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Record W2971814564 · doi:10.1002/cjas.1546

Media technology shifts: Exploring millennial consumers' fashion‐information‐ seeking behaviors and motivations

2019· article· en· W2971814564 on OpenAlexvenueno aff
Aimee Jones, Jiyun Kang

Bibliographic record

VenueCanadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsnot available
Fundersnot available
KeywordsGratificationPopularitySocial mediaSeekersAdvertisingThematic analysisAutonomyNetnographyDigital mediaClothingMedia consumptionInformation seekingQualitative researchInternet privacyBusinessSociologyPsychologyComputer scienceWorld Wide WebPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

Abstract There has been an evident decline in the number of subscriptions for traditional media while the digital forms of consumer‐centric media, specifically in the fashion area, including fashion blogs and social media, have ascended to unprecedented popularity for information‐seeking, especially with millennials. Despite the transformation of media consumption patterns, the literature has primarily focused on information givers' perspectives, while it has paid little attention to information seekers' standpoints. Utilizing thematic analysis of qualitative data collected from six focus groups, we found key motivations driving millennials to turn to digital fashion media for their information needs: search autonomy, virtual storage, instant gratification, visual inspiration, gratuitous information, and authenticity. This study provides insight into how to strategically respond to consumers' needs in the current digitalized media 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0010.005
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.102
GPT teacher head0.291
Teacher spread0.189 · 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 teacher head, not a consensus.

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

Citations24
Published2019
Admission routes1
Has abstractyes

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