A Structural Analysis of the Role of Superstars in Crowdsourcing Contests

40 Pages Posted: 21 Apr 2016 Last revised: 20 Sep 2017

See all articles by Shunyuan Zhang

Shunyuan Zhang

Harvard University - Business School (HBS); Harvard University

Param Vir Singh

Carnegie Mellon University - David A. Tepper School of Business

Anindya Ghose

New York University (NYU) - Leonard N. Stern School of Business

Date Written: September 19, 2017

Abstract

We investigate the long-term impact of competing against superstars in crowdsourcing contests. Using a unique 50-month longitudinal panel data set on 1677 software design crowdsourcing contests, we illustrate a learning effect where participants are able to improve their skills (learn) more when competing against a superstar than otherwise. We show that an individual’s probability of winning in subsequent contests increases significantly after she has participated in a contest with a superstar coder than otherwise.

We build a dynamic structural model with individual heterogeneity where individuals choose contests to participate in and where learning in a contest happens through an information theory-based Bayesian learning framework. We find that individuals with lower ability to learn tend to value monetary reward highly, and vice versa. The results indicate that individuals who greatly prefer monetary reward tend to win fewer contests, as they rarely achieve the high skills needed to win a contest. Counterfactual analysis suggests that instead of avoiding superstars, individuals should be encouraged to participate in contests with superstars early on, as it can significantly push them up the learning curve, leading to higher quality and a higher number of submissions per contest. Overall, our study shows that individuals who are willing to forego short-term monetary rewards by participating in contests with superstars have much to gain in the long term.

Keywords: Crowdsourcing Contests, Superstar Effect, Bayesian Learning, Utility, Economics of Information System, Dynamic Structural Model, Dynamic Programming, Monte Carlo Markov Chain

Suggested Citation

Zhang, Shunyuan and Singh, Param Vir and Ghose, Anindya, A Structural Analysis of the Role of Superstars in Crowdsourcing Contests (September 19, 2017). Available at SSRN: https://ssrn.com/abstract=2764553 or http://dx.doi.org/10.2139/ssrn.2764553

Shunyuan Zhang

Harvard University - Business School (HBS) ( email )

Soldiers Field Road
Morgan Hall
Boston, MA 02163
United States

Harvard University ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States

Param Vir Singh (Contact Author)

Carnegie Mellon University - David A. Tepper School of Business ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States
412-268-3585 (Phone)

Anindya Ghose

New York University (NYU) - Leonard N. Stern School of Business ( email )

44 West 4th Street
Suite 9-160
New York, NY NY 10012
United States

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