“Not tested on animals”: how consumers react to cruelty-free cosmetics proposed by manufacturers and retailers?
Bibliographic record
Abstract
Purpose Animal welfare is increasingly favoured by consumers in their choice of food and cosmetic products, proposed by manufacturers and retailers. This study aims to investigate the impact of the “not tested on animals” claim on consumers' attitude and behavioural intention towards a cosmetic product through an enriched version of Ajzen's theory of planned behaviour. Design/methodology/approach A between-subjects design has been used. 450 participants were recruited through the social network of a cosmetics and personal hygiene brand in Quebec, Canada, and answered a questionnaire. They were randomly assigned to either a manipulation group ( n = 226) or a control group ( n = 224). Data were analysed with partial least squares structural equation modelling. Findings This study shows that external (credibility and attitude towards marketing claims) and internal psychological variables (subjective norms and altruistic concerns with animal welfare) influence attitude towards and purchase intention of “not tested on animals” personal care products. More egotistic concerns, such as personal appearance, also explain the formation of attitude towards cruelty-free cosmetics. Research limitations/implications This research supplements Ajzen's original model with internal psychological (individuals' concerns with animal welfare and personal appearance) and external (general credibility of cosmetic products claims, credibility of the “not tested on animals” claim and attitude towards this claim) variables. These variables, as suggested by previous research on cosmetics and their claims, improve the understanding of consumer attitude and purchase behaviour patterns. Practical implications The study's findings point out the role of companies to increase consumers' knowledge on the significance and transparency of their messages, notably the “not tested on animals” claim. They also stress that policymakers in regions where regulation is unclear should at least punish untruthful communication pertaining to animal testing in cosmetic and personal care products. Originality/value Prior studies on cosmetic products did not investigate the difference of consumer attitude formation towards cruelty-free products compared to conventional cosmetic products. Consequently, this research shows that the construction of attitude towards cruelty-free products highly differs from conventional personal care.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".