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Optimal crowdsourcing contests

Shuchi Chawla, Jason D. Hartline and Balasubramanian Sivan

Games and Economic Behavior, 2019, vol. 113, issue C, 80-96

Abstract: We study the design and approximation of optimal crowdsourcing contests. Crowdsourcing contests can be modeled as all-pay auctions because entrants must exert effort up-front to enter. Unlike all-pay auctions where a usual design objective would be to maximize revenue, in crowdsourcing contests, the principal only benefits from the submission with the highest quality. We give a theory for optimal crowdsourcing contests that mirrors the theory of optimal auction design: the optimal crowdsourcing contest is a virtual valuation optimizer (the virtual valuation function depends on the distribution of contestant skills and the number of contestants). We also compare crowdsourcing contests with more conventional means of procurement. In this comparison, crowdsourcing contests are relatively disadvantaged because the effort of losing contestants is wasted. We show that the total wasted effort is at most the maximum effort which implies that crowdsourcing contests are a 2-approximation to an idealized model of conventional procurement.

Keywords: Crowdsourcing contest; All-pay auction; Bayes–Nash equilibrium; Approximation (search for similar items in EconPapers)
JEL-codes: D44 D47 D82 (search for similar items in EconPapers)
Date: 2019
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