Effect of Crowd Voting on Participation in Crowdsourcing Contests

Liang Chen, Pei Xu, De Liu

Research output: Contribution to journalArticlepeer-review

32 Scopus citations


While expert rating is still a dominant approach for selecting winners in contests for creative works, a few crowdsourcing platforms have recently used “crowd voting” for winner selection–that is, let users of the crowdsourcing community publicly vote for contest winners. We investigate how a contest’s reliance on crowd voting for winner selection, defined as the percentage of crowd-voted prizes to the total prize sum (in dollar amounts), affects contest participation. Drawing upon expectancy theory and tournament theory, we develop a theoretical understanding of this relationship. Using a novel dataset of contests employing both crowd voting and expert rating, we find that a contest’s reliance on crowd voting is positively associated with participation. Specifically, every 10% increase in the crowd-voting reliance can boost users’ odds of participation by about 7%. Moreover, crowd voting is more appealing to users whose expertise is not high and whose status in the crowdsourcing community is high.

Original languageEnglish (US)
Pages (from-to)510-535
Number of pages26
JournalJournal of Management Information Systems
Issue number2
StatePublished - Apr 2 2020

Bibliographical note

Publisher Copyright:
© 2020, © 2020 Taylor & Francis Group, LLC.


  • Crowdsourcing
  • crowd voting
  • crowdsourcing contests
  • expectancy theory
  • expert rating
  • tournament theory
  • winner-selection mechanisms


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