Three-Party Evolutionary Game Model of Stakeholders in Mobile Crowdsourcing

As a new paradigm to solve problems by gathering the intelligence of crowds, mobile crowdsourcing has become one of the hot spots in academic and industrial fields. Task requester, platform, and crowd workers are stakeholders in mobile crowdsourcing, which inevitably leads to conflicts of interest. In order to solve this problem, this article constructs a three-party evolutionary game model among task requester, platform, and crowd workers. This model also considers the collusion between crowd workers and the platform to make it more realistic. Then, the replication dynamics method is utilized to analyze the evolutionary stability strategy. The strategies of rewards and penalties are given to avoid free-riding and false-reporting problems. Finally, the stability of the equilibrium point in the three-party game system is verified through simulation experiments, and the effective methods to motivate each player to choose a trusted strategy are given.

Automated summary

This article focuses on the conflicts of interest among task requester, platform, and crowd workers in mobile crowdsourcing. A three-party evolutionary game model, considering collusion between crowd workers and the platform, is constructed. The replication dynamics method is used to analyze the evolutionary stability strategy. Rewards and penalties are proposed to address free-riding and false-reporting problems. Simulation experiments verify the stability of the equilibrium point in the three-party game system and effective methods to motivate players to choose a trusted strategy.