Optimal crowdsourcing contests

Shuchi Chawla, Jason D Hartline, Balasubramanian Sivan*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)80-96
Number of pages17
JournalGames and Economic Behavior
Volume113
DOIs
StatePublished - Jan 2019

Keywords

  • All-pay auction
  • Approximation
  • Bayes–Nash equilibrium
  • Crowdsourcing contest

ASJC Scopus subject areas

  • Finance
  • Economics and Econometrics

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