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Evaluating Willingness‐to‐Pay for Bison Attributes: An Experimental Auction Approach

2006· article· en· W2007007088 on OpenAlexaffvenueabout
Jill E. Hobbs, Kim Sanderson, Morteza Haghiri

Bibliographic record

VenueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomie · 2006
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsMount Allison UniversityLakes Environmental (Canada)University of Saskatchewan
Fundersnot available
KeywordsBison bisonWillingness to payAgricultural scienceGeographyBusinessMarketingEconomicsBiologyEcology

Abstract

fetched live from OpenAlex

Domestic bison herds in Canada and the United States have grown rapidly over the past decade. For this growth to be sustainable, viable markets for bison meat products are necessary. Bison products are available at the retail level to only a limited extent in some localized markets. Very little is known about consumer preferences for bison in Canada. A consumer research study was conducted across five Canadian locations. An experimental auction was used to evaluate willingness‐to‐pay (WTP) for bison versus beef, plus the marginal WTP for bison with additional health‐related attributes. Bison products verified to be lower in fat than beef, and bison verified to have been produced without the use of growth hormones were evaluated. Results suggest that there was no significant WTP for bison over beef, either with or without the additional quality assurances. Delivering a positive eating experience to consumers was more important than the health‐related attributes per se. Distinct market segments with significantly different WTP for bison are identified. Some regional differences are also apparent. The industry cannot rely solely on the touted health benefits of bison to deliver a competitive advantage over beef. While some consumers may be willing to pay more for these health‐related attributes, consumers in general are unlikely to compromise eating experience. Au Canada et aux États‐Unis, les troupeaux de bisons domestiques ont crû rapidement au cours de la dernière décennie. Pour que cette croissance soit durable, il faut développer des marchés viables pour le bison. Le bison est vendu au détail dans quelques marchés locaux seulement. Au Canada, les préférences des consommateurs pour le bison sont peu connues. Une étude à cet effet a été réalisée dans cinq villes canadiennes. La volonté de payer (VDP) des consommateurs pour du bison plutôt que pour du bœuf de même que la VDP marginale des consommateurs pour du bison ayant des propriétés supplémentaires pour la santé ont étéévaluées à l'aide d'enchères expérimentales. Des produits du bison ayant une teneur en gras inférieure à celle du bœuf et provenant d'élevages sans hormones de croissance ont étéévalués. Les résultats ont montré qu'il n'existait pas de VDP significative pour du bison plutôt que pour du bœuf, et ce, avec ou sans assurance de qualité supplémentaire. L'expérience alimentaire s'est révélée plus importante que les propriétés pour la santé en soi. Nous avons identifié des segments de marché distincts où la VDP pour du bison était significativement différente. Certaines différences régionales étaient aussi apparentes. L'industrie ne peut pas se fier qu'aux avantages vantés de la viande de bison pour la santé pour offrir un avantage concurrentiel par rapport au bœuf. Bien que certains consommateurs soient prêts à payer davantage pour des propriétés favorables pour la santé, il est peu probable que les consommateurs en général compromettent une nouvelle expérience alimentaire.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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.

Opus teacher head0.145
GPT teacher head0.219
Teacher spread0.074 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations56
Published2006
Admission routes3
Has abstractyes

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