Doctor of Philosophy (PhD)
Stephenson Department of Entrepreneurship & Information Systems
With the advances in internet technologies and the emergence of crowdsourcing, organizations are now increasingly looking outside their boundaries for solving problems. These new technologies have enabled companied to tap into online crowds with variety of skills, talents, experience, and knowledge. Yet, the success of crowdsourcing depends on high quality participation of crowdsourcing individuals and teams. In recent studies, examining the effect of simultaneous collaboration and competition mechanisms on individual and team performance in crowdsourcing have received considerable attention. But, none of these studies examined how different levels of collaboration affect team performance in crowdsourcing contests. In this paper, using a rich data set from a crowdsourcing platform, Kaggle.com, we study how team discussion-forum performance and solution-sharing performance affect its performance in online crowdsourcing contests. Our results suggest that team’s discussion-forum performance and solution-sharing performance have significant effect on its competition performance. We also found that for a team high in intellectual capital, an increase in its discussion-forum performance decreases their competition performance. Moreover, we found that the time gap between final solution submission and competition deadline moderates the relationship between discussion-forum performance and competition performance and the relationship between solution-sharing performance and competition performance. To further our findings and to get an in-depth understanding of individuals’ collaborative behavior in crowdsourcing contests, we conducted 21 semi-structured interviews with Kaggle members. Based on the analysis results, we propose a framework for understanding individuals’ collaborative behavior in crowdsourcing contest environments. Our data analysis revealed 19 constructs of motivators, barriers and enablers for joining a team and sharing knowledge in the community. Our findings offer valuable theoretical and managerial implications for researchers and crowdsourcing sponsors to: understand collaborative behavior in crowdsourcing contests; design crowdsourcing contests and choose appropriate mechanisms for crowdsourcing; and improve the performance of individuals and teams in these contests.
Javadi Khasraghi, Hanieh, "Collaboration in Crowdsourcing Contests: Towards an Understanding of Collective Behavior in Crowdsourcing Contests" (2018). LSU Doctoral Dissertations. 4690.
Available for download on Wednesday, August 06, 2025