The effect of respondents' nationality and familiarity with a product category on the importance of product attributes in consumer choice: Globalization and the evaluation of domestic and foreign products
Bibliographic record
Abstract
This study compared the perceptions of 376 Japanese and 191 Canadian consumers concerning the importance of different product attributes for categories of products at various stages of globalization. There was less multivariate statistical difference between the two countries for those products at a more advanced stage of globalization (consumer electronics and clothing vs. food). The joint effects of the degree of familiarity with the category of product and the country of the respondent on the importance of the product attributes were tested. The effect of familiarity was found to result in a significant statistical multivariate difference for the clothing category only. The observed statistical power of the effect of country of respondent confirmed that more statistical difference was apparent for the least globalized product. No multivariate significant statistical interaction was found between familiarity and country of respondent. Using a multi‐attribute model, the evaluation of the three categories of product was computed for seven different countries of manufacture. Comparison of the total scores of each country for each product category for the Japanese and the Canadian samples confirmed that the most globalized product showed least difference in its evaluation between countries of manufacture. A well‐known strong bias toward domestic products was, however, observed in both samples.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".