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Record W2078897463 · doi:10.1108/eb047415

CANADIAN CONSUMERS' PERCEPTIONS OF PRODUCTS MADE IN NEWLY INDUSTRIALIZING EAST ASIAN COUNTRIES

2001· article· en· W2078897463 on OpenAlexaboutno aff
Sadrudin A. Ahmed, Alain d’Astous

Bibliographic record

VenueInternational Journal of Commerce and Management · 2001
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsnot available
Fundersnot available
KeywordsNewly industrialized countryEast AsiaWarrantyContext (archaeology)Product (mathematics)OriginalityBusinessDeveloped countryPerceptionDeveloping countryQuality (philosophy)MarketingGeographyPolitical sciencePsychologyEconomicsEconomic growthChinaSociologyDemography

Abstract

fetched live from OpenAlex

This article presents the results of a survey of 250 Canadian male consumers. In this study consumer judgements of products made in both highly and newly industrializing countries were obtained in a multi‐attribute and multidimensional context. The results show that younger and less affluent respondents react more favorably towards products made in newly industrializing East Asian countries. The country‐of‐origin image of East Asian countries is less negative for products that generate a medium level of involvement (e.g., a VCR). This negative image of East Asian countries is attenuated by providing other product‐related information to consumers such as brand name and warranty. East Asian countries are perceived more negatively as countries of design than as countries of parts and assembly. In comparison with products made in highly developed countries, products made in East Asia are perceived to be poorer in terms of performance, quality and originality but more economical.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.143
Threshold uncertainty score0.287

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.029
GPT teacher head0.269
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 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

Citations82
Published2001
Admission routes1
Has abstractyes

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