Research Publications

We study innovation contests on crowdsourcing platforms that seek solutions to a set of problems from solvers who face capacity constraints in their solution-development efforts due to limited (financial, time, cognitive) resources. We analyze how solvers utilize their limited capacity and allocate it when competing in multiple contests by considering the moderating effects of solver uncertainty and platform growth.

We study parallel innovation contests that seek solutions from independent solvers. We analyze whether solvers should be restricted to participating in a single contest and, when restricted, whether they should observe which contests other solvers join.

We study flexible awards in innovation contests, specifically focusing on a "fuzzy" award scheme where the total award budget is known, but the distribution of it remains uncertain. This study explores how such a scheme influences solver behavior in effort and participation decisions, contrasting it with traditional award structures like winner-take-all or fixed multiple prizes.