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Record W4318480120 · doi:10.5539/ass.v19n1p36

Communicating Sustainability Fashion in Marketing Advertisements on the Context of Malaysia: Stimuli Development and Pre-Testing Results

2023· article· en· W4318480120 on OpenAlexvenueno aff
Nornajihah Nadia Hasbullah, Ag Kaifah Riyard Kiflee, Zuraidah Sulaiman, Adaviah Mas’od, Hainnuraqma Rahim

Bibliographic record

VenueAsian Social Science · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsnot available
Fundersnot available
KeywordsRegulatory focus theoryPromotion (chess)Context (archaeology)SustainabilityAdvertisingBusinessTest (biology)Focus groupMarketingFocus (optics)Sustainable developmentPsychologyPolitical scienceSocial psychologyCreativity

Abstract

fetched live from OpenAlex

Although awareness of sustainable fashion in Malaysia is present, it is growing slowly. Consumers may find it challenging to understand messages or communicating advertisements on pro-environmental actions. Accordingly, stimuli development was designed in this study using regulatory focus theory for the structural development of an advertisement message. The advertisement content was generated based on promotion and prevention regulatory focus messages. This pre-testing study involved 30 university students who were randomly assigned to one of two treatment conditions: promotion or prevention regulatory focus message (n = 15 per group). The data were analysed with an independent samples t-test. The advertisement with the promotion-focused message was more persuasive than that with the prevention-focused message. The findings suggest guidelines for practitioners to devise effective strategies when designing advertisements that will not only help firms obtain personal benefits but also benefit society and the environment.

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)0.007
metaresearch head score (Gemma)0.015
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 score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.053
GPT teacher head0.305
Teacher spread0.252 · 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
Published2023
Admission routes1
Has abstractyes

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