Coordination plays a pivotal role in successful design and implementation of supply chains, especially for those that are formed by independent and autonomous companies. More specifically, information sharing has widely been regarded as an essential tool to coordinate supply chains activities in order to overcome supply chains dynamics. A major contribution of this paper is to analyse the effects of negotiation-based information sharing in a distributed make-to-order manufacturing supply chain in a multi-period, multi-product types environment, which is modelled as a multi-agent system. Information can only be exchanged through negotiation in the agent-based framework with delivery quantity and due date flexibility, which is significantly different from the past reported literature that shared information is available anytime. Four schemes, namely, stochastic model (STO), flexibility in delivery quantity and due date without information sharing (FLEX_NI), flexibility in delivery quantity and due date with partial information sharing (FLEX_PI), and flexibility in delivery quantity and due date with full information sharing (FLEX_FI), are considered. Simulation results indicate that FLEX_PI in the system has comparable performance in terms of total cost and fill rate against FLEX_FI, while both systems outperform STO and FLEX_NI. Considering the associated costs and limitations to achieve full information sharing, partial information sharing may be more practical in real-life applications. Nevertheless, the proposed agent-based framework with delivery quantity and due date flexibility but without information sharing (i.e. FLEX_NI) is not that worse as compared with the two schemes of information sharing (FLEX_PI and FLEX_FI). Therefore, by taking the difficulties of implementing information sharing into account, flexibility in delivery quantity and due date that could be introduced may be a more feasible solution.
- Information sharing
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Management Science and Operations Research
- Strategy and Management