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Record W1596922546 · doi:10.1108/13612020410537889

Perceptions of countries as producers of consumer goods

2004· article· en· W1596922546 on OpenAlexaff
Sadrudin A. Ahmed, Alain d’Astous

Bibliographic record

VenueJournal of Fashion Marketing and Management · 2004
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsHEC MontréalUniversity of Ottawa
Fundersnot available
KeywordsBusinessContext (archaeology)MarketingProduct (mathematics)PerceptionQuality (philosophy)Chinese marketValue (mathematics)Developing countryAdvertisingEconomicsChinaEconomic growthPolitical sciencePsychologyGeography

Abstract

fetched live from OpenAlex

This article presents the results of a survey of 209 Mainland Chinese male consumers carried out in the late 1990s. In this study, consumer judgements of products made in both highly and newly industrialised countries were obtained in a multi‐attribute and multi‐dimensional context. As expected, the results showed that Chinese consumers' perceptions of country of design and country of assembly were much more positive for products made in highly industrialised countries than for those made in newly industrialised countries. However, some exceptions to this are addressed. A multi‐attribute analysis with country‐of‐origin variables indicates that the perception of a T‐shirt quality was strongly related to price and product satisfaction assurance, whereas the perception of a T‐shirt purchase value was mainly linked to satisfaction assurance. It is therefore concluded that Chinese consumers, having recently emerged from a totalitarian state‐controlled market condition, are in the process of forming enduring attitudes towards products made in foreign countries. This provides excellent opportunities for countries/brands that wish to build an image of fashion leadership in the Chinese market to gain a first‐mover advantage.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.633
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.014
GPT teacher head0.255
Teacher spread0.240 · 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.

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

Citations77
Published2004
Admission routes1
Has abstractyes

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