Dynamics of an Agent-Based Opinion Model with Project-Based Interorganizational Networks

Abstract

The opinions of multi-agent in the project-based interorganizational networks (PIONs) are identified as major roles in the success of interorganizational cooperation. Existing models of opinion dynamics consider only the influence of the heterogeneous bounded confidence of neighbors on agents, ignoring the combined effect of the global reputation of the entire network, neighbors' similar opinions, and their degree of stubbornness. In this paper, a perspective exchange framework for project-based interorganizational networks is used to identify agents who can proactively raise the level of their opinions. A modified agent-based opinion model of PIONs based Hegselmann-Krause (HK) model is then proposed. Extensive case experiments are conducted on an artificially generated network dataset, and the theory of Shannon-like entropy is applied to verify the stability and convergence of the proposed model. The simulation results show that the increase in the proportion of global reputation leads the group to evolve toward consensus and converge slowly, while the increase in the proportion of neighbor's opinions makes the group evolve toward polarization and converge quickly.