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Record W2476479533 · doi:10.1108/bfj-03-2016-0121

Meat consumption and higher prices

2016· article· en· W2476479533 on OpenAlexaffabout
Sylvain Charlebois, Maggie McCormick, Mark Juhasz

Bibliographic record

VenueBritish Food Journal · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomics of Agriculture and Food Markets
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPurchasingConsumption (sociology)SustainabilityBusinessProduction (economics)Volatility (finance)WelfareAnimal welfareMarketingFood safetyPurchasing powerEconomicsAgricultural economicsMicroeconomicsFood scienceMarket economy

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to evaluate if sudden retail price increases for beef products have affected consumers purchasing behaviors. Little research has been conducted that integrates retail price volatility with subdued food consumption motivations. Prior research about consumers’ meat-purchasing habits and systemic concerns linked to sustainability and animal welfare is limited or de-contextualized. This study also attempts to assess if retail price increases have triggered a change in perception of the meat industry, by looking at specific values related to animal protein production and consumption. Design/methodology/approach This study is based on an inductive, quantitative analysis of primary data obtained from a survey on beef consumption. For convenience and validity, all respondents had to be living in Canada for 12 months, and were at least 18 years old. The choice of country is not trivial. First, access to data were convenient for this study. Second, and most importantly, Canada has supply managed commodities that include poultry and chicken. In effect, Canada produces the amount of chicken it needs. Beef production is vulnerable to market volatility. As a result, demand-focussed market conditions for one often influence conditions for the other. Findings Findings indicate that higher prices have compelled 37.9 percent of the sample to reduce or to stop beef consumption altogether in the last 12 months. Beyond the issue of price, sustainability, food safety and health appear to be significant factors, more so than ethics (animal welfare). Results also show that education can be considered as a determinant for sustainable aspects of beef production when prices increase. Age and gender had no statistical significance on survey results. Some limitations are presented and future research paths are suggested. Research limitations/implications Since the sample in this study was mainly composed of consumers based in Canada, the generalizations of the findings should be approached with some caution. The same research should be conducted with consumers from other parts of the Western world to verify if the results can be generalized. Practical implications This survey help the authors to understand some aspects of beef consumption at retail. Findings of this empirical study have implications for future communications to consumers, in that greater emphasis should be given to the connection consumers have with other nutritional alternatives. Since meat consumption in the Western world is intrinsically linked to culinary traditions, behaviors can be challenging to change. Social implications The economic implications of a rapid adoption of a plant-based diet for the agricultural economy would be significant. However, the reality is that according to many studies of consumer behavior, customers still place a higher value on buying and eating meat than on any other food group. Canada’s relationship with animal proteins has deep cultural roots, particularly during holidays and summertime. Originality/value The present study has given important insights into the determinants of meat consumption reduction, a behavior which could both have long-term economic implications for the cattle and beef industries. This paper provides a deeper insight into some socio-economic factors that contribute to slow erosion of meat consumption reduction, and the effects of higher prices at retail. This is, as far as the authors know, likely the first study of its kind.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.027
GPT teacher head0.184
Teacher spread0.158 · 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

Citations43
Published2016
Admission routes2
Has abstractyes

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