Virtual Enterprise risk management under asymmetric information

Abstract

Information plays an important role in the decision process of risk management in a Virtual Enterprise (VE). The private information between owner and partners is a gap, which hinders the optimal decision of risk management for the whole VE. This paper studies the impact of asymmetric information on decision results of risk management in the VE, and gives useful advices to improve the information situation between owner and partners. More specifically, Distributed Decision Making (DDM) theory and stochastic programming theory are employed to build a significant model to describe the decision process of risk management. A Two-Level Particle Swarm Optimization (TLPSO) is then designed to solve the resulting optimization problem. The result shows that the proposed algorithm is effective and the proposed model can help to improve the description of the information situation between the owner and the partners, which is helpful to reduce the risk of the VE.

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