The Effects of Publicity on Demand: The Case of Anti-Cholesterol Drugs
Bibliographic record
Abstract
Over the past 10 years there has been increased recognition of the importance of publicity as a means of generating product awareness. Despite this, previous research has seldom investigated the impact of publicity on demand. We contribute to the literature by (i) proposing a new method for the interpretation of publicity data, one that maps the information in news articles (or broadcasts) to a multidimensional attribute space; (ii) investigating how different types of publicity affect demand; and (iii) investigating how different types of publicity interact with firms’ own marketing communication efforts. We study these issues for statins. We find that publicity plays an important role both for expanding the market for statins and for determining which statins patients or physicians choose. We also find evidence that publicity can serve as either a substitute or a complement for traditional marketing channels depending on the complexity of the information type. We argue that the interaction results are driven by the relative strengths of the corroborative and rational inattention functions in publicity. These results suggest that managers should be aware of the interactions between publicity and traditional marketing channels to better determine how to allocate their marketing expenditures.
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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 | 0.006 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.017 | 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".