Multiple sources of support, affective commitment, and citizenship behaviors
Bibliographic record
Abstract
Purpose – The purpose of this paper is to examine the moderating role of passive leadership in the relationships of perceived support from organization, coworkers, and physicians to affective commitment and organizational citizenship behavior (OCB) among hospital employees. Design/methodology/approach – Using a sample of 182 hospital employees and a time-lagged design in which predictors and moderator were assessed at Time 1 and self-reported OCB was obtained 2.5 years later, the authors examined whether passive leadership moderates the relationships of perceived supports to commitment and their indirect effects on OCB. Findings – Analyses indicate that at high levels of passive leadership, the relationship between support from organization and coworkers and commitment is less positive and the relationship between support from physicians and commitment is negative. Moreover, the indirect effect of perceived support from coworkers and physicians on OCB through affective commitment is weaker at high levels of passive leadership. Research limitations/implications – Although the data used were self-reported, the analyses show that method variance accounted for only 9 percent of the variance among constructs at Time 1. Findings contribute to highlight the boundary conditions associated with perceived support and establish that passive leadership severely limits the beneficial effects expected from support available to employees. Practical implications – Findings suggest that supervisors should be trained not only on improving positive leadership skills but also on reducing passive behaviors in the face of problems in their teams. Originality/value – This study extends the understanding of social exchange processes in organizations and invites managers and researchers to look at factors that slow down the development of social exchange relationships with employees.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".