
TL;DR
This paper develops mechanisms for maintaining public goods in crowdsourced systems, balancing incentives and truthful reporting, with implications for digital platforms offering adjustable recommendation settings.
Contribution
It introduces a novel mechanism that reduces contributions and restricts access to promote truthful reporting and participation in public goods maintenance.
Findings
Optimal mechanism pairs reduced contributions with restricted access.
At most two membership tiers are optimal for maximizing welfare.
Platforms can benefit from simple user-adjustable recommendation settings.
Abstract
We design mechanisms for maintaining public goods which require periodic in-kind contributions, motivated by incentives problems facing crowd-sourced recommender systems. Utilitarian welfare is maximized by redistributive policies which are infeasible when group members can leave or misreport their preferences. An optimal mechanism reduces contributions for group members with low benefit-cost ratios to encourage participation; and pairs reduced contributions with restricted access to the good to ensure truthful reporting. At most two membership tiers are offered at the optimum, indicating that ecommerce and digital content platforms may benefit substantially from offering simple user-adjustable recommendation settings.
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Taxonomy
TopicsMobile Crowdsensing and Crowdsourcing · Game Theory and Voting Systems · Expert finding and Q&A systems
