Capacity pooling games in crowdsourcing services

In crowdsourcing services, employers often post some complex (or difficult) tasks that individual workers cannot complete independently. In this paper, we investigate that a group of independent workers willingly form a workers coalition by pooling their capacities together to jointly complete a crowdsourcing task, with the goal of being to obtain a reward from an employer. The capacity pooling games in the crowdsourcing service setting are formulated as optimization problems. Using the duality theory of a linear program, we not only establish that the core of the capacity pooling game is nonempty but also provide a simple way to compute a fair profit allocation policy in the bidding mode, employment mode and contrast mode of crowdsurcing services, respectively. Then, we further analyze the capacity pooling games with concave investment cost and convex quality reward structures, which exhibit the economies of scale and quality incentives. More interestingly, we give a constructive proof to the nonemptiness of the core of the resulting capacity pooling game with nonlinear structures.