Page 253 -

11 How Many Times Should One Run a Computational Simulation? 251

Secchi, D., & Gullekson, N. (2016). Individual and organizational conditions for the emergence
and evolution of bandwagons. Computational and Mathematical Organization Theory, 22(1),
88–133.
Secchi, D., & Seri, R. (2014). ‘How many times should my simulation run?’ Power analysis for
agent-based modeling. In European Academy of Management Annual Conference, Valencia,
Spain.
Secchi, D., & Seri, R. (2017). Controlling for ‘false negatives’ in agent-based models: A review
of power analysis in organizational research. Computational and Mathematical Organization
Theory, 23(1), 94–121.
Shimazoe, J., & Burton, R. M. (2013). Justification shift and uncertainty: Why are low-probability
near misses underrated against organizational routines? Computational and Mathematical
Organization Theory, 19(1), 78–100.
Simon, H. A. (1976). How complex are complex systems. In PSA: Proceedings of the Biennial
Meeting of the Philosophy of Science Association (Vol. 2, pp. 507–522). Baltimore: Philosophy
of Science Association.
Simon, H. A. (1978). Rationality as process and a product of thought. American Economic Review,
68, 1–14.
Simon, H. A. (1997). Administrative behavior (4th ed.). New York: The Free Press.
Thiele, J., Kurth, W., & Grimm, V. (2015). Facilitating parameter estimation and sensitivity
analysis of agent-based models: A cookbook using NetLogo and R. Journal of Artificial
Societies and Social Simulation, 17(3), 11.
Thomsen, S. E. (2016). How docility impacts team efficiency. An agent-based modeling approach.
In D. Secchi & M. Neumann (Eds.), Agent-based simulation of organizational behavior. New
frontiers of social science research (pp. 159–173). New York: Springer.
Troitzsch, K. G. (2017). Historical introduction. doi:https://doi.org/10.1007/978-3-319-66948-
9_2.
van der Vaart, A. W. (2000). Asymptotic statistics. Cambridge: Cambridge University Press.
Wasserstein, R. L., & Lazar, N. A. (2016). The ASA’s statement on p-values: Context, process, and
purpose. American Statistician, 70(2), 129–133.
Wilensky, U. (1999). Netlogo. Center for Connected Learning and Computer-Based Modeling,
Northwestern University, Evanston, IL.