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Record W3203305808 · doi:10.3390/foods10102366

The Impact of Responsible Food Packaging Perceptions on Naturalness and Healthiness Inferences, and Consumer Buying Intentions

2021· article· en· W3203305808 on OpenAlexaff
Alain d’Astous, JoAnne Labrecque

Bibliographic record

VenueFoods · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Packaging Perceptions and Trends
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsNaturalnessProduct (mathematics)MediationPerceptionPsychologyScale (ratio)MarketingFood productsQuality (philosophy)Consumer behaviourAdvertisingSocial psychologyBusinessFood scienceMathematicsSociology

Abstract

fetched live from OpenAlex

The research presented in this article examines the relationship between consumer perceptions that a food package is responsible (sustainable) and consumers' intention to purchase the product that it contains. On the basis of the relevant literature, a conceptual model is proposed where this relationship is hypothesized to be mediated by two variables: the product's perceived naturalness and healthiness. A first study was conducted with the objective of developing a scale with good psychometric properties to measure the perceived naturalness of a food product. The objective of the second study was to test the validity of the two-mediator conceptual model. The results show that the extent to which a food product package is seen as responsible (i.e., recyclable, reusable, compostable) has a positive and statistically significant impact on consumers' intention to buy it, and that it is through the sequential mediation of the product's perceived naturalness and healthiness that this relationship unfolds.

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)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.029
GPT teacher head0.300
Teacher spread0.271 · 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 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

Citations25
Published2021
Admission routes1
Has abstractyes

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