Reimagining fast food: Consumers' judgments and acceptance of fast food alternatives
Bibliographic record
Abstract
Fast food corporations specializing in cheeseburgers are highly successful. However, consumption of cheeseburgers' main components (white flour buns, cheese, and beef patties) has been related to public health risks and environmental issues. Drawing on the theory of planned behavior, this study aimed to characterize consumers' acceptance of burger component alternatives (wholegrain buns, vegetables, and hybrid beef-oat patties) that promoted cardiovascular health and were more environmentally-friendly than some of the offered items. Analyzing the results of two online surveys comprising choice and rating tasks ( N = 986), this study suggested that most consumers perceived the alternatives to be healthier but less tasty than the original items. Many consumers were unsure about the alternatives' environmental impact. Consumers' taste judgments influenced their acceptance of the alternatives more strongly than their healthiness and environmental impact judgments, and these results were robust for consumers who were concerned about their health, had high body mass indices, or ate fast food frequently. Accordingly, most consumers preferred the original burger components over the alternatives. Nevertheless, a substantial proportion of consumers perceived the healthier alternatives to be tastier, expressed their readiness to adopt them, and were willing to pay for them. This study offers applications for fast food corporations and educators. • Fast food is often related to cardiovascular risks and environmental issues. • Consumers' acceptance of healthier and more sustainable burger components was studied. • Taste judgments affected acceptance more than healthiness or sustainability judgments. • A substantial proportion of consumers considered the alternatives to be tastier. • Consumers expressed the intention to pay additional price for component alternatives.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".