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Record W4402370421 · doi:10.3390/bs14090789

Unconscious Drivers of Consumer Behavior: An Examination of the Effect of Nature–Nurture Interactions on Product Desire

2024· article· en· W4402370421 on OpenAlexaff
Jim B. Swaffield, Jesus Sierra Jimenez

Bibliographic record

VenueBehavioral Sciences · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsVancouver Island UniversityAthabasca University
Fundersnot available
KeywordsProduct (mathematics)Nature versus nurtureAffect (linguistics)PsychologyConsumption (sociology)Social psychologyConsumer behaviourAdvertisingMarketingBusinessSociologyCommunication

Abstract

fetched live from OpenAlex

Both biological and environmental factors can affect consumer behavior. Consumer behavior can also be a product of an interaction between one's evolved biology and environmental factors. If marketers aim to increase healthy consumption behavior and decrease unhealthy behavior, they need to identify whether the behavior is a product of one's evolved biology or environmental factors acting in isolation, or if the behavior is a product of a biology-environment interaction. Therefore, the purpose of this study is to examine the effect of biology-environment interactions on product desire. This study comprises two experiments that used a repeated-measures design. The first experiment included 315 females and examined the effect of perceived physical safety, economic well-being, and social support on the desire for beautifying and wealth-signalling products. The second experiment included 314 men and examined the effect of perceived physical safety, economic well-being, and social support on the desire for products that are used to signal wealth and toughness. The results showed that under harsh economic conditions, product desire generally decreased. However, there were significant differences in the amount of decrease between product categories in different environmental conditions.

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 score0.536
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.036
GPT teacher head0.327
Teacher spread0.292 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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