Concepts Of Complexity Theory Research Articles

Understanding New Digital Media

How should we understand the new digital media and the effect of digital networks on global communication? Medium theory would be an obvious candidate, suggesting that we are in the middle of a transition from a society based on analogue media (print and electronic) to a society based on digital media. However, the present article suggests we examine another candidate: complexity theory. According to writers such as John Urry, we are in the middle of a paradigm turn, the so-called complexity turn. The aim of this article is to discuss whether complexity theory can be applied to media studies. What are the gains, and what would we lose? The author takes as his point of departure two case examples. The first is the case of the Mohammed cartoons in the Danish newspaper Jyllands- Posten. The second is the case of the Internet. How are we to understand the Internet as a qualitatively new medium? The author goes on to present two fundamental concepts of complexity theory. The first is the concept of complexity. The second is the concept of mediated communication, which appears to change significance in the context of complexity theory.

Complexity Theory and Strategic Change: an Empirically Informed Critique*

We present a four‐year ethnographic study of a public‐sector organization and use narrative to describe its development in terms of four complexity theory concepts: sensitivity to initial conditions, negative and positive feedback processes, disequilibrium and emergent order. Our study indicates that order emerges at the boundary between the organization's legitimate and shadow systems. We suggest that the underlying dynamic leading to the emergent order is the need to reduce anxiety. Our findings cause us to question the assertion that organizations are naturally complex adaptive systems producing novel forms of order. We propose an alternate view that in social systems, equilibrium‐seeking behaviour is the norm; such systems can self‐organize into hierarchy. We draw attention to some of the difficulties we found in applying complexity‐theory concepts to a social system and conclude by advocating the development of complexity theory through the incorporation of insights from psychology and social theory.

On the Relationship Between Organizational Complexity and Organizational Structuration

This article represents a contribution to the conceptualization of organizational complexity. The first part of the article relates the concept of complexity to the production tasks of the organization by deriving measures of the complexity of production and planning tasks within the organization. This move allows us to analyze organizational activities in terms of the computational complexity of the tasks that the organization carries out. Drawing on concepts from theoretical computer science, the article introduces a taxonomy of production tasks based on their computational complexity and shows how to use the notion of computational complexity to analyze organizational phenomena such as vertical integration disintegration, the choice between markets and organizations as performers of particular production tasks, and the internal partitioning of organizational tasks and activities. The article then relates the complexity of the production function of the organization to the ways in which organizations structure themselves. It attempts to bring theorizing about organizational behavior based on complexity theory closer to the conceptual realm of "mainstream" organization theory and to make the concepts of complexity theory more useful to empirical examinations of firm dynamics and organizational behavior.

Participation as chaos: Lessons from the principles of complexity theory for democracy

Current organizational communication theorists and practitioners seek to remedy organizational ills by advancing democracy within the workplace. Specifically, organizational democracy has been introduced with a variety of goals in mind: improving representation, increasing job satisfaction, improving productivity, and reducing costs. Although democracy emerges in myriad forms, theorists are still uncertain as to how to involve employees in the process and produce observable results. In this article, recent developments in complexity theory are invoked to both illuminate and resolve problems on the perspective of workplace democracy. The article closes by showing how complexity theory concepts can be used to encourage democratic practices in organizations. Ultimately, complexity theory is used to shed light on the processes surrounding the considerable problem solving and experimentation required to implement democratic practices.

“Customerized" innovation through the emergence of a mutually adaptive and learning environment

– This paper describes an experimental approach to model an innovation process on the basis of principles and concepts of complexity theory and its possible implications on the outcome of the innovation process. It is part of ongoing research carried out at the University of Nyenrode in the Netherlands, at the Nyenrode Institute of Virtual Education and Knowledge Management. In this paper the intricate and complex relation underlying the process of new product development and customer response, is the focus of attention. This relation is primarily defined as a process of knowledge management and mutual learning (Baets, 1998). In addition innovation is defined as a process of “manageable chaos” (adapted from Quinn, 1985). This means that innovation is conceptualized as a process of interaction and subsequent knowledge flows between people that are organized in a network and form a complex system. In the sixties Simon, one of the founders of complexity theory, defined a complex system as one made up of many parts that have many intricate interactions. An alternative will be brought forward to model innovation processes. Instead of defining innovation success in terms of organizational characteristics or factors linked to the success rate of a product innovation; the latter will be modeled as the outcome of interaction among a variety of agents that pursue strategies in a co-evolutionary process with each other. Classification Codes: M21.

