Globalization or Localization: Global Brand Perception in Emerging Markets
Bibliographic record
Abstract
With the globalization of world economy, more brands from emerging markets have entered the international market, which brought changes to the competitive landscape previously dominated by global brands from developed countries. It becomes more critical for marketing managers to understand consumers’ perceptions of the two types of global brands: traditional global brands from developed countries and emerging global brands from developing countries, and to uncover the changes in consumers’ purchase intentions in the new competitive environment. This study attempts to identify factors influencing consumers’ purchase intentions concerning the aforementioned two types of global brands. The results indicated that consumers’ interpretation of global brands is becoming increasingly complicated. In addition to the already established pathway of “perceived brand globalness (PBG)” influencing consumers’ brand attitude (hereinafter referred to as “BA”) and purchase intentions, there emerged a new pathway of “perceived brand localness (PBL)” influencing consumers’ brand perception and purchase intentions. These two pathways have different effects on traditional global brands and emerging global brands. Specifically, for traditional global brands, PBG has greater influence than PBL; for emerging global brands, PBL has more influence than PBG.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".