Effect of Crowd Voting on Participation in Crowdsourcing Contests

• 成果类型: Article
• 署名作者: Chen, Liang; Xu, Pei; Liu, De
• 署名单位: Texas A&M University System; West Texas A&M University; Auburn University System; Auburn University; University of Minnesota System; University of Minnesota Twin Cities; University of Minnesota System; University of Minnesota Twin Cities
• 刊物名称: JOURNAL OF MANAGEMENT INFORMATION SYSTEMS
• ISSN/ISSBN: 0742-1222
• DOI: 10.1080/07421222.2020.1759342
• 发表日期: 2020
• 页码: 510-535
• 关键词: innovation contests; reputation; IMPACT; idea; communities; PERSPECTIVE; performance; COMPETITION; auctions; QUALITY

摘要

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.