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Incentivizing High Quality Entrants When Creators Are Strategic

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  • Felicia Nguyen

Abstract

We study how a platform should design early exposure and rewards when creators strategically choose quality before release. A short testing window with a pass/fail bar induces a pass probability, the slope of which is the key sufficient statistic for incentives. We derive three main results. First, a closed-form ``implementability bounty'' can perfectly align creator and platform objectives, correcting for incomplete revenue sharing. Second, front-loading guaranteed impressions is the most effective way to strengthen incentives for a given attention budget. Third, when impression and cash budgets are constrained, the optimal policy follows an equal-marginal-value rule based on the prize spread and certain exposure. We map realistic ranking engines (e.g., Thompson sampling) into the model's parameters and provide telemetry-based estimators. The framework is simple to operationalize and offers a direct, managerially interpretable solution for platforms to solve the creator cold-start problem and cultivate high-quality supply.

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  • Felicia Nguyen, 2025. "Incentivizing High Quality Entrants When Creators Are Strategic," Papers 2509.14102, arXiv.org.
    • Handle: RePEc:arx:papers:2509.14102
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