Network Agents to Support Information Sharing for Buyer- Buyer-Supplier Coordination

Finding most promising suppliers based on consistency with the overall goals of buyers’ companies is of great importance where different small buyers are dependent on large suppliers. Here, the authors attempt to model and implement an e-supply network considering the buyer-buyer-supplier triadic. This approach facilitates horizontal information exchange among buyers in sharing their experience and thereby buyers are inclined to find the most acceptable suppliers. Indeed, vertical information sharing among buyers and suppliers are considered in order to allocate the benefits of the mechanism to all partners while optimizing the network global objective function. The concept of discrepancy is first utilized to search for the most promising suppliers in the network based on the overall goals (exclusive attributes) of buyers and suppliers. Then, products’ specific attributes (bilateral attributes) are used to sharpen the results. At the last step, a genetic algorithm is used by the network agent to coordinate the network. Ultimately, the authors utilize intelligent agents to simulate buyers’ and suppliers’ behaviors with the aim of evaluating the system. They find out that information sharing in supply networks can be effectively established if the barriers of information access and information effects are wisely defined.