The Relationship Between Employees’ Daily Customer Injustice and Customer-Directed Sabotage: Cross-Level Moderation Effects of Emotional Stability and Attentiveness
Bibliographic record
Abstract
Customer injustice has received considerable attention in the field of organizational behavior because it generates a variety of negative outcomes. Among possible negative consequences, customer-directed sabotage is the most common reaction, which impacts individuals' well-being and the prosperity of organizations. To minimize such negative consequences, researchers have sought to identify boundary conditions that could potentially attenuate the occurrence of customer-directed sabotage. In this study, we explore potential attenuation effects of emotional stability and attentiveness on the customer injustice-sabotage linkage. The results showed emotional stability and attentiveness moderate the relationship between customer injustice and customer-directed sabotage. Specifically, the representatives with higher (vs. lower) emotional stability or higher (vs. lower) attentiveness are less likely to engage in customer-directed sabotage when they experience customer injustice. Moreover, there is a three-way interaction among daily customer injustice, emotional stability, and attentiveness that predicts daily customer-directed sabotage. Theoretical and practical contributions, limitations, and directions for future development are also discussed.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".