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Record W7104178477 · doi:10.1108/ejm-07-2024-0562

The impact of self-construals on bicultural consumers’ counterfeit postpurchase regret

2025· article· en· W7104178477 on OpenAlexaff

Bibliographic record

VenueEuropean Journal of Marketing · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsRegretCounterfeitPriming (agriculture)ShameIdentity (music)Acculturation

Abstract

fetched live from OpenAlex

Purpose Counterfeiting poses a growing threat to global luxury brands. While international marketing research has largely focused on the antecedents of counterfeit purchases and cross-cultural differences, the understanding of postpurchase regret remains limited. As a result, firms lack clear guidance on when to adopt specific anti-counterfeiting strategies. This study aims to address this research gap by examining how self-referential mechanisms, namely, cultural identity conflict and self-construals, shape postpurchase regret among bicultural consumers. Design/methodology/approach The authors conducted two studies to test their hypotheses. Study 1, a survey, examines how cultural identity conflict moderates the relationship between bicultural consumers’ attitudes toward counterfeits and postpurchase regret. Study 2, an experiment, demonstrates how priming self-construals can shift the source of postpurchase regret, also moderated by cultural identity conflict. Findings The findings demonstrate that bicultural consumers’ self-construals can be primed to amplify either guilt-based or shame-based postpurchase regret. However, this priming effect is most effective among biculturals who experience low levels of bicultural conflict. In contrast, for biculturals with high levels of cultural conflict, the relationship between attitudes toward counterfeit goods and postpurchase regret is significantly weaker. Research limitations/implications The authors build on their findings to propose an integrative model of counterfeit purchasing, ranging from prepurchase antecedents to postpurchase regret. Practical implications The proposed model helps companies design actionable strategies, such as activating bicultural consumers’ guilt and shame emotions, subsequently increasing their postpurchase regret to deter unethical counterfeit purchases. Originality/value First, this paper challenges the common approach in the counterfeiting literature of examining only prepurchase motivations, which limits its utility for explaining whether a consumer will repeat counterfeit purchases over time. Second, it further dissects the two negative emotions, guilt and shame, that come along with postpurchase regret of counterfeit products. Third, it contributes to the cultural identity literature by examining the interaction between consumers’ self-construals and cultural identity conflict.

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)0.003
metaresearch head score (Gemma)0.008
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 score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.265
Teacher spread0.249 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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