Showing papers in "Emergence in 2001"
TL;DR: The need for a special issue of Emergence on the question “What is complexity science?” is disturbing on several levels as mentioned in this paper, and the inability to clearly differentiate science from pseudoscience in complexity studies is also problematic.
Abstract: The need for a special issue of Emergence on the question “What is complexity science?” is disturbing on several levels. At one level, one could be forgiven for thinking that the voluminous literature generated in recent years on chaos and complexity theory must contain a clear exposition on the definition, mission, and scope of complexity science. That this exposition has not been forthcoming, or is the subject of controversy, is disconcerting. On another level, the inability to clearly differentiate science from pseudoscience in complexity studies is also problematic. Allowing pseudo-science to penetrate a field of study lowers the credibility of that field with mainstream scientists and hinders the flow of resources for future development.
124 citations
TL;DR: A provisional epistemology will be developed that attempts to remain faithful to the limitations derived from this aspect of complexity science, and has some affinity to sceptical postmodernism.
Abstract: This paper explores the implications of the incompressibility of complex systems for the analysis and modelling of such systems. In particular, a provisional epistemology will be developed that attempts to remain faithful to the limitations derived from this aspect of complexity science. We will argue that such an investigation of complex systems highlights the relevance of paradigmatic pluralism or eclecticism, analytical creativity and boundary critique, and therefore has some affinity to sceptical postmodernism. Complexity science, like postmodernism, provides a clear warning as to the dangers of uncritically adopting any 'black and white' theoretical position. It encourages the deferral of paradigm selection and a healthy scepticism.
83 citations
TL;DR: In this paper, the limits to knowledge emergence are discussed. But complexity science is not the same as complexity science, and complexity science does not necessarily imply knowledge emergence, either.
Abstract: (2001) What Is Complexity Science? Knowledge of the Limits to Knowledge Emergence: Vol 3, No 1, pp 24-42
75 citations
TL;DR: The paper concludes by outlining essential problematics of order-creation science by outlining the basic causal processes underlying emergent order that have been ignored in most managerial and organizational applications of complexity science.
Abstract: (2001). What Is Complexity Science? It Is Really Order-Creation Science. Emergence: Vol. 3, No. 1, pp. 137-157.
65 citations
58 citations
TL;DR: Emergence must not become yet another excuse for idealism and the assumption that the idea behind appearances is the truth; or for empiricism and the claim that the world outside of consciousness is true while subjectivity is false.
Abstract: (2001). Phenomenal Complexity Theory and the Politics of Organization. Emergence: Vol. 3, No. 4, pp. 5-31.
51 citations
40 citations
TL;DR: Self-Organizing Leadership: A Way of Seeing What Is Happening in Organizations and a Pathway to Coherence (Part II) Emergence: Vol 4, No. 4, pp. 86-97 as mentioned in this paper.
Abstract: (2002). Self-Organizing Leadership: A Way of Seeing What Is Happening in Organizations and a Pathway to Coherence (Part II) Emergence: Vol. 4, No. 4, pp. 86-97.
33 citations
TL;DR: In the field of science, boundary recognition is regarded as a straightforward exercise as discussed by the authors, and it is easy to understand how some scientists can wholeheartedly buy into their models as true representations of what is.
Abstract: Contemporary science with its strong positivism tends to trivialize the nature of boundaries. Boundaries are supposedly real and our ability to recognize them as such is regarded as a straightforward exercise. This by-product is a direct result of science’s focus on the quantifiable and mathematizable (Goodwin, 2000). Given such a naïve belief in the (ontological) status of boundaries, it is easy to understand how some scientists can wholeheartedly buy into their models as true representations of what is. If absolute boundaries exist, then as scientists we have simply to map them and with a little mathematical manipulation “hey presto!”—we have true knowledge of the universe. Scientists aren’t the only ones who approach nature in such a black-and-white manner, however. We are all frequently guilty of unquestioningly accepting the efficacy of certain physical and conceptual boundaries that may be totally inappropriate for the context of interest. Managers cling on to organizational models that have far outlived their use and relevance; politicians dogmatically cling to ideologies that should have been put to rest many decades ago; employees at every level of organization naïvely assume that their view of the world is the “right” one. Decision makers often think that failure more often than not results from the bad implementation of their decisions. It is both interesting and
33 citations
32 citations
TL;DR: In this article, what is complexity science? Postmodernist or psotpositivist? Emergence: Vol. 3, No. 1, pp. 104-119.
Abstract: (2001). What Is Complexity Science? Postmodernist or Psotpositivist? Emergence: Vol. 3, No. 1, pp. 104-119.
TL;DR: In this article, the authors make a distinction between the study of complex social orders and complex social orderings, and argue there continues to be a problem of establishing the grounds upon which complexity science can be seen to offer an adequate account of social dynamics, in particular because of a continued tendency towards determinism and reductionism.
