Exploring Demand toward Celebrity Memorabilia: Do Celebrities Never Really Die?
Bibliographic record
Abstract
Celebrities always seem larger than life; it is when they die that we remember they are only human. With the emergence of the Internet and social networking sites, consumers are able to follow the daily activities of their favorite celebrities. After a celebrity’s death, consumers exhibit a stronger interest in the lives of these celebrities and demand for celebrity-related products increases sharply. The aim of the present study is to examine young consumers’ responses to celebrity deaths and explore the major factors that lead to increased demand for celebrity memorabilia and merchandise. Specifically, this research will attempt to present why young consumers exhibit such a sudden and strong interest in celebrity-related products after their death and why these products are cherished so greatly. Factor analysis is applied and the results indicate that a celebrity’s death increases young consumers’ demand for memorabilia due to five major factors. These factors include immortality of the celebrity, keepsake value & deep-felt love as well as uniqueness of the celebrity, prestige and financial value attached with the product and wide availability & increased media promotion. Based on these factors, it can be argued that consumption of celebrity merchandise is motivated by the attachment and significance of the celebrity to the young consumer before death. These results are important for marketers to grasp the effect of death on the consumption of celebrity merchandise. Online and traditional retailers need to understand the major factors attracting consumers to celebrity memorabilia and merchandise so that they can respond quickly and efficiently to sudden demand fluctuations.
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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 | 0.006 |
| 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 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".