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Record W4367547636 · doi:10.55905/ijsmtv9n1-030

Conditional effects of consumer-brand relationships on admired and non-admired brands, and its impact on schadenfreude

2023· article· en· W4367547636 on OpenAlexaff
Flávio Santino Bizarrias, Jussara da Silva Teixeira Cucato, Suzane Strehlau, Vivian Iara Strehlau

Bibliographic record

VenueInternational Journal of Scientific Management and Tourism · 2023
Typearticle
Languageen
FieldPsychology
TopicEmotions and Moral Behavior
Canadian institutionsImpact
Fundersnot available
KeywordsFeelingPleasurePsychologyAdvertisingSocial psychologyBrand equityRivalryBrand loyaltyExtant taxonBrand extensionEconomicsBusiness

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.749
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.343
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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