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Record W4403002074 · doi:10.56397/jlcs.2024.09.02

The Semiotic Role of Color in Alcoholic Beverage Packaging and Its Advertising Synergy

2024· article· en· W4403002074 on OpenAlexaff
S. T. Carson, W. F. Lysander, B. H. Elowen

Bibliographic record

VenueJournal of Linguistics and Communication Studies · 2024
Typearticle
Languageen
FieldPsychology
TopicColor perception and design
Canadian institutionsLakehead University
Fundersnot available
KeywordsSemioticsAdvertisingBusinessFood sciencePsychologyChemistryLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

This study explores the semiotic role of color in alcoholic beverage packaging and its synergy with advertising campaigns. Through a mixed-methods approach involving content analysis, case studies, and consumer surveys, we examine how color choices in packaging influence consumer perception, brand identity, and marketing effectiveness. This finding reveal that specific colors evoke distinct psychological responses and cultural meanings, which significantly impact brand recognition and consumer loyalty. The research highlights successful strategies used by brands such as Absolut Vodka, Coca-Cola, and Heineken, demonstrating the importance of color consistency across packaging and advertising in creating a cohesive and memorable brand image. Additionally, this study discusses the role of digital advertising in maintaining color synergy and the need for cultural adaptation in global marketing. This study provides valuable insights for brand managers and marketers, emphasizing the strategic use of color to enhance visual identity, brand recall, and consumer engagement.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.004
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0000.001
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 head0.046
GPT teacher head0.387
Teacher spread0.341 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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