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Record W3102505501 · doi:10.5539/ijms.v12n4p30

Brand Activism, the Relation and Impact on Consumer Perception: A Case Study on Nike Advertising

2020· article· en· W3102505501 on OpenAlexvenueno aff
Bassant Eyada

Bibliographic record

VenueInternational Journal of Marketing Studies · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsnot available
Fundersnot available
KeywordsNikeAdvertisingBusinessMarketingPerceptionBrand managementProfit (economics)Social marketingProfit marginAdvertising campaignBrand equityBrand loyaltyPsychologyEconomics

Abstract

fetched live from OpenAlex

Recently various brands have been promoting their products through social issues that consumers are engaging with, by moving from social corporate responsibility to leadership and harnessing the brands' power to inspire social and environmental problems and change. Whether brands are creating social leadership campaigns to raise profit margins, or because they simply care about the issues they discuss, several brands have been playing this role through their campaigns, as seen for example with brands like Nike, Under Armor, Gillette, and Uber. This paper follows the qualitative methodology by proposing an analytical study of the advertising messages and concepts through a case study of Nike advertising promoting their products through social leadership campaigns, and an analysis which aims to measure the impact of these campaigns on brand image, profit margins, and the means the social causes are being perceived by the consumers.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.003
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.002
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 head0.027
GPT teacher head0.308
Teacher spread0.281 · 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 designCase report
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

Citations65
Published2020
Admission routes1
Has abstractyes

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