Jeffrey Barker

Real-time business intelligence in multi-agent adaptive supply networks

The increasing speed and complexity of inter-organisational communication in supply networks requires effective automation. Multi-agent systems have been proposed as a possible solution. However, the information needs of the agent, particularly in responding to any variation from the norm, are similar to a human in the same position. This paper reviews the concepts of business intelligence (BI) and real-time enterprises (RTE) and looks at the need for BI in dynamic information management. A multi-agent framework is described and case-based reasoning investigated as a reasoning paradigm capable of responding to the need for business intelligence. A CBR approach is proposed with key performance indicators defining the case problem and BI operations the case solution.

The Next Generation Demand Network in Quick Response Systems: Intelligent Products, Packet Switching and Dynamic Information

This chapter discusses several innovations in information and communication technology and develops their potential to radically alter our view of the supply chain in quick response applications. Using the packet-switching framework as an analogy, it explores the way in which intelligent products may operate to dynamically adjust to market volatility. The changes will require new thinking in areas such as supply chain optimization and the handling of services in the supply chain or demand network. The main contribution here is to extend the research framework for dynamic information management for quick response networks.

Viewing demand networks with intelligent products as digital business ecosystems

The business digital ecosystem is based on autonomous proactive agents that act for their own advantage. This paper uses the ecosystem paradigm to develop a novel view of the behaviour of a demand network using a packet switching model of intelligent products. Products may have local intelligence and allocation of products to nodes in the demand network is based on optimal return for all parties using dynamic information.