Place branding-exploring knowledge and positioning choices across national boundaries
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine the effects of the product-specific region-of-origin (ROO) and product-specific country-of-origin (COO) on the willingness to pay a premium price for a wine label designated as a superbrand by the Italian Government: the Chianti Classico. Design/methodology/approach The paper introduces the concept of “ROO-COO distance”, defined as the importance attributed to a product-specific ROO as compared to its COO. In order to better understand whether the construct “ROO-COO distance” influences the willingness to pay a premium price, the paper considers consumers’ cross-national differences and their knowledge, distinguishing among three types of knowledge: consumers’ subjective general product knowledge, consumers’ subjective country product knowledge and consumers’ regional product experience (PE). Four hypotheses were tested focussing on Chianti Classico – a premium wine – as related to its ROO and COO (Tuscany, Italy). The authors employed a sample of 4,254 consumers originating from New World countries (Australia, USA and Canada) and Old World countries (Germany, UK, Sweden and Belgium). Findings The findings confirm that a place-of-origin influence on price-related product evaluations is country specific. Furthermore, the moderating role of consumers’ subjective product knowledge and consumers’ region-related PEs differ across countries. The ROO-COO distance was found to positively affect only Old World consumers. It was established that respondents’ subjective country/product knowledge and consumers’ regional knowledge or PEs positively moderate this relationship. Originality/value The paper links the COO and ROO effects in a single framework and analyses it at the cross-national level, while also considering the moderating effect of consumer’s knowledge.
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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 | 0.005 |
| 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 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".