Through the Looking Glass of Complexity: The Dynamics of Organizations as Adaptive and Evolving Systems

Benoit Morel and Rangaraj Ramanujam
Additional contact information
Benoit Morel: Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
Rangaraj Ramanujam: Graduate School of Industrial Administration, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213

Organization Science, 1999, vol. 10, issue 3, 278-293

Abstract: This paper examines how organization theory can benefit from advances made in the interdisciplinary field of complex systems theory (CST). Complex systems theory is not so much a single theory as a perspective for conceptualizing and modeling dynamic systems. The field of complexity is described in terms of the characteristics of systems that are typically the subject of its study, the type of analytical tools used by researchers in this field, and the recurring paradigms that characterize this research perspective. The concepts of self-organized criticality and self-organization and their relevance to organizational studies are examined. The potential usefulness of these concepts is illustrated in the context of organizational evolution and social network analysis. An alternative model of organizational evolution, based on biological evolution, is proposed and propositions are developed. Unlike traditional models for organization, this model does not rely on an algorithm of optimization of a fitness function. The problem of self-organization is approached from the viewpoint of random graph theory and is applied to the analysis of social networks. Finally, important issues in using concepts from the field of CST are discussed. It is suggested that the immediate benefits of CST may be as a framework that facilitates conceptual elaborations and encourages formal modeling; both activities may provide fresh and deep insights into organizational phenomena.

Keywords: complex systems theory; computer simulations; organizational evolution; organizational adaptation; social network analysis (search for similar items in EconPapers)
Date: 1999
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (41)

Downloads: (external link)
http://dx.doi.org/10.1287/orsc.10.3.278 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ororsc:v:10:y:1999:i:3:p:278-293

Access Statistics for this article

More articles in Organization Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().