How Consumers’ Content Preference Affects Cannibalization: An Empirical Analysis on E-book Market
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite the increasing popularity of e-books and the growing maturity of e-book markets, there have been few studies on the e-book channel and its influence on the existing paper book channel. In order to fill this gap in the literature, we investigate the extent to which e-book release boosts or cannibalizes demand for the paper book. Using unique data on the actual sales of paper books and e-books, we conduct an empirical analysis on this question. Our results without addressing selection bias suggest that the e-book release boosts the demand for the paper book. However, this effect disappears once we control for selection bias by using matching. We also find that the impact of ebook release is moderated by consumers’ content preference. Specifically, the e-book release increases paper book sales as well as total sales for those books with light contents that consumers prefer to consume through a digital channel. In contrast, the books that appeared on the bestseller lists experience significant demand cannibalization from e-book release.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it