Modern multiagent technology can be applied fruitfully to supply chain or to be more precise to demand chain management. In current research there is not much discussed in this direction because today’s business processes are often characterized more by small solutions than by integrated ones. This paper will prove that this approach offers very new and challenging possibilities to manage deman...

V. Agrawal and S. Seshadri (2000) [Risk intermediation in supply chains. IIE Transactions, 32, 819–831] considered a problem in which 7 a single risk neutral distributor supplies a short-lifecycle, long-leadtime product to several retailers that are identical except in their attitudes towards risk. They proved that the distributor should not offer the same terms to every retailer but instead of...

This article develops a dynamic game model of a supply chain consisting of one manufacturer and one retailer to study the coordination mechanism and the effect of demand disruption on the coordination mechanism, where the market demand is sensitive to retail price and service. We assume that the supplier and the retailer only know the distribution of the disrupted amount after the demand disrup...

Supply chain demand prediction plays a very important role for enterprises to realize sales and markets management target effectively, especially for fresh agricultural product enterprises. A new model for supply chain demand prediction for fresh agricultural product enterprises is presented based on improved BP neural network. First the advantages and disadvantages of BP neural network algorit...

Though often analyzed separately, supply chain instability and customer demand interact through product availability. We investigate the feedback between supply chain performance and demand variability in a model grounded in a first-hand study of the hybrid push–pull production system used by a major semiconductor manufacturer. While customers’ response to variable service levels represents an ...