Abstract
Agent-based modeling is gaining popularity for investigating the behavior of
complex systems involving interactions of many players or agents. In this paper an agent-based
simulation modeling technique is applied to understand the long term implications of strategy
decisions for an aerospace value chain. The industry has unique elements including new
business models, high levels of collaboration, long product lifecycles and long periods before
positive paybacks are realized. Forecasting market conditions over this long term lifespan is
inherently problematic and adds further complexity when devising a strategy. The model
described includes all the major players and entities in the value chain and their interactions.
Illustrative results are presented to demonstrate how the simulation approach can be used to
evaluate strategy and policy decisions and their operational implications over the long term.
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