Conditional effects of consumer-brand relationships on admired and non-admired brands, and its impact on schadenfreude
Bibliographic record
Abstract
Extant literature on schadenfreude, a pleasure towards the misfortune of others, is concentrated on brand rivalry however is silent about situations when one own brand causes the schadenfreude. Based on brand relationship theory we advance knowledge on this topic by investigating how one brand’s bad malicious strategy leads to schadenfreude for admired and non-admired brands and is mitigated when admired brands interact with positive feelings elicited by brand-consumer relationship to protect against their own bad behavior. Through three experimental studies we point out the feelings elicited exact region of moderations. The first study tests the mitigating effect of congruence between brand and Self. Study two tests higher-order affective levels such as brand love, as a negative moderating construct for schadenfreude. Study three advances previous studies on consumers’ self-promoting feelings and their interaction with brands to produce schadenfreude. Finally, we discuss the findings and further directions for research on schadenfreude.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".