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Record W1490426310 · doi:10.7939/r3br8mp4x

Consumer Attitudes, Willingness to Pay and Revealed Preferences for Different Egg Production Attributes: Analysis of Canadian Egg Consumers

2007· preprint· en· W1490426310 on OpenAlexaboutno aff
Peter C. Boxall, John Paul Emunu, Andre Asselin, Curtis Boyd, Ellen Goddard, Amanda Neall

Bibliographic record

VenueRePEc: Research Papers in Economics · 2007
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsnot available
Fundersnot available
KeywordsPurchasingWillingness to payPreferenceBusinessConsumption (sociology)Animal welfareWelfareHomogeneousMarketingEconomicsBiologyEcology

Abstract

fetched live from OpenAlex

The Canadian egg industry has introduced a number of specialty eggs, including Omega-3, organic, free run/range, vitamin enhanced and vegetarian over the past few decades. These eggs are generally sold at prices higher than the ‘normal’ egg and there has been little analysis of the consumer awareness of and interest in purchasing these eggs. All previous econometric analysis of the Canadian egg market has assumed eggs and consumers are homogeneous. This study makes use of Stated preference and Revealed preference data to model the consumer interest in the different egg types. Stated preference surveys were conducted in two separate years: 2005 during which consumers were surveyed on their interest in Omega-3 and Vitamin Enhanced eggs relative to ‘normal’ eggs, white large, Grade A eggs, and 2006 during which consumers were surveyed on their interest in organic, freerun and vegetarian eggs relative to brown Grade-A eggs. Consumers were also assessed on their health behaviour, health consciousness, and in 2006 on their attitudes towards animal welfare, novelty foods, and environmental concerns. Results from this phase of the research suggested that among the sample of Alberta consumers, there is only modest interest in the specialty eggs, eggs, in general, are associated with other healthy behaviours, health conscious consumers are willing to pay more for specialty eggs, of all types, older consumers and consumers with families are significantly more price sensitive and hence, have constraints on their ability to purchase specialty eggs. As well, consumers with concerns about animal welfare will pay more for free run eggs, there is an increased interest in eggs with identified health attributes among older consumers. Revealed preference analysis of actual purchase behaviour was conducted on an A C Nielsen Homescan© panel data set over a three year period. Separate analyses were conducted for Alberta and Ontario frequent egg purchasers, with some significant differences across provinces. In Alberta no one is willing to pay more for specialty eggs than for normal eggs, with either modeling technique applied. In Ontario this assessment is less clear, the frequency model of how often across a three year period households purchased each type of egg, would suggest that consumers are willing to pay more for specialty eggs than for ‘normal’ eggs, with organic the egg that they are willing to pay the most for. At the same time the choice model for Ontario, a model of actual purchases across time with the type of egg as the dependent variable, suggests that consumers are willing to pay the most for ‘normal’ eggs with Free run and Organic close behind. Overall, as we look more closely at the relative ranking of specialty eggs, at the mean of all variables, organic eggs are the ones all households are willing to pay the most for. In the frequency model Alberta consumers’s willingness to pay for organic eggs is closest to the normal egg and Ontario consumers would pay $1.72 relative to normal eggs. The choice model exhibits similar patterns. Free run eggs are also popular in Ontario, but less so than organic. One of the findings of the study is that there may be some misunderstanding of the relative nutritional benefits of the different types of eggs or other human health aspects of agricultural production. Health seems to be an issue in the purchase of organic eggs as much as it does in the purchase of Omega-3 eggs. Further specific research on the reasons why consumers purchase organic would allow the industry to develop better marketing tools.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.154
GPT teacher head0.314
Teacher spread0.160 · 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 teacher head, not a consensus.

Study designObservational
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

Citations21
Published2007
Admission routes1
Has abstractyes

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