develop targeted interventions and strategies to foster a culture of knowledge sharing and enhance e-leadership effectiveness. This paper is the first study to examine how the complexities of e-leadership could negatively affect a leader's health and knowledge-sharing behavior.
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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 | 0.001 | 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 | 0.001 |
| 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".