Complex Adaptive Systems
Introduction
Complex Adaptive Systems in Business, Special issue of International Journal of Business and Systems Research Special, Edited by Rosanna Garcia; Deadline 10 May 2010
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International Journal of Business and Systems Research Special Issue on “Complex Adaptive Systems in Business”. Guest Editor is Dr. Rosanna Garcia, Northeastern University, Boston, MA. The topic of this special issue is:
Complex adaptive systems (CAS) have been defined as systems that involve the interactions of numerous individual agents or elements that change and learn from experience and can show emergent and adaptive properties not exhibited by the individual agents. Organizational management studies have embraced the study of CAS as a means of explaining how firms adapt, learn, and evolve (Organization Science May/June 1999; Management Science, July 2007). Although organization scientists have studied complex organizations for many years, a developing set of conceptual and computational tools makes possible new approaches to modeling nonlinear interactions within and between organizations. Network dynamics, socio-economics, agent-based computational economics, and other multi-agent modeling approaches have allowed management researchers to expand into unexplored areas in business applications.
We welcome interdisciplinary discourses that serve to enhance our understanding of the business environments, recognizing that the marketplace in which organizations operate are living dynamic systems that is not always predictable. Studies using system dynamics modeling, agent-based modeling or other dynamic methodologies are encouraged. Preference will be given to high quality papers that have a firm grounding in scientific and mathematical methods, instead of primarily application-based papers. Because a substantial gap continues to exist between theory and practice, theoretical papers that also include a real-world application are very useful. Of additional interest are papers developing benchmarks and metrics that will provide guidance for future research.
The full paper deadline is May 10, 2010. Details for submission are at
or by contacting r.garcia@neu.edu.