Allwood, JM and Lee, J-H (2005) The design of an agent for modelling supply chain network dynamics. International Journal of Production Research, 43. pp. 4875-4898. ISSN 0020-7543Full text not available from this repository.
A useful insight into managerial decision making can be found from simulation of business systems, but existing work on simulation of supply chain behaviour has largely considered non-competitive chains. Where competitive agents have been examined, they have generally had a simple structure and been used for fundamental examination of stability and equilibria rather than providing practical guidance to managers. In this paper, a new agent for the study of competitive supply chain network dynamics is proposed. The novel features of the agent include the ability to select between competing vendors, distribute orders preferentially among many customers, manage production and inventory, and determine price based on competitive behaviour. The structure of the agent is related to existing business models and sufficient details are provided to allow implementation. The agent is tested to demonstrate that it recreates the main results of the existing modelling and management literature on supply chain dynamics. A brief exploration of competitive dynamics is given to confirm that the proposed agent can respond to competition. The results demonstrate that overall profitability for a supply chain network is maximised when businesses operate collectively. It is possible for an individual business to achieve higher profits by adopting a more competitive stance, but the consequence of this is that the overall profitability of the network is reduced. The agent will be of use for a broad range of studies on the long-run effect of management decisions on their network of suppliers and customers.
|Uncontrolled Keywords:||Multi-agent Simulation Supply chain dynamics Supply chain network|
|Divisions:||Div D > Structures|
|Depositing User:||Cron Job|
|Date Deposited:||07 Mar 2014 11:25|
|Last Modified:||27 Jan 2015 19:00|