6.4 Simulation

Simulations portray some aspect of a real-world system that can be used to study its behavior. This section introduces simulation and several simulation methods useful in forecasting and technology management. The first method discussed is cross-impact analysis, which is useful for understanding the forces surrounding an evolving technology. It can also serve as a vehicle for launching discussions about the impacts of the technology. Next, Monte Carlo simulation is presented and applied to economic decision making. RFID is used as an example of both cross-impact and Monte Carlo analyses. System dynamics methods also are described as a philosophy for analyzing and understanding complex real-world systems. Lastly, gaming is introduced as a means to study the behavior of decision makers in pursuit of goals or in competition with each other.

Simulation means different things to different people. To an airline pilot, for instance, it means physical emulation of the cockpit and analog or digital emulation of aircraft flight behavior. Operations researchers, however, generally think of simulation in terms of discrete-event computer models that imitate the system they wish to study. Once such models have been verified and validated, they can be used to study the effect of changes in the real system. A military analyst may see simulations as war games with stochastic behavior and may use them to study strategy and tactics, the effects of new weapon systems, or other battlefield ...

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