Comparing Strategies for Winning Expert-rated and Crowd-rated Crowdsourcing Contests: First Findings
Abstract
Many studies have been done on expert-rated crowdsourcing contests but few have examined crowd-rated contests in which winners are determined by the voting of the crowd. Due to the different rating mechanisms, determinants for winning may be different under two types of contests. Based on previous studies, we identify three types of winning determinants: expertise, submission timing, and social capital. Our initial investigation, based on 91 entries of two contests in Zooppa, supports that those variables play different roles in winning crowd-rated contests than in winning expert-rated contests. Specifically, past winning experience in crowd-rated contests predicts future success in crowd-rated contests, while past winning experience in expert-rated contests predicts future success in expert-rated contests. We discover a U-shaped relationship between the submission time and winning in both types of contests. Social capital elevates the probability of winning a crowd-rated contest only if the social capital is sufficiently high.
Recommended Citation
Chen, Liang and Liu, De, "Comparing Strategies for Winning Expert-rated and Crowd-rated Crowdsourcing Contests: First Findings" (2012). AMCIS 2012 Proceedings. 16.
https://aisel.aisnet.org/amcis2012/proceedings/VirtualCommunities/16
Comparing Strategies for Winning Expert-rated and Crowd-rated Crowdsourcing Contests: First Findings
Many studies have been done on expert-rated crowdsourcing contests but few have examined crowd-rated contests in which winners are determined by the voting of the crowd. Due to the different rating mechanisms, determinants for winning may be different under two types of contests. Based on previous studies, we identify three types of winning determinants: expertise, submission timing, and social capital. Our initial investigation, based on 91 entries of two contests in Zooppa, supports that those variables play different roles in winning crowd-rated contests than in winning expert-rated contests. Specifically, past winning experience in crowd-rated contests predicts future success in crowd-rated contests, while past winning experience in expert-rated contests predicts future success in expert-rated contests. We discover a U-shaped relationship between the submission time and winning in both types of contests. Social capital elevates the probability of winning a crowd-rated contest only if the social capital is sufficiently high.