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How to Design Crowdsourcing Contest : A Structural Empirical Analysis

In the past few years several firms have undertaken crowdsourcing initiatives to benefit from wisdom as well as labor of the consumer crowds. In particular, crowdsourcing contests where, individuals, typically unaffiliated with the firm, compete with each other to solve firms' problems to gain a monetary reward have become very popular. A key challenge faced by the firms that undertake crowdsourcing contests is to design an incentive structure which helps attract high quality solutions. Theoretical literature on tournaments, which are similar to crowdsourcing contests, suggests a high monetary reward could affect the quality of solutions in two opposite ways. On the one hand a higher reward would encourage individuals to put in more effort as there is higher return on winning increasing the quality of solutions. On the other hand, a higher reward could encourage a lot of individuals to participate increasing the competition and reducing the chances of winning for everyone. As a result each individual may put in lower effort reducing the quality of solutions. In this study, we present the first empirical evidence on how incentive structures could affect the quality of the solutions produced in crowdsourcing contests. Specifically, we develop a dynamic structural model of user participation in crowdsourcing contests. Our model captures two important characteristics of users' behavior: 1) competition among users for the award; 2) experience based learning. We also explicitly model how users make decisions on how much effort they will exert when facing the tradeoff between increasing the probability of winning and incurring higher cost. The structural model allows us to conduct several policy simulations to understand how incentive structure may affect quality of solutions produced by the crowd. Using data from Threadless.com, we find that participants put in less effort as competition for the award increases. This may indicate that increasing the reward may adversely affect the quality of the solutions produced by the crowd as it will invariably increase the competition. However, counter-intuitively the policy simulations indicate that increasing the award would increase not only the quantity but also the quality of the solutions. This is because under the new policy of higher reward, individual equilibrium behavior is different. Our policy simulations suggest that when the firm increases the award and if the additional utility from the increase in the award can offset the reduction in the probability of winning resulting from intensified competition, such that the expected payoff will …