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Record W2777949735 · doi:10.1002/cb.1701

Paradoxical effects of famous music in retail venues

2017· article· en· W2777949735 on OpenAlexaff
Luca Petruzzellis, Jean‐Charles Chebat, Ada Palumbo

Bibliographic record

VenueJournal of Consumer Behaviour · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Retail Behavior Studies
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsMediationAffect (linguistics)PsychologyQuality (philosophy)CognitionProduct (mathematics)AdvertisingSocial psychologyBusinessSociologyCommunication

Abstract

fetched live from OpenAlex

Abstract The present study analyzes the effects of famous versus nonfamous ambient music in retail venues on actual shoppers' emotions and cognitions, which, in turn, affect buying intention and brand images. Our theoretical model was basically validated by the data collected in actual shopping venues in 2 studies. Study 1 explores the effects of music famousness on buying intention through the mediation of affect, self‐congruity, and product quality ( N = 304). Study 2 explores the effects of music famousness on perceived brand quality through the mediation of self‐congruity and store attitude ( N = 351). As expected, famous music has positive effects on shoppers' responses according to the mediating role of affective and cognitive responses and their sequential mediating effects. Paradoxically, famous music has also negative effects on these variables because it distracts consumers from their shopping, reducing cognitive activities. We draw theoretical and managerial conclusions from these findings.

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)0.006
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.037
GPT teacher head0.272
Teacher spread0.235 · 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

Citations13
Published2017
Admission routes1
Has abstractyes

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