Abstract: I argue that the question �what is complexity science?� presents an opportunity to think critically about complexity science, and to ask the question tells us something about what work still needs to be done in understanding complex social dynamics. The paper is a performance of complexity science, putting complexity science to the ultimate test asking, how can complexity science help us answer the question �what is complexity science�? Making a distinction between the study of complex social orders and complex social orderings, I argue there continues to be a problem of establishing the grounds upon which complexity science can be seen to offer an adequate account of social dynamics, in particular because of a continued tendency towards determinism and reductionism. I suggest that the concept of emergence needs to be re-thought, and, drawing upon Luhmann, that a key role for complexity science is to ask, how is ignorance dealt with?
TL;DR: This book is the latest shot in an ongoing dispute between the hard physical sciences and the “soft” social sciences such as sociology, anthropology, and other observation-based studies of human affairs.
Abstract: (2001). When Modeling Social Systems, Models ≠ the Modeled: Reacting to Wolfram's A New Kind of Science. Emergence: Vol. 3, No. 4, pp. 95-111.
TL;DR: In this article, the authors propose that mergers and other structural changes are a rational response to market pressures, under the assumptions of the currently dominant, mechanistic business model of health care.
Abstract: Structural changes are commonplace in modern health care systems. Mergers, alliances, networks and other forms of structural change are being undertaken to reduce costs, improve utilization and service breadth, and reduce variation in demand. While some of these changes have provided benefits to both the health care provider and consumers, many have failed to reach their full potential, or worse. In this paper we propose that mergers and other structural changes are a rational response to market pressures, under the assumptions of the currently dominant, mechanistic business model of health care. Most mergers are primarily aimed at exploiting existing knowledge and capability. Synergy is thought of only as a deterministic phenomenon, something that can be created and managed. We next present a biologically based model using complexity science that illustrates the broader, explorative role that mergers based on the principles of selforganization could have. First, these self-organizing mergers—we call them emergers— could focus on much broader objectives than merely reducing costs. Second, emergers could be used to innovate radically different configurations of our health care system. Building on the first two roles, we see a third role that challenges the fundamental assumptions of what health care is, what it could be and how it could be delivered.
TL;DR: In this article, the authors explore and present a way of connecting complexity and community through the framework of the Integral Model, which is further informed by the Spiral Dynamics (Beck and Cowan).
Abstract: Does complexity science help us understand community? Does the study of community help us better grasp complexity? The purpose of this paper is to explore these questions. Each of these two domains of complexity and community has an extensive literature addressing different definitions and different theories. The authors review a representative selection of each domain’s literature, in order to acknowledge the roots of their emergent inquiry. In some cases the authors have connected the two domains and emerged new understandings because of this cross informing process. Subsequently, the authors explore and present a way of connecting complexity and community through the framework of the ‘Integral Model’ (Ken Wilber), which is further informed by ‘Spiral Dynamics’ (Beck and Cowan). Finally, the authors pose further questions concerning the relationship between complexity and community and invite others to join in this exploration.
TL;DR: In this paper, the authors have recognized that the environment plays a significant but not absolute role in the origin and evolution of organizations and that an organization can only exist if it exchanges individuals, information, or material resources with the environment permanently surrounding it.
Abstract: Interaction among and unification of people are the very agents that create an organization. An organization can only exist if it exchanges individuals, information, or material resources with the environment permanently surrounding it. Many organizational scientists have recognized that the environment plays a significant but not absolute role in the origin and evolution of organizations (see, e.g., Lawrence & Lorsch, 1967; Meyer & Scott, 1983; Pfeffer & Salanick, 1978). Although every organization continually feels the influence of the environment, it can preserve integrity (invariability of behavior) through four natural operators:
TL;DR: Brown and Eisenhardt as mentioned in this paper defined complex adaptive systems (CAS) as nonlinear systems made up of multiple interacting agents that are sufficiently different from each other that their behavior will not be exactly the same in all conditions.
Abstract: The operational art of air power, as articulated by its earliest pioneers (Douhet, Mitchell, and Trenchard) as well as by recent air power theorists (Col. John Warden III, Lt. Col. Stephen McNamara, and others), has increasingly been seen as innately flexible, nonlinear, and adaptive. From the reconnaissance, air supremacy, and strategic bombardment lessons of the First and Second World Wars to recent experiences in the Gulf War and Operation Allied Force with stand-off precision engagement and parallel system-wide attacks on enemy leverage points, the US Air Force has learned to minimize force-on-force encounters by first removing an enemy’s ability to resist. In essence, the enemy and the Air Force are thought of as “complex adaptive systems.” Complex adaptive systems (CAS) are defined here as nonlinear systems made up of multiple interacting agents that are sufficiently different from each other that their behavior will not be exactly the same in all conditions (Brown & Eisenhardt, 1998: 18).
TL;DR: A discipline that is based on a unified concept of information in order to enable us to cope with the challenges facing the emerging information societies on a global scale is about to take shape.
