Incentive Scheme for Crowdsourcing Considering Different user Relationships

Crowdsourcing is a way of collecting adequate and valuable data from a group of users with sensors-embedded-in mobile devices. Because of the information asymmetry between crowdsourcer and users, one problem called moral hazard may arise, which is the crowdsourcer has no idea about whether the users will provide qualified data and how much effort exerted by them. Accordingly, it is necessary to introduce contract-based incentive mechanism to provide participants with a certain reward to overcome the moral hazard problem, so as to achieve the purpose of encouraging more users to participate data collection. A novel contract is proposed to model one crowdsourcer and multiple users engaged in exchange for data and money, in which the users are of different relationships, which are cooperative, competitive, and independent. Then, we derive the optimal contract that maximizes the crowdsourcer's utility while achieving the benefits of the users. Finally, through simulations, we reveal the key parameters' influences on the crowdsourcer's utility under three relationships, and shows the proposed contracts are efficient and effective.