Think global, act local! A cross-cultural study of five Nutella websites on adaptation
Bibliographic record
Abstract
The aim of the present research is to analyse commercial websites of the same global brand from a cultural perspective looking for the presence of cultural patterns which might reflect marketers’ awareness for the need of cross-cultural adaptation.\nThrough a qualitative content analysis of main pages of in total five Nutella websites addressing Germany, Italy, Sweden, Canada and Australia, this paper targets to investigate how a global brand adapts to local cultures and more specifically which similarities/differences can be found on its websites and how these can be related to the culture of each country. In order to do so Hall’s and Hofstede’s taxonomies are used as the framework of analysis.\nThe findings of this paper show that in addition to several cultural characteristics that influence web design other factors such as law regulations, marketing strategies and the popularity of a product play a role when designing a website for a specific host-culture.\nThe diverse results make this study a contribution to the field of cross-cultural communication as well as of digital marketing. Finally, some possible limitations are recognized and suggestions for future research are also given.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".