Bibliographic record
Abstract
Purpose Drawing from conservation of resources theory, the purpose of this paper is to investigate the relationship between employees’ job satisfaction and helping behaviour, and, particularly, how it may be moderated by two personal resources (work meaningfulness and collectivistic orientation) and one organisational resource (organisational support). Design/methodology/approach Quantitative data were collected from a survey administered to employees and their supervisors in a Pakistani-based organisation. Findings The usefulness of job satisfaction for stimulating helping behaviour is greater when employees believe that their work activities are meaningful, emphasise collective over individual interests, and believe that their employer cares for their well-being. Practical implications The results inform organisations about the circumstances in which they can best leverage employees’ positive job energy, which arises from their job satisfaction, to encourage their voluntary assistance of other organisational members. Originality/value This study extends research on positive work behaviours by examining the concurrent roles that job satisfaction and several contingent factors play in promoting employee helping behaviour. In particular, it highlights the invigorating effects of these factors on the usefulness of the enthusiasm that employees feel about their job situation for increasing their willingness to extend help to other members, on a voluntary basis.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".