A trust model for supply chain management

Many real-world applications, such as Supply Chain Management (SCM), can be modeled using multi-agent systems. One shortcoming of current SCM models is that their trust models are ad hoc and do not have a strong theoretical basis. We propose a trust model for SCM that is grounded in probabilistic game theory. In this model, trust can be gained through direct interactions, and/or by asking for information from other trustworthy agents. We will use this model to simulate and study supply chain market behavior. Supply chain networks have often been modeled in the research literature with multi-agent systems in which the agents need to collaborate with one or more partners. This collaboration becomes more effective when agents have the ability to choose their partners based on the trustworthiness of the candidates. Trust is defined as the belief an agent has that the other party will fulfill its promises, given the possibility that the partner may defect to get higher benefits (Dasgupta 1998). A major shortcoming in previous research on trust in Supply Chain Management is that their trust-based decision making is not grounded in a formal trust model. In this work, we propose a trust model for SCMs that incorporates trust factors specific to SCM, represented in probabilistic and utility-based terms. Our model also takes into account the effects of variable payoffs. We will investigate how market behavior is affected by different trust factors. We will identify optimal strategies for different situations; i.e., those strategies that result in the best performance and overall returns. This abstract describes our initial framework, which we are currently implementing.