Unconscious Drivers of Consumer Behavior: An Examination of the Effect of Nature–Nurture Interactions on Product Desire
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".