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Record W2133701838 · doi:10.1108/00070701311289920

Impact of corporate social responsibility claims on consumer food choice

2013· article· en· W2133701838 on OpenAlexaboutno aff
Simone Mueller Loose, Hervé Remaud

Bibliographic record

VenueBritish Food Journal · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessCorporate social responsibilityMarketingConsumer choiceAdvertisingPublic relationsPolitical science

Abstract

fetched live from OpenAlex

Purpose The study seeks to assess the impact of two different corporate social responsibility (CSR) claims, relating to social and environmental dimensions, on consumers' wine choice across international markets. It analyses how point of purchase CSR claims compete with other food claims and their awareness, penetration and consumers' trust are examined. Design/methodology/approach A discrete choice experiment with a visual shelf simulation was used to elicit consumer preferences and to estimate marginal willingness to pay for CSR and other food claims across the UK, France, Germany, the US East Coast, the US Midwest, and Anglophone and Francophone Canada. Findings CSR claims relating to social and environmental responsibility have a similar awareness, penetration and consumer trust, but differ in their impact on consumer choice, where environmental corporate responsibility claims benefit from a higher marginal willingness to pay. Consumer valuation of CSR claims significantly differs across international markets, but is consistently lower than for organic claims. Originality/value This is the first cross‐national study that analyses the impact of CSR claims on consumer food choice relative to other food claims using large representative consumer samples. The strength of the paper also pertains to the utilisation of innovative choice experiments covering a large range of choice relevant product attributes.

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)0.001
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 score0.045
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.245
Teacher spread0.219 · 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

Citations122
Published2013
Admission routes1
Has abstractyes

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