Support, trust, satisfaction, intent to leave and citizenship at organizational level
Bibliographic record
Abstract
Purpose The purpose of this paper is to propose to test a research model to gain a better understanding of the connection between perceived support, trust, satisfaction, intention to quit and citizenship at the organizational level. Design/methodology/approach A total of 355 white‐collar employees were recruited among alumni of a business school in France. Structural equation modeling was used to test the predicted relationships. Findings Except for the relation between perceived organizational support (POS) and intention to leave, study results showed strong support in favour of the different hypothetical relations in the research model. Research limitations/implications The results are based on a single sample and a transversal research design. For these reasons, the data should be approached with caution. Practical implications The paper highlights the importance of considering trust over and above organizational efforts directed at supporting employees through a show of appreciation for their contribution and concern for their well‐being. Originality/value This paper provides data that lead to a better understanding of the relationship between POS, trust and satisfaction for the purpose of predicting outcomes such as intention to leave an organization and citizenship behaviour towards an organization.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.019 | 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".