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Record W2128957565 · doi:10.1086/676980

Should the Devil Sell Prada? Retail Rejection Increases Aspiring Consumers' Desire for the Brand

2014· article· en· W2128957565 on OpenAlexaff
Morgan K. Ward, Darren W. Dahl

Bibliographic record

VenueJournal of Consumer Research · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAdvertisingBrand namesPsychologyBusiness

Abstract

fetched live from OpenAlex

In response to consumers' complaints that they feel rejected in and thus avoid luxury stores, retailers have encouraged sales personnel to be more friendly. However, prior research on social rejection supports the idea that rejection encourages people to elevate their perceptions of their rejecters and strengthens their predilection to affiliate with them. Four studies examine the circumstances in which consumers increase their regard and willingness to pay after brand rejection. In a retail context, the data reveal that after threat, consumers have more positive attitudes and higher willingness to pay when (1) the rejection comes from an aspirational (vs. nonaspirational) brand, (2) the consumer relates the brand to his/her ideal self-concept, (3) s/he is unable to self-affirm before rejection, (4) the salesperson delivering the threat reflects the brand, and (5) the threat occurred recently. The substantive implications of these findings for retailers are discussed, and opportunities for future research are identified.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.238
GPT teacher head0.378
Teacher spread0.140 · 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 source (direct Gemma or distilled Codex), 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

Citations177
Published2014
Admission routes1
Has abstractyes

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