Moreover, the rules that govern the interaction of agents within the system are totally transparent and open to public scrutiny and debate. Simulations are also capable of producing large amounts of data to drive even the greediest statistical model. Unlike researchers in the real world, simulation researchers are not limited to one version of events. Critics of quantitative methods have criticised their ability to capture change, complexity and uniqueness. By allowing a computer to trace the evolution of a model over time, almost all simulation models are dynamic by design.
Simulations are therefore ideal environments in which to study change, flux and evolution.
Finally, agent-based simulations provide a breakthrough in modelling uniqueness. In agent-based systems, aggregate data emerges from the interplay of individual agents. The scarcity and inadequacy of data sources in strategic management has been identified as an important problem confronting researchers in the discipline. It is the unexplored potential of agent-based simulations to alleviate data scarcity, by combining the rigour of quantitative approaches with the complexity and uniqueness of qualitative approaches, that provides the rationale for this study. In turn, creating a new data source allows us to test theories that have previously been considered untestable due to the cost or difficulty of acquiring reliable volumes of data.