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Record W4385421611 · doi:10.18280/ijsdp.180725

Influence of Cause-Related Packaging on High Cultural Capital Consumers’ Purchase Intention Toward Snacking Products – Use of Consumption Value Theory

2023· article· en· W4385421611 on OpenAlexvenueno aff
Suchita Jha, Manisha Palliwal, Shruti Sengupta

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Packaging Perceptions and Trends
Canadian institutionsnot available
Fundersnot available
KeywordsSnackingConsumption (sociology)Value (mathematics)Cultural capitalBusinessMarketingCapital (architecture)AdvertisingEconomicsMathematicsGeographySociologyStatistics

Abstract

fetched live from OpenAlex

Recently, many FMCG marketers, due to the increased interest of consumers towards health and sustainability, started focusing on their product packaging with an association of causerelated packaging. Snacking product purchase is highest among high culture consumers, so this category was chosen for study. This research aims to understand the reason for purchasing a snacking product associated with any cause. Whether consumers are purchasing the product because of functional, emotional, hedonic, conditional, epistemic, or social values. The questionnaire was framed using a validated scale of consumption value theory. Cluster analysis was done using SPSS is an attempt to segregate the respondents into different consumer types. The study clustered the groups into three distinct groups. Social and emotional values and epistemic drive the first cluster, whereas the second cluster is purchasing the product because of hedonic value, and the last cluster is purchasing the product because of its functional value, and they are bothered about any cause association.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.040
GPT teacher head0.274
Teacher spread0.234 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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Same venueInternational Journal of Sustainable Development and PlanningSame topicConsumer Packaging Perceptions and TrendsFrench-language works237,207