Free E-Books May Increase Print Sales: A Study With Mixed Results
Bibliographic record
Abstract
A Review of: Hilton, J. III, & Wiley, D. (2010). The short-term influence of free digital versions of books on print sales. Journal of Electronic Publishing, 13(1). Objective – To determine whether the availability of free digital versions of books impacts print sales. Design – Quantitative data comparison. Setting – University Instructional Psychology Department. Subjects – A total of 41 books, each with a free digital version and a traditional print version. Methods – This study used Nielson BookScan data to track print book sales during a 16-week period, 8 weeks before a free digital version of the book became available and 8 weeks after the availability of the free digital version. The authors tracked 41 books and organized them into four categories. The first included 7 nonfiction books, the second consisted of 5 science fiction/fantasy books, the third included 5 science fiction/fantasy books released together by Random House, and the fourth group consisted of 24 science fiction/fantasy books released by Tor Books. The books released by Tor Books, unlike the other books in the study, were available by free download only if a person registered for Tor’s newsletter and the downloads were only available for one week. When a free digital book from any of the other three groups was released, it remained available for several weeks, and more often, indefinitely. Main Results – Combined print sales of the nonfiction titles in the first group increased 5% after the release of a free digital copy. The majority of the science fiction/fantasy books in the second group also had an increase in post-free release sales, with a combined increase of 26%. The combined sales of the Random House titles increased by 9% after the release of the free digital versions. However, in stark contrast to the results of the first three groups, the fourth group of Tor books had a combined decrease in print sales of 18%. While the authors were not able to explain this difference with certainty, they point out that the Tor model for releasing the free digital books (making the free books available for only one week and requiring registration in order to download the books) was substantially different from the models used by the other publishers. Conclusion – The study suggests a positive relationship may exist between free digital books and short-term print sales. However, the availability of free digital books did not always lead to increased print sales. The authors acknowledge a number of factors not fully accounted for, including the timing of the free digital release, the promotion it received, and the differences in the size of the audiences for the various books studied. Ultimately, however, the authors believe the data indicates that when free digital books are offered for a period of time longer than a week, without requiring registration, print sales will increase.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.092 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".