Complex systems theory (e.g. Bar-Yam, 1997) is a rich and vital research area that has a huge potential for organizational research (Lewin, 1999). In particular, the study of complex adaptive systems (CASs) provides many insightful results concerning the adaptability and strategic management of organizations in turbulent environments (ibid). In the following, I will take this characterization of CASs as a starting point for exploring possible connections between CAS and ADT. This is done against the background of the previously reported complexity inherent in both telecom systems and projects developing these systems.
TopComplex Systems Theory And Adt
Complex systems theory (e.g. Bar-Yam, 1997) is a rich and vital research area that has a huge potential for organizational research (Lewin, 1999). In particular, the study of complex adaptive systems (CASs) provides many insightful results concerning the adaptability and strategic management of organizations in turbulent environments (ibid).
There is no clear definition of complexity that is generally accepted (see e.g. Morel & Ramanujam, 1999). However, some characteristics can be identified. Complex systems are self-organizational; order emerges naturally in open systems that exchange resources with its environment (Lewin, 1999). They consist of interconnected parts that are often complex systems themselves. The behavior of complex systems is an emergent property “contained in the behavior of the parts if they are studied in the context in which they are found” (Bar-Yam, 1997, p. 10). A complex organization consists of “a set of interdependent parts, which together make up a whole that is interdependent with some larger environment” (Anderson, 1999, p. 216). More specifically, complexity in organizations has been defined with respect to the number of levels in the organizational hierarchy, the number of departments in the organization, and the number of geographical locations (ibid, p. 216).
CASs are special cases of complex systems. A general definition is given by COSI (2009): “Macroscopic collections of simple (and typically nonlinearly) interacting units that are endowed with the ability to evolve and adapt to a changing environment.” In the literature, the following characteristics of CASs can be identified:
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Agents with schemata: A CAS is a “dynamic network of many agents (which may represent cells, species, individuals, firms, nations) acting in parallel, constantly acting and reacting to what the other agents are doing” (Wikipedia, 2009c).
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Self-organizing networks sustained by importing energy: Agents are “partially connected to one another, so that the behavior of a particular agent depends on the behavior (or state) of some subset of all the agents in the system […].Maintaining a self-organized state requires importing energy into the system” (Anderson, 1999, p. 219-220).
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Coevolution to the edge of chaos: Agents coevolve with one another. Each agent adapts to its environment by striving to increase a payoff or fitness function over time. The equilibrium that results from such coevolution lies at the edge of chaos (ibid, p. 220).
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System evolution based on recombination: CASs “evolve over time […]. New agents may be formed by recombining elements of previously successful agents. Furthermore, the linkages between agents may evolve over time […]. CASs can contain other complex adaptive systems, as, for example, organisms have immune systems” (ibid, p. 220).
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Self-similarity: Self-similarity indicates that a CAS system is invariant under a change of scale (Morel & Ramanujam, 1999). Self-similarity is closely related to fractals, where the structure of a system on a coarse scale is repeated on finer scales.
In the following, I will take this characterization of CASs as a starting point for exploring possible connections between CAS and ADT. This is done against the background of the previously reported complexity inherent in both telecom systems and projects developing these systems.