Evolutionary game-based performance/default behavior analysis for manufacturing service collaboration supervision

Abstract

Platform-based manufacturing service collaboration (MSC) is a growing trend of manufacturing enterprise cooperation in the era of digital economy. Multiple users have the right to choose collaboration online or offline. During the process of platform-MSC, the collaboration behavior choices may make other stakeholders’ behaviors change passively, which result in the complex platform operation. Hence, platform-based MSC supervision considering the performance/default behavior of multiple users is crucial. This article proposes a tripartite evolutionary game model (i.e. consumers, providers and the operator) to analyze complex behaviors of users in platform-based MSC. This model can explore the impact of platform supervision measures on user performance/default behavior taking into account users’ bounded rationality and subjective preferences by simulating the learning, imitation, and dynamic evolution of collaboration behaviors among users. The experimental results provide insights into supervision measures optimization for platform-based MSC.