Perceived organizational support and organizational commitment
Bibliographic record
Abstract
Purpose The aim of this article is to deepen the understanding of the relationships between perceived organizational support (POS) and the dimensions of organizational commitment (i.e. affective, normative and continuance commitment), and to test the moderating effect of locus of control and work autonomy. Design/methodology/approach This study, based on a cross‐sectional research design, was conducted in an organizational setting. The sample includes 249 prison employees. The data were collected through questionnaires. Findings The results show that POS is positively and significantly correlated with affective and normative commitment. In addition, the results of the hierarchical multiple regression analyses support the moderating effect of locus of control and work autonomy with regard to the relationship between POS and affective commitment. Practical implications This study highlights the importance of providing support to employees in order to foster their affective and normative commitment to the organization. Moreover, the results provide evidence in favour of managerial interventions aimed at enhancing perceived control and, consequently, minimizing the negative effects of a lack of organizational support on employees' affective commitment. Originality/value In addition to taking into account three dimensions of organizational commitment, this study underlines personality and job design factors that can modulate the relationship between POS and organizational commitment.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".