Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
Knowledge Assets: Securing Competetive Advantage in the Information Economy
Knowledge Assets: Securing Competetive Advantage in the Information Economy
Environments and Languages to Support Social Simulation
Social Science Microsimulation [Dagstuhl Seminar, May, 1995]
Simulation for the Social Scientist
Simulation for the Social Scientist
Experiences creating three implementations of the repast agent modeling toolkit
ACM Transactions on Modeling and Computer Simulation (TOMACS)
How Much to Copy? Determinants of Effective Imitation Breadth
Organization Science
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The paper proposes a novel research architecture for social scientists that want to employ simulation methods. The new framework gives an integrated view of a research process that involves simulation modelling. It highlights the importance of the theoretical foundation of a simulation model and shows with the help of the non-statement view and its structuralist theory reconstruction how new theory-driven propositions and hypotheses can be derived from simulations that are empirically testable. It also illustrates the role of theory-based simulation environments. The paper describes the different aspects of the framework in detail and shows how it can help structure the research efforts of scholars interested in using simulation.