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Record W4401991483 · doi:10.1016/j.jbusres.2024.114932

The impact of social presence cues in social media product photos on consumers’ purchase intentions

2024· article· en· W4401991483 on OpenAlexaff
Sara‐Maude Poirier, Sarah Cosby, Sylvain Sénécal, Constantinos K. Coursaris, Marc Frédette, Pierre‐Majorique Léger

Bibliographic record

VenueJournal of Business Research · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsSocial mediaAdvertisingProduct (mathematics)BusinessMarketingPsychologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

• Social presence evokes positive emotional reactions and arousal in consumers. • Implied human presence (vs. human presence) leads to greater photo diagnosticity. • Photo diagnosticity, positive emotions, and arousal increase purchase intentions. On social media, brand-generated photos enable firms to communicate information about their products. The present research investigates the effect of social presence cues in product photos on consumers’ purchase intentions. We conducted three experiments to explore how varying levels of perceived social presence (i.e., physical, implied, or absent human presence) in product photos affect consumer responses. The results indicate that social presence positively influences consumers’ emotions and product photo diagnosticity, which, in turn, positively impacts purchase intentions. In addition, a consumption background in product photos moderates the relationship between social presence and product photo diagnosticity. Utilizing the Elaboration Likelihood Model, this research contributes to the literature on social presence and mental imagery in the context of brand-generated photos. The implications for managers are also discussed, highlighting how the level of social presence in product photos influences consumers’ purchase intentions.

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)0.009
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.702
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.129
GPT teacher head0.466
Teacher spread0.337 · 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.

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

Citations26
Published2024
Admission routes1
Has abstractyes

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