An evaluation of consumers’ preferences for certified farmed Atlantic salmon
Bibliographic record
Abstract
Purpose – The fisheries and aquaculture industry has observed substantial reduction in the demand for farmed Atlantic salmon after the food incidence of polychlorinated biphenyls in the product. To regain consumer confidence in the quality and safety of the product new policies, such as advanced traceability and identity preservation systems in the fisheries and aquaculture industry have been suggested. The purpose of this paper is to examine consumers’ preferences to pay a premium price for certified farmed Atlantic salmon that is passed through various quality and traceability systems in the province of Newfoundland and Labrador, Canada. Design/methodology/approach – The paper uses the contingent valuation (CV) method by estimating a probit regression model to assess consumers’ preferences for certified farmed Atlantic salmon. In particular, the paper measures consumers’ willingness to pay (WTP) a premium price to purchase the product. The CV method is the most widely used methodology in measuring individuals’ attitudes toward purchasing certified products. To estimate the parameters of the model, the authors carried out a consumer survey in spring 2010 and successfully completed 120 questionnaires in the province. Findings – The paper provides empirical insights about how households are interested in consuming certified farm-raised Atlantic salmon by paying an additional premium price to purchase the product. The results of the study show that although consumers believe that traceability methods, on average, will increase the price of certified farmed Atlantic salmon their preferences toward the consumption of the product will not be changed. Research limitations/implications – Since the paper uses the CV method to evaluate individuals’ preferences for certified farm-raised Atlantic salmon, the authors also suggest another study that uses a non-hypothetical choice experimental approach to elicit households’ WTP a premium price for the product. Originality/value – This paper shows how consumers’ decisions to purchase certified farm-raised Atlantic salmon can be affected by a series of demographic, socio-economicand other variables that reflect consumers’ awareness of issues surroundings farmed Atlantic salmon and quality assurance.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".