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Record W3041829775 · doi:10.69554/ftgy5757

Nationalism vs globalism: Customer citizenship behaviour and foreign product purchase intention

2020· article· en· W3041829775 on OpenAlexaff
Wootae Chun

Bibliographic record

VenueJournal of cultural marketing strategy. · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Trade and Competitiveness
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsGlobalismNationalismCitizenshipProduct (mathematics)BusinessPsychologyPolitical scienceGlobalizationLawMathematics

Abstract

fetched live from OpenAlex

This paper examines the interplay between socio-psychological variables linked to nationalism and globalism (namely animosity, ethnocentrism and cosmopolitanism), customer citizenship behaviour (CCB) and foreign product purchase intention in the context of global marketing strategy. The paper focuses most closely on the concept of CCB, which has received little attention in international marketing research, while considering nationalistic outbursts and globalist tendencies. CCB and purchase intention models were developed and tested using multilevel mixed-effects linear regression. Results indicate that both consumer animosity and ethnocentrism are negatively associated with CCB toward foreign firms. However, consumer cosmopolitanism has a positive impact on CCB toward foreign firms. The findings also confirm that consumers with CCB toward foreign firms are more likely to buy foreign products. Finally, the results reveal that consumers exposed to trustworthy consumers with CCB toward foreign firms are more likely to purchase foreign products. The setting selected to test models is Chinese and South Korean consumers’ attitudes toward Japan. A total of 160 Chinese and 163 South Korean consumers were sampled.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score0.571

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.035
GPT teacher head0.251
Teacher spread0.216 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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