Stochastic Sequential Allocations for Creative Crowdsourcing

Creative crowdsourcing is an innovative online business model in which a platform marshals independent professionals (e.g., designers) to conduct creative work projects. Typically, clients submit project requests stochastically to a platform which possesses a pool of registered designers. For each submitted project, designers decide whether to participate and attempt to submit a design, and the client either chooses a winner among all submissions, or rejects them all, based on subjective criteria. In general, platforms cannot control individual designers directly because of the nature of the freelance market, incurring possible mismatches between designers and arriving projects. To tackle the problem, we present a dynamic control policy applied to the maximum number of participants for each arrived project. Our study reveals that the optimal policy follows an inverted‐U‐shaped function of the project value, highlighting the importance of applying a stronger restriction on the number of participants for some sufficiently high‐valued projects. In addition, the optimal policy we have developed allows the platform to gain higher rewards judiciously even when the market is more volatile. Furthermore, extensive numerical studies have been conducted to glean managerial insights. Specifically, the optimal policy becomes more beneficial even when more designers are available, which is counter‐intuitive to the common‐sense notion that control should be more valuable when designers are scarcer; and the optimal policy is further shown to be robust when the objective is changed from maximizing the total reward to maximizing the total number of successful projects.