Bibliographic record
Abstract
Purpose Drawing on principles of social exchange and equity theory, the purpose of this paper is to examine the relationship between employee reports of leader-member exchange (LMX) and two types of organizational citizenship behavior (OCB): affiliative and change-oriented OCB. Further, equity sensitivity, a dispositional variable reflecting one’s tendency to “give” or “take” in their interpersonal interactions, was tested as a moderator of these effects. Design/methodology/approach Data were collected from a sample of 240 manufacturing employees in China and their respective supervisors. Multilevel analyses were conducted to test the hypothesized effects. Findings LMX was found to be positively associated with affiliative, but not change-oriented OCB. Equity sensitivity moderated these relationships, such that LMX was positively associated with both types of OCB when employees are benevolent, but not when they are entitled. Research limitations/implications Given the different pattern of relationships that were observed between LMX and affiliative vs change-oriented OCB, the results suggest that LMX may differentially influence these two types of OCB. Future studies should continue to explore the role of dispositional traits in moderating the effects of LMX, including less desirable (“negative”) traits. Originality/value Very few studies have examined the role of dispositional variables in moderating the effects of LMX. Consistent with principles of the social exchange and equity theory, the results suggest that LMX will only be associated with OCB when employees are benevolent (i.e. they are “givers”), and not when they are entitled (i.e. they are “getters”).
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".