Understanding Chinese consumers’ and Chinese immigrants’ purchase intentions toward global brands with Chinese elements
Bibliographic record
Abstract
Purpose This study aims to investigate how consumers respond to global brands adapting to local elements. Specifically, this study identified three factors (i.e., cultural compatibility, cultural elements authenticity and cultural pride) affecting the purchase intentions (PIs) toward global brands using Chinese elements among Chinese consumers in China and Chinese immigrants in North America. Another aim is to examine the moderating role of acculturation in the relationship between cultural pride and PIs among Chinese immigrants. Design/methodology/approach Three studies were conducted to test the hypotheses in China and North America. Confirmatory factor analysis was used to confirm the factor structure. Hierarchical regression was used to test the main effects and moderated regression analysis was used to test the moderation effect. Findings Results show that cultural compatibility, cultural elements authenticity (CEA) and cultural pride positively affect the PIs toward global brands with Chinese elements for both Chinese consumers and Chinese immigrants. Further, among Chinese immigrants, acculturation moderates the relationship between cultural pride and PIs. Originality/value This study explored the factors influencing the PIs toward global brands using Chinese elements, filling a research gap. To the best of the authors’ knowledge, this study is the first to examine how perceived CEA affects consumers’ PIs toward global brands with Chinese elements. Further, the findings have implications for global brands that want to target Chinese consumers and Chinese immigrants in overseas markets.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".