The Influence of the Culture dimension 'Power Distance' on product choice: A Cross Cultural Exploration of Effects of Country of Origin on the Choice of Branded Products
Bibliographic record
Abstract
This thesis investigates how cultural traits, such as the cultural dimension of Power Distance, influence preference for foreign made branded products. Cultural background influences several aspects of human behaviour, including the behaviours of consumers. In marketing, individual cultural differences affect consumers’ choice as well as their response to \nadvertising message and brand associations. One example, impact on consumer choice, is related to the country of origin (COO) of the product. \nThe effect of COO has been extensively explored in the literature. However, cultural frameworks like those of Hofstede (2001) have seldom been considered as a factor explaining the variability of consumers’ preference (or avoidance) for products originating in different countries. The objective of this research is to identify how cultural aspects affect product choice for foreign made branded products. A quantitative cross-cultural study was conducted to explore Hofstede’s cultural dimension of Power Distance. This study found that the replication of PDI measures within students samples from Brazil (UDESC) and from Canada (UoGuelph) do not replicate the variations of PDI observed between these two countries in the theoretical background. Yet, the results from the discrete choice experiment show that individuals from UDESC differ from individuals from UoGuelph when choosing products. Prestige products are more preferred by the individuals from UDESC than by individuals from UoGuelph. However, \nthe impact of COO on the preference for prestige branded product is bound to the product type. When it comes to price sensitiveness, individuals from UDESC show less price sensitiveness to prestige branded product than individuals from UoGuelph, but this may also be product bound.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".