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Record W4404913191 · doi:10.1007/s43546-024-00755-x

Perceived values of luxury fashion brands—evidence from Indonesian Millennials

2024· article· en· W4404913191 on OpenAlexaff
Yan Sun, Rachel Wang, Huifeng Bai, Georgina Whyatt, Tesalia Tamara Ohandi

Bibliographic record

VenueSN Business & Economics · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsIndonesianAdvertisingBusinessPsychology

Abstract

fetched live from OpenAlex

Abstract Consumers in the Association of Southeast Asian Nations (ASEAN) countries represent rapid growth, and they are anticipated to become next wave of important markets for luxury fashion sector. This empirical study aims to examine millennials’ perceptions towards luxury fashion brand values and how these influence their purchase intentions in Indonesia, the biggest market in the ASEAN. Through quantitative research, the primary data was collected from 301 self-completed online questionnaires. It is revealed that Indonesian millennials regard the consumption of luxury fashion brands as an investment. Meanwhile, ethical and sustainability issues have become increasingly important in consumers’ decisions to purchase luxury fashion brands. Based upon the value-based segmentation of luxury consumption, the present study recognizes that Indonesian millennials prioritize symbolic and financial values and seek conspicuousness in line with self-identity.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.253
Teacher spread0.213 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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