Showing papers on "Complex adaptive system published in 2007"

Complex Adaptive Systems: An Introduction to Computational Models of Social Life

Abstract: Theoretical physics is replete with models. When equations of motion are not available, or not amenable to perturbation theory, or just too hard from which to extract useful information, then physicists turn to models and computation. The Ising model of ferromagnetism is a classic example. A simple nearest neighbor temperature dependent interaction, in two or more dimensions, leads to long-range order and a phase transition at a finite temperature. This model has many locally interacting parts and an emergent behavior (ferromagnetism) at a critical temperature. However, the system never adapts. It does not change the phase transition to a higher temperature or avoid a phase transition altogether. Social systems are always adapting, and this interesting twist produces a vast array of possibilities and forms the basis of much of the discussion in Miller and Page’s book. This book is not a textbook, but rather an essay on complex adaptive systems. The discussions and insights will be better appreciated by readers who have already tried their hand at investigating complex adaptive systems. These systems can be so complex that the best method to discover their properties is to dispatch many computer agents to experience the system’s possibilities. The study becomes more interesting when the agents can alter their actions and the rules of the game. Miller and Page give the simple, but instructive example of forest growth and lightning induced forest fires. If trees grow too rapidly they will cover the allowable space and a fire started anywhere in the forest will spread and destroy the entire forest. A very slow growth will only produce a sparse forest. The authors find a tree growth rate to achieve an optimal stable high forest coverage. Their solution is trumped when altruistic agents are introduced, one for each tree. Some of the agents adapt by not growing a tree in their plot of land (to their personal disadvantage) but the overall global organization is one of firebreaks preventing large scale fires. Adaptation wins! Another model discussed is what physicists call the minority game, that is, making a choice that puts you in the minority. This is perhaps best known through the El Faro example of choosing whether or not to go to Santa Fe’s El Faro bar tonight based on whether it was

Complex adaptive systems

Abstract: The field of Complex Adaptive Systems (CAS) is approximately 20 years old, having been established by physicists, economists, and others studying complexity at the Santa Fe Institute in New Mexico, USA. The field has spawned much work, such as Holland's contributions of genetic algorithms, classifier systems, and his ecosystem simulator, which assisted in provoking the fields of evolutionary computation and artificial life. The framework of inducted principles derived from many natural and artificial examples of complex systems has assisted in the investigation in such diverse fields of study as psychology, anthropology, genetic evolution, ecology, and business management theory, although a unified theory of such complex systems still appears to be a long way off. This work reviews the principles of complex adaptive systems as a framework, providing a number of interpretations from eminent researches in the field. Many example works are cited, and the theory is used to phrase some ambiguus work in the field of artificial immune systems and artificial life. The methodology of using simulations of CAS as the starting point for models in the field of biological inspired computation is postulated as an important contribution of CAS to that field.

The Origin Of Wealth: Evolution, Complexity, and the Radical Remaking of Economics

Abstract: Economics is changing radically. This paradigm shift, the biggest in the field for over a century, will have profound implications for business, government and society for decades to come. In this groundbreaking book, economic thinker and writer Eric Beinhocker surveys the cutting-edge ideas of the leading economists, physicists, biologists and cognitive scientists who are fundamentally reshaping economics, and brings their work alive for a broad audience. These researchers argue that the economy is a 'complex adaptive system', more akin to the brain, the internet or an ecosystem than to the static picture of economic systems portrayed by traditional theory. They claim it is the evolutionary process of differentiation, selection and amplification, acting on designs for technologies, social institutions and businesses that drives growth in the economy over time. If Adam Smith provided the inspiration for economics in the twentieth century, it is Charles Darwin who is providing it in the twenty-first. If we can understand how evolution creates wealth, then we can better answer the question 'How can we create more wealth for the benefit of individuals, businesses and society?' Beinhocker shows how 'Complexity Economics' turns conventional wisdom on its head in areas such as business strategy, the design of organisations, the workings of stock markets and public policy. As sweeping in scope as its title, "The Origin of Wealth" is a landmark book that shatters orthodox economic theory, and will rewire our thinking about how we came to be here - and where we are going.

