The Effect of Brand Position on Consumer Choices of Luxury Brands: A Cross- Cultural Study Between British and Chinese Consumers
Bibliographic record
Abstract
This dissertation is grouped by topics—luxury brands, values, consumer luxury shopping behaviour, luxury brand management, and luxury brand differentiations. It intends to address the influence of luxury brand positioning on consumer choices. Despite various changes in internal and external environment, little research has investigated the differences of Chinese and British luxury markets. Therefore, in this article, an approach to understanding the positioning of luxury brands and luxury consumption behaviour is presented. The existing definitions are reviewed, which suggests that consumer consumption decisions of luxury brands can be evaluated by 39 items models. Based on this, the purpose of this paper is to focus on and to offer a deeper understanding of the luxury brand positioning effects. In order to fulfil this purpose, four research objectives and three propositions are expounded focusing on the variables of consumer choice decision as well as an explanation of the brand unique personality. By following the research objectives and propositions as a direction guide, literature studies are critically analysed resulting in a composite framework which guides the data interpretation. This research takes a qualitative case study for collecting secondary data by means of previous research data. The analysed results demonstrate that there would be a difference in the effect of brand positioning between the Chinese and British consumers. By identifying the equity of different luxury brands, consumer choice behaviour can be better understood, and this may assist luxury brand managers in their exploration of luxury market.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".