An experimental investigation of the use of brand extension and co‐branding strategies in the arts
Bibliographic record
Abstract
Purpose The purpose of this study is to examine the impact of two different extension strategies, namely brand extension and co‐branding, on consumer attitude toward an extension in the context of the arts. Design/methodology/approach An experiment was conducted in which the type of extension strategy, as well as other variables identified as potentially having an impact on consumer attitudes, were manipulated. Findings The results showed that, whatever extension strategy is chosen, the new product should be congruent with the arts organization's activities and should be of low complexity. If these conditions are met, a co‐branding strategy appears to be preferable. Research limitations/implications Because only two arts organizations were analyzed in this study, i.e. museums and symphonic orchestras, future studies should consider other domains of the arts. New products introduced as brand extensions should be simple and congruent with the business activities of the arts organization. If the product is not congruent with the organization's activities, then simple brand extension appears be a better strategy. Originality/value This study has examined the extent to which marketing strategies that work for conventional goods and services may succeed in the case of artistic and cultural products. It brings valuable knowledge to managers of arts organizations and marketing researchers with respect to the impact of brand extension strategies in the arts.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".