Complexity theory: the changing role of leadership

The study of complex adaptive systems which explains the constant flux of living systems is arousing much interest as a paradigm and model for studying organisational behaviour and associated disciplines. A new order of reality emerges as a result of the constant interaction and coevolution of the elements of the system as well as their interaction with the system itself. The space of complexity is that state which the system occupies and which lies between order and chaos. One major impact on organisations in applying the concepts of complexity theory is the way in which leadership is seen and the need for change.

Complexity Theory and the Fifth Discipline

Complexity Theory is a relatively new area of research, which has been applied successfully in the chemical and biological sciences and is now beginning to find applications in the social sciences, especially in economics and organizational analysis. The paper sets out an understanding of Complexity Theory and its application to problems in the Management area and, in particular, relates current Complexity Theory thinking in Management with Senge's approach of the “Fifth Discipline.” It puts forward a set of principles for Complexity Theory in organization which form the basis for this comparison. After raising some concerns about the concept of self-organization, which is shown to be one of the key concepts in Complexity Theory, and the apparent lack of focus in Complexity Theory research to date with organizational politics and success criteria, the paper concludes by considering whether, at present, Complexity Theory can be considered to have deeper applications in addition to providing useful metaphors relevant to organizational analysis.

Machines Over the Reals and Non‐Uniformity

AbstractWe survey the research performed in the last few years on a specific topic: the power of real machines over binary inputs. This research attempts to characterize the classes of decision problems over a finite alphabet ‐ say {0,1} ‐ which can be decided by real machines working under several resource restrictions. Non‐uniformity appears here in a natural way. However, since this is a technical concept which is not widely known, we summarize in Section 2 some of the intuitive notions, as well as a few basic theorems related to it. In Section 3 we do this for the subject of real machines and then, in Section 4 we present the state of the art of the surveyed topic. We devote Section 1 to introduce the main concepts of complexity theory. Proofs in this article are quite sketchy and are included more to convey intuitive ideas than to completely prove the claimed statements. Bibliographical references to the original literature are supplied for the latter purpose.

Rudiments of complexity theory for scientists and engineers

Complexity theory is an important and growing area in computer science that has caught the imagination of many researchers in mathematics, physics and biology. In order to reach out to a large section of scientists and engineers, the paper introduces elementary concepts in complexity theory in a informal manner, motivating the reader with many examples.

Some complexity theory for cryptography

Abstract : This report concerns some of the elementary concepts in complexity theory. In particular, a mathematical model is developed for a finite-state machine and the Turing machine. This model has applications to public key cryptosystems, in determining which problems are P, NP, or NPC. The report was written to be as accessible to the nonspecialist as possible.

Complexity of some problems from the theory of automata

1.1. Given a finite alphabet L', the regular events over X are those accepted by a finite-state automaton. By Kleene's theorem, a subset W of S* is a regular event if and only if it can be constructed from the finiteword sets by boolean operations together with concatenation and *operation. In some sense, the regular events are quite simple because they are accepted by a machine with no storage capacity. Nevertheless, in recent years, much attention has been paid to special subclasses of the class of regular events; in this paper, we shall be concerned with star-free events, events of dot-depth one and piecewise testable events. Star-free events are constructed like regular events from the finite-word sets but with the restriction that the *-operation is not allowed; .events of dot-depth one and piecewise testable events are star free of a very simple form and will be defined below; star-free events have been characterized in the work of Schiitzenberger (1965) in terms of their syntactic monoid; algebraic characterizations of the other two classes have been given (Simon, 1975; Knast, 1983). From an algorithmic point of view, these algebraic characterizations do not yield efficient procedures because computing the syntactic monoid of a regular event given, e.g., by an automaton is obviously time consuming. In this paper, we investigate the complexity of three problems which we now describe in the style of (Garey and Johnson, 1979). We refer the reader to (Aho, Hopcroft, and Ullman, 1983; Garey and Johnson, 1979), for standard concepts of complexity theory.