An organization is more than the sum of its parts, and the individual components that function as a complex social system can be understood only by analyzing their collective behavior. This book shows how state-of-the-art simulation methods, including genetic algorithms, neural networks, and cellular automata, can be brought to bear on central problems of organizational theory related to the emergence, permanence, and dissolution of hierarchical macrostructures. The emphasis is on the application of a new generation of equation- and agent-based computational models that can help students of organizations to reformulate their basic research questions starting from assumptions about how to link-rather than separate-different levels of organizational analysis.

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