Abstract: Due to the turbulence of these times and to the embeddedness of an interdependent, global economy, many organizations attempt to enhance their competitive advantage by actively exploring their external environment. Building on earlier research to explore organization-environment interaction via boundary-spanning activity, this study investigates such interactions via tests of analytical adequacy to observe the emergence of the adaptive tension between exploration and exploitation of organizations in a coevolutionary context. After replicating March’s (1991) seminal research, this study extends the March model to investigate a coevolutionary, competitive context. Results from computational experiments confirmed the analytical adequacy of the extensions to the original March model. Future research should address further investigation of the extended model’s analytical adequacy and ontological adequacy. In so doing, this study provides support for a model-centered organization science and the application of complexity theory to organization science research.* In addition to the personal acknowledgments below, I am grateful for discussions of a technical nature with the following: Robert Axtell, Michael Cohen, Stephen Guerin, Matthew Koehler, James March, John Miller, Melanie Mitchell, Michael Prietula and Stephen Upton. I would also like to thank participants at the 3rd Lake Arrowhead Conference on Human Complex Systems, the 2006 Organization Science Winter Conference, and the 2006 Santa Fe Institute Complex Systems Summer School where many aspects of this research were developed and presented.
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Bongard's work focuses on understanding the general nature of cognition, regardless of whether it is found in humans, animals or robots. This unique approach focuses on the role that morphology and evolution plays in cognition. Addressing these questions has taken him into the fields of biology, psychology, engineering and computer science.
Danforth is an applied mathematician interested in modeling a variety of physical, biological, and social phenomenon. He has applied principles of chaos theory to improve weather forecasts as a member of the Mathematics and Climate Research Network, and developed a real-time remote sensor of global happiness using messages from Twitter: the Hedonometer. Danforth co-runs the Computational Story Lab with Peter Dodds, and helps run UVM's reading group on complexity.
Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.
Hines' work broadly focuses on finding ways to make electric energy more reliable, more affordable, with less environmental impact. Particular topics of interest include understanding the mechanisms by which small problems in the power grid become large blackouts, identifying and mitigating the stresses caused by large amounts of electric vehicle charging, and quantifying the impact of high penetrations of wind/solar on electricity systems.
Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).