Linking autonomous agents to CPFR to improve SCM

Purpose - The standpoint of this research lies in the study of the CPFR process for trading partners (belonging to the same supply chain) who are willing to collaborate in exchanging sales and order forecast. This points out the need for providing a collaboration process with an intelligent tool to optimise negotiation. Design/methodology/approach - A literature review and classification has been carried out concerning autonomous agents used to manage supply chain processes. To evaluate the strengths coming from an intelligent system embedded within the CPFR process, several experiments in different conditions were conducted using simulation tool. Findings - The analysis of experimental results points out that the agent-driven negotiation process (by comparison to CPFR without intelligent agents) benefits in terms of costs, inventory level, stock-out level and sales. Research limitations/implications - The study represents a one-to-one scenario, in which only two trading partners collaborate. Further, research has been identified to extend the work. Practical implications - The study represents a first step towards the analysis of a multi-agent system being used to automate and optimise collaboration along a supply chain. Originality/value - The study represents a novel approach to resolving exceptions concerning sales and forecast data.