Manufacturer’s “1-Up” from Used Games: Insights from the Secondhand Market for Video Games
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
The video game industry has a robust secondhand market for games, even though some of the major gaming-console companies possess the means to shut it down. What is the special ingredient in this industry that would incentivize a manufacturer to give tacit approval to buying and selling used games? In this study, leveraging a game-theoretic model, we investigate the effect of gaming console on a manufacturer’s strategy in the presence of a secondhand market for games. We find that when the manufacturer offers a console that provides additional value outside of playing games (e.g., media hub with apps), the secondhand market improves the manufacturer’s profit, consumer surplus, and social welfare, all at the same time. Moreover, the manufacturer enjoys greater benefit from the secondhand market as the intrinsic value of the console increases. This is in stark contrast with cases where there are no consoles involved or the consoles do not offer any intrinsic value; in such settings, the manufacturer would opt to shut down the secondhand market. Overall, our results have implications that apply not only to the past and present of the gaming industry but also to its future and to other types of platform-based markets for contents.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it