Consumer preference for infant milk‐based formula with select food safety information attributes: Evidence from a choice experiment in China
Bibliographic record
Abstract
Abstract The melamine milk powder incident in China undermined consumers’ confidence in dairy products including infant milk‐based formula (IMF). In this study, three quality IMF product attributes are considered in a choice experiment survey in China including organic label, traceability information, and country of origin (COO). Results reveal that consumers have the highest willingness to pay (WTP) for an organic label from the United States. Traceability information regarding milk production was preferred the most. Consumers prefer IMF originated from the United States and New Zealand over China. Consumer heterogeneity was revealed through a latent class model. Compared to price‐sensitive consumers, certification‐inclined consumers had significantly higher WTP for organic labels. Origin‐preferred consumers displayed higher WTP for IMF produced in the United States and New Zealand, and concerned consumers had higher WTP for all food safety informational attributes. The conclusions of this paper should not only aid Chinese domestic producers and policy makers, they should also provide references for organic certification bodies and dairy enterprises from around the world for their business decision making.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".