Abstract: An as yet to be developed unified theory of information will have to be based on the most advanced insights into the evolution and order of what we perceive as our world Contributions to the development of a theory of such evolutionary systems often use concepts of emergence without elaborating the ontological dimension Particularly its presuppositions about causality and determinism remain unclear A less strict determinism in causal relationships as well as a concept of the stages of systemic evolution however will be shown to be prerequisites for a proper understanding of information phenomena The Quest for a Unified Theory of Information Since the nature of the global challenges facing the system of world society is widely recognized to be complex and all encompassing these challenges require to be approached in an as complex and all encompassing a way (Mainzer ) After centuries of predominance of the analytical ratio i e the modern Western controlled (natural) sciences critics like to call for a paradigm change in academic thinking in the direction of a synthetic overall view However this integrative view of what can be perceived by human intelligence does not need to indeed must not be a return to the pre modern vision of the speculative natural philosophy of Antiquity Rather it can and must assimilate the knowledge gained from research in all disciplines in an historical process which rises from the abstract to the concrete That is what philosophers aim at when they want science to revisit the ideas of the enlightenment with reason as a guide (see e g Schäfer ) Although the split into a number of disciplines which are both estranged and deaf to each other is still an obstacle to this development the urge to transcend the barriers between the disciplines the trend towards transdisciplinarity and the search for a base of understanding between the domains of science has been growing What is known as “sciences of complexity ” “theories of dynamic open non linear systems ” “second order cybernetics ” “self organization theories ” is one element if not the core of this overall shift (Laszlo ) The goal is therefore the compatibility of all theories in the field of science and the generalization of their results without however the benefit of a paradigm change in those disciplines that are concerned in one way or another with information processes i e cognition communication and cooperation processes in and outside of society There is no general theory of information that deserves the name Nonetheless a discipline that is based on a unified concept of information in order to enable us to cope with the challenges facing the emerging information societies on a global scale is about to take shape Whilst at the end of World War II the concept of information was still seen largely from a limited and one sided military point of view scientific debate on the topic has since been dominated by attempts to move away from these limitations and to adopt a different perspective Semiotic considerations entered into the discourse Shannon‘s syntactic definition was thus followed by attempts to formulate a semantically based concept (most notably by Carnap and Bar Hillel [ ]) and a pragmatically based concept (with E v Weizsäcker [ ] as its most prominent proponent) Since then there has been a search for a concept that is able to integrate the various aspects of information processes include useful discoveries owed to the old concept as special cases and develop the old information theory into a new one a universal theory Thus conceptualisations that date from the second half of the ’s mark the beginning a new period These are ( ) the hypothesis of the control revolution with which James R Beniger ( ) draws parallels between the breakthrough to the information society and former revolutions in the course of the development of life on earth and human culture; ( ) the hypothesis of the evolution of information processing systems put forward by Klaus Haefner ( ) which regards the information society as the end product of the evolution of systems we know in the universe capable of generating ever higher information levels These two outstanding contributions are the initial steps towards a single comprehensive information science Such a science–the term used hitherto to signify library science only is hereby redefined–is in fact the point where endeavours of scholars of various disciplines from Europe the USA Japan and other countries have been converging since the early nineties A series of conferences and publications on the foundations of information science has documented and presented this impending paradigm change to the scientific community (e g Hofkirchner a) Every scientific enterprise serves a particular purpose pursues research in a particular area and does so by applying a particular approach (Hofkirchner b) An Information science based on a unified theory of information ( ) would likewise aim at contributing toward what generally is called sustainable development of the global information society by means of “re engineering” the information infrastructure ( ) in keeping with true insights into how information is generated in cognitive communicative and cooperative processes in economic political cultural environmental and technological subsystems of world society ( ) which must be gained by transdisciplinary methods The focus of this paper will be on what is deemed to be a prerequisite for a unified theory of information as well as one for the shift towards a synthetic world view It is located at the second level and relates to how information generation is assumed in the context of causality and determinism Since this assumption deals with the object of the investigation and its mode of existence it is an ontological one and the discussion of this assumption will be an ontological one The Ontological Aspect of Emergentism
TL;DR: Goodhue et al. as mentioned in this paper discuss the problem of systemic organizational change, and present an incentive mechanism that works too well in the context of complexity and organization, which they call When an Incentive Isn't: An Addictive Motivator that Works Too Well.
Abstract: December 31, 2001 · Emergence Alan Goodhue, Karen Norum Goodhue A, Norum K. When an Incentive Isn’t: An Addictive Motivator that Works Too Well. Emergence: Complexity and Organization. 2001 Dec 31 [last modified: 2016 Nov 21]. Edition 1. doi: 10.emerg/10.17357.e5fd3d5d50aa8c12d4cff3d3ad65dd68. Quests to determine the truth about the difficulties of systemic organizational change begin with questions. We wonder what the problem is with our organizations. Why does almost everyone, including the CEOs who have the most to lose, feel that change is needed? What kind of organizations do we all want (need) to end up with? And what kind of leadership is required to effect this change actually and successfully? Even though the “new science” teaches us that organizations are dynamic living systems (Capra, 1982, 1996; Daft & Lengel, 1998; McKelvey et al., 1999; Senge, 1990; Senge et al., 1999; Wheatley, 1999; Wheatley & Kellner-Rogers, 1996; Zohar, 1997), why do we insist on treating them like machines and attempting to “operate” the people in them (Meyerson, 1998)?