A Conjoint Analysis Evaluation of Consumer Perspectives on Cricket-Based Snacks: A Case Study for Alberta, Canada
Bibliographic record
Abstract
Insects have been proposed as a sustainable protein alternative to conventional meat sources. However, consumer acceptance of edible insects is still low in the Western Hemisphere. This study examined how product characteristics and consumer beliefs influence the liking and willingness to try cricket-based food products. An online survey was conducted in the province of Alberta, Canada. Alberta is a major site for beef production and plays a vital role in Canada’s agricultural and economic landscape. Participants (n = 548) were asked to indicate their overall liking (OL) and willingness to try (WTT) a cricket-based snack in a conjoint analysis experiment. A 2 × 2 × 5 design was used for the product characteristics (type of product, presence of an image of the product, and product benefit claims). Each participant was assigned five product profiles using a balanced incomplete block design. The type of product (cricket chips and whole roasted crickets) was the most important attribute for participants. Product benefit claims did not effectively increase the OL or WTT of the cricket-based snacks. Higher scores on the Entomophagy Attitude Scale and previous experiences consuming insect-based food products positively influenced WTT and OL. The findings of this study underscore the significance of the type of product and personal attitudes towards entomophagy in shaping consumer preferences for sustainable protein sources and offer valuable insights for the development and marketing of insect-based food products in a Western market where meat products are accessible and affordable for many.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".