Crowdsourcing Tasks Allocation based on Incentives via Group Multirole Assignment

Motivation is a key factor in improving the enthusiasm and work performance of crowdsourcing workers. It is important for crowdsourcing platforms to allocate tasks. In order to increase the enthusiasm of workers and thus improve their work performance, this paper formalizes the Crowdsourcing Tasks Allocation (CTA) based on incentives and proposes an adaptive task allocation method with Role-Based Collaboration (RBC) and its E-CARGO model by considering the dynamic changes of the weights of the evaluation factors and the evaluation values. Large-scale randomized experiments show that this method is effective and reliable, which can maximize the performance of the team. More importantly, it can motivate workers under the influence of multiple incentive factors and the environment of real-time growth of crowdsourcing tasks.