Abstract
Online innovation contests have been used by more and more firms for idea seeking and problem solving. Most studies of contests take the perspective of innovation seekers, and little is known about solvers’ strategies and responses. However, contest performance also relies on understanding solver responses. This paper provides insights to these questions. Specifically, we show that past experience of a solver is a good predictor of his future winning probability and that winners are more likely to be those who submit early or later during the submission period as opposed to those submit in the middle. We also find that “strategic waiting” (to submit solutions) is associated with higher winning probability. Furthermore, we show that different contests appear to attract solvers with different expertise, which invalids the common assumption of fixed solver expertise distribution across projects in previous literature. This finding has strategic implications to the design of contest parameters.
Recommended Citation
Yang, Yang; Chen, PEI-YU; and Banker, Rajiv, "Winner Determination of Open Innovation Contests in Online Markets" (2011). ICIS 2011 Proceedings. 16.
https://aisel.aisnet.org/icis2011/proceedings/ebusiness/16
Winner Determination of Open Innovation Contests in Online Markets
Online innovation contests have been used by more and more firms for idea seeking and problem solving. Most studies of contests take the perspective of innovation seekers, and little is known about solvers’ strategies and responses. However, contest performance also relies on understanding solver responses. This paper provides insights to these questions. Specifically, we show that past experience of a solver is a good predictor of his future winning probability and that winners are more likely to be those who submit early or later during the submission period as opposed to those submit in the middle. We also find that “strategic waiting” (to submit solutions) is associated with higher winning probability. Furthermore, we show that different contests appear to attract solvers with different expertise, which invalids the common assumption of fixed solver expertise distribution across projects in previous literature. This finding has strategic implications to the design of contest parameters.