Agent based decision support in the supply chain context

Purpose – The purpose of this paper is to investigate the benefits and the barriers of agent based decision support (ABDS) systems in the supply chain context. Design/methodology/approach – Two ABDS systems have been developed and evaluated. The first system concerns a manufacturing supply chain while the second concerns a service supply chain. The systems are based on actual case companies. Findings – This research shows that the benefits of ABDS systems in the supply chain context include the possibility to increase versatility of system architecture, to improve supply chain visibility, to conduct experiments and what-if analyses, to improve the understanding of the real system, and the possibility to improve communication within and between organizations in the supply chain. The barriers of ABDS systems in the supply chain context include the difficulty to access data from partners in the supply chain, the difficulty to access data on a higher level of granularity, and the difficulty to retrieve data from other information systems. Research limitations/implications – The research is explorative in nature therefore empirical data from similar and other research settings should be gathered to reinforce the validity of the findings. Practical implications – This research provides knowledge and insights on how ABDS systems may be developed and used in the supply chain context and demonstrates its main benefits and barriers. Originality/value – This research expands the current research of benefits of ABDS systems to the supply chain domain and also addresses the barriers of ABDS systems to a larger extent than previous research. Comparisons to other simulation based decision support systems are also given