Title :
Coevolutionary dynamics and agent-based models in organization science
Author :
Tivnan, Brian F.
Author_Institution :
Executive Leadership Doctoral Program, George Washington Univ., Ashburn, VA
Abstract :
This paper provides empirical and theoretical support for the application of coevolutionary dynamics and agent-based models in organization science. The support stems from the following logical progression: (a) organization science theorists have explored, and in many instances, acknowledged the applicability of complexity theory to organization science research; (b) much of the acceptance for complexity science applications follows from the conceptualization of an organization as a complex adaptive system (CAS); (c) complexity science offers a robust explanation of order in natural and social systems; (d) revolutionary dynamics provide the mechanisms with the highest explanatory power for describing order-creation in social systems. This paper provides an overview of the literature for each element of the preceding logical progression and concludes with a discussion of the applications of agent-based models to instantiate coevolutionary dynamics
Keywords :
adaptive systems; computational complexity; multi-agent systems; social sciences computing; agent-based models; coevolutionary dynamics; complex adaptive system; complexity theory; natural systems; organization science; revolutionary dynamics; social systems; Adaptive systems; Aggregates; Biological system modeling; Chemical elements; Complexity theory; Content addressable storage; Mechanical factors; Nonlinear dynamical systems; Robustness; Tagging;
Conference_Titel :
Simulation Conference, 2005 Proceedings of the Winter
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-9519-0
DOI :
10.1109/WSC.2005.1574353