Enterprises continuously seek decision support tools that can help automate and codify business decisions. This is particularly true in the business of consumer electronics manufacturing where components are often interchangeable and several manufacturers can supply the same component over the life of a product. In this kind of dynamic environment, businesses are faced with the choice of signing long-term (possibly quite risky) contracts or of waiting to procure necessary components on the spot market (where availability may be uncertain). Having analytical tools to analyze previous and forecast future market conditions is invaluable. We analyze a supply chain scenario from an economic perspective that involves both component procurement and sales uncertainties. The data we analyze comes from a multi-agent supply chain management simulation environment (TAC SCM) which simulates a one-year product life-cycle. The availability of simulation logs allows us access to a rich set of data which includes the requests and actions taken by all participants in the market. This rich informational access enables us to calculate supply and demand curves, examine market efficiency, and see how specific strategic behaviors of the competing agents are reflected in market dynamics.

agent-mediated electronic commerce, decision support, economic simulation, market forecasting, supply chain management
dx.doi.org/10.1007/978-3-642-17449-0_5, hdl.handle.net/1765/31589
Lecture Notes in Business Information Processing (LNBIP)
Erasmus School of Economics

Groves, W, Collins, J, Ketter, W, & Gini, M. (2010). Analyzing market interactions in a multi-agent supply chain environment. In Lecture Notes in Business Information Processing (LNBIP) (Vol. 52, pp. 44–58). doi:10.1007/978-3-642-17449-0_5