Abstract
In the last decade a new generation of information systems (ISs), such as Web-based information systems and knowledge management support systems, have emerged in response to ever-changing organizational needs. Therefore, the need for new “Information System Design Theories” for the emerging ISs is recognized. According to Walls, Widmeyer, and El-Sawy (1992), an “IS design theory” must have two aspects?one dealing with the description of the system and one dealing with the prescription, that is, the process of developing of the system. The prescription aspect includes a description of procedures and guidelines for system development. In addition, these two aspects must be grounded on theories from natural or social sciences (i.e., kernel theories). As information systems are socio-technical phenomena in which social and technical factors interweave the ways in which people work, the issue of “how to integrate the work activity and social context of users into the IS which is being designed” becomes one of the principal problems of IS development (Bai & Lindberg, 1999). Therefore, the development of new IS design theories requires a closer look at the system theories that go beyond the traditional system theory that is based, among other things, on Cartesian dualism (i.e., mind/body or cognition/action) and on a model of cognition as the processing of representational information (Mingers, 2001). One of the candidate theories is the theory of autopoiesis, which can be best viewed as a system-grounded way of thinking with biological foundations, together with its extension into social domain.
TopBackground
In order to conceive of living systems in terms of the processes that realized them, rather than in terms of their relationships with an environment, Maturana and Varela (1980) coined the word autopoiesis (αυτοσ = self, ποιενιν = creation, production) to denote the central feature of their organization, which is “autonomy.” The meaning of this word coveys the very nature of living systems as systems that maintain their identity through their own operations of continuous self-renewal. Moreover, these systems could only be characterized with reference to themselves and whatever takes place in them, takes place as necessarily and constitutively determined in relation to themselves—that is, self-referentiality.
One of the key concepts of autopoiesis is the distinction between organization and structure. On one hand, organization is the capability of a system to reproduce its identity by referring constantly to itself, through the alternate reproduction of its components together with the component-producing processes, that is, the capability of a recursive self-reproduction. On the other hand, structure is the realization of a system’s organization through the presence and interplay of its components in a specific realization space. While organization is necessary to establish system unity and identity, structure is necessary because different spaces of its actualization impose different constraints on a system’s components (Maturana & Varela, 1980). By rough analogy, an algorithm for solving certain problem can be viewed as a description of the system’s organization, whereas the corresponding computer program can be viewed as the realization of this organization (structure) in a certain space (programming language).
Key Terms in this Chapter
Organization: The configuration of relationships among a system’s components that define a system as a unity with distinctive identity, and determine the dynamics of interaction and transformations that it may undergo as such a unity.
Cognitive Domain: The domain of all the interactions in which one can enter without loss of identity ( Maturana & Varela, 1980 , p. 119).
Structure: The physical embodiment of system’s organization in a certain physical domain.
Consensual Domain: “The domain of interlocked conducts that results from ontogenetic structural coupling between structurally plastic organisms” ( Mingers, 1995b ).
Strong vs. Weak Methods: “Strong methods are those designed to address a specific type of problem, while weak methods are general approaches that may be applied to many types of problems” ( Vessey & Glass, 1998 ).