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Record W2151470721 · doi:10.5539/ijms.v6n6p34

Consumer Perceived Value of Salon Hair Coloring in China

2014· article· en· W2151470721 on OpenAlexvenueno aff
Xin Zhao

Bibliographic record

VenueInternational Journal of Marketing Studies · 2014
Typearticle
Languageen
FieldPsychology
TopicColor perception and design
Canadian institutionsnot available
Fundersnot available
KeywordsValue (mathematics)SalonMarketingChinaDemographicsBusinessProduct (mathematics)AdvertisingQuality (philosophy)PerceptionService (business)PsychologyMathematicsSociologyGeographyStatistics

Abstract

fetched live from OpenAlex

The primary objective of this study is to examine how Chinese consumers perceive the value of salon hair coloring? Based on the findings from a qualitative study and literature review on consumer perceived value (CPV), we developed a survey to measure Chinese consumers’ perceptions of quality value, emotional value, epistemic value, social value, monetary cost, time/effort cost, and health risk cost of salon hair coloring. Quality value and monetary cost were found to be the most important dimensions for Chinese consumers. The results suggest that the model for CPV proposed in this study could be beneficially applied to other areas, such as to other product/service categories, other demographics, and in other cultural settings.

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 score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.369
Teacher spread0.337 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

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