The Problem of Fit between Ecosystems and Institutions: Ten Years Later

Abstract: The problem of fit is about the interplay between the human and ecosystem dimensions in social-ecological systems that are not just linked but truly integrated. This interplay takes place across temporal and spatial scales and institutional and organizational levels in systems that are increasingly being interpreted as complex adaptive systems. In 1997, we were invited to produce one of three background papers related to a, at that time, new initiative called Institutional Dimensions of Global Environmental Change (IDEG), a research activity of the International Human Dimensions Program of Global Environmental Change (IHDP). The paper, which exists as a discussion paper of the IHDP, has generated considerable interest. Here we publish the original paper 10 years later with an extended introduction and with reflections on some of the issues raised in the original paper concerning problems of fit.

The implications of complexity for integrated resources management

Abstract: Integrated environmental resources management is a purposeful activity with the goal to maintain and improve the state of an environmental resource affected by human activities. In many cases different goals are in conflict and the notion ''integrated'' clearly indicates that resources management should be approached from a broad perspective taking all potential trade-offs and different scales in space and time into account. However, we are yet far from putting into practice integrated resources management fully taking into account the complexity of human-technology-environment systems. The tradition of resources management and of dealing with environmental problems is characterized by a command and control approach. The increasing awareness for the complexity of environmental problems and of human-technology-environment systems has triggered the development of new management approaches. The paper discusses the importance of focusing on the transition to new management paradigms based on the insight that the systems to be managed are complex adaptive systems. It provides arguments for the role of social learning processes and the need to develop methods combining approaches from hard and soft systems analysis. Soft systems analysis focuses on the importance of subjective perceptions and socially constructed reality. Soft systems methods and group model building techniques are quite common in management science where the prime target of management has always been the social system. Resources management is still quite slow to take up such innovations that should follow as a logical consequence of adopting an integrated management approach. Integrated water resources management is used as example to provide evidence for the need to implement participatory and adaptive management approaches that are able to cope with increasing uncertainties arising from fast changing socio-economic conditions and global and climate change. Promising developments and future research directions are discussed. The paper concludes with pointing out the need for changes in the scientific community to improve the conditions for interdisciplinary, system-oriented and trans-disciplinary research.

Complexity and Adaptivity in Supply Networks: Building Supply Network Theory Using a Complex Adaptive Systems Perspective*

Abstract: Supply networks are composed of large numbers of firms from multiple interrelated industries. Such networks are subject to shifting strategies and objectives within a dynamic environment. In recent years, when faced with a dynamic environment, several disciplines have adopted the Complex Adaptive System (CAS) perspective to gain insights into important issues within their domains of study. Research investigations in the field of supply networks have also begun examining the merits of complexity theory and the CAS perspective. In this article, we bring the applicability of complexity theory and CAS into sharper focus, highlighting its potential for integrating existing supply chain management (SCM) research into a structured body of knowledge while also providing a framework for generating, validating, and refining new theories relevant to real-world supply networks. We suggest several potential research questions to emphasize how a CAS perspective can help in enriching the SCM discipline. We propose that the SCM research community adopt such a dynamic and systems-level orientation that brings to the fore the adaptivity of firms and the complexity of their interrelations that are often inherent in supply networks.

Complexity Thinking and Evolutionary Economic Geography

Abstract: Thus far, most of the work towards the construction of an evolutionary economic geography has drawn upon a particular version of evolutionary economics, namely the Nelson-Winter framework, which blends Darwinian concepts and metaphors (especially variety, selection, novelty and inheritance) and elements of a behavioural theory of the firm. Much less attention has been directed to an alternative conception based on complexity theory, yet in recent years complexity theory has increasingly been concerned with the general attributes of evolutionary natural and social systems. In this article we explore the idea of the economic landscape as a complex adaptive system. We identify several key notions of what is being called the new ‘complexity economics’, and examine whether and in what ways these can be used to help inform an evolutionary perspective for understanding the uneven development and adaptive transformation of the economic landscape.

Storytelling, time, and evolution: The role of strategic leadership in complex adaptive systems ☆

Abstract: Organizations are increasingly being described as complex adaptive systems (CAS). In this view, the behavior and structure of an organization emerges out of the interaction of a collection of organizational agents. Seemingly, there is no role for strategic leadership because the system self-organizes. We argue that strategic leaders play a crucial role in moving organizations to the “edge of chaos” and aid in organizational learning and adaptation by influencing the tags that produce the structure of interactions among organizational agents. Through dialogue and storytelling, strategic leaders shape the evolution of agent interactions and construct the shared meanings that provide the rationale by which the past, the present, and the future of the organization coalesce.

Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity)

Abstract: Complex Adaptive Systems An Introduction To Computational Models Of Social Life Princeton Studies In Complexity *FREE* complex adaptive systems an introduction to computational models of social life princeton studies in complexity Computational science (also scientific computing or scientific computation (SC)) is a rapidly growing multidisciplinary field that uses advanced computing capabilities to understand and solve complex problems.It is an area of science which spans many disciplines, but at its core it involves the development of models and simulations to understand natural systems.Computational science Wikipedia Computational science also scientific computing or scientific computation SC is a rapidly growing multidisciplinary field that uses advanced computing capabilities to understand and solve complex problems It is an area of science which spans many disciplines but at its core it involves the development of models and simulations to understand natural systems Chaos theory Wikipedia Chaos theory is a branch of mathematics focusing on the behavior of dynamical systems that are highly sensitive to initial conditions Chaos is an interdisciplinary theory stating that within the apparent randomness of chaotic complex systems there are underlying patterns constant feedback loops repetition self similarity fractals self organization and reliance on programming at the NetSci Schedule The University of Vermont Complex Peter S Dodds Director of the Vermont Complex Systems Center Professor UVM Department of Mathematics and Statistics Peter s research focuses on system level big data problems in many areas including language and stories sociotechnical systems Earth sciences biology and ecology Answering Schrödinger s question A free energy formulation

Leadership and the choice of order: Complexity and hierarchical perspectives near the edge of chaos

Abstract: This conceptual article critically examines the view that, in complex adaptive systems (CAS), organizations are moved toward the edge of chaos and will exhibit “order for free” behaviors. Will organizations naturally self-organize to seek greater fitness? We suggest that, as hierarchies, organizations may be collectively led to establish a dynamic system where bottom-up structuration emerges to increase the long-term viability of the organization. Thus, it is our contention that while there is order for free, a desired order is not. To examine if a desired order for free emerges calls for analyses emphasizing the interplay among leadership, organization hierarchy, and CAS perspectives where these are systematically compared and contrasted. Based on such compare and contrast interplay, we argue that leadership researchers can help foster the evolution of a new type of dynamic emergent hierarchy that yields a sustained desired order across time.

The Global Superorganism: An Evolutionary-cybernetic Model of the Emerging Network Society

Abstract: The organicist view of society is updated by incorporating concepts from cybernetics, evolutionary theory, and complex adaptive systems. Global society can be seen as an autopoietic network of self-producing components, and therefore as a living system or ‘superorganism’. Miller's living systems theory suggests a list of functional components for society's metabolism and nervous system. Powers' perceptual control theory suggests a model for a distributed control system implemented through the market mechanism. An analysis of the evolution of complex, networked systems points to the general trends of increasing efficiency, differentiation and integration. In society these trends are realized as increasing productivity, decreasing friction, increasing division of labor and outsourcing, and increasing cooperativity, transnational mergers and global institutions. This is accompanied by increasing functional autonomy of individuals and organisations and the decline of hierarchies. The increasing complexity of interactions and instability of certain processes caused by reduced friction necessitate a strengthening of society's capacity for information processing and control, i.e. its nervous system. This is realized by the creation of an intelligent global computer network, capable of sensing, interpreting, learning, thinking, deciding and initiating actions: the ‘global brain’. Individuals are being integrated ever more tightly into this collective intelligence. Although this image may raise worries about a totalitarian system that restricts individual initia

The origin of wealth : the radical remaking of economics and what it means for business and society

Abstract: Over 6.4 billion people participate in a $36.5 trillion global economy, designed and overseen by no one. How did this marvel of self-organized complexity evolve? How is wealth created within this system? And how can wealth be increased for the benefit of individuals, businesses, and society? In "The Origin of Wealth," Eric D. Beinhocker argues that modern science provides a radical perspective on these age-old questions, with far-reaching implications. According to Beinhocker, wealth creation is the product of a simple but profoundly powerful evolutionary formula: differentiate, select, and amplify. In this view, the economy is a "complex adaptive system" in which physical technologies, social technologies, and business designs continuously interact to create novel products, new ideas, and increasing wealth. Taking readers on an entertaining journey through economic history, from the Stone Age to modern economy, Beinhocker explores how "complexity economics" provides provocative insights on issues ranging from creating adaptive organizations to the evolutionary workings of stock markets to new perspectives on government policies. A landmark book that shatters conventional economic theory, "The Origin of Wealth" will rewire our thinking about how we came to be here--and where we are going.

On the Evolutionary Dynamics of Supply Network Topologies

Abstract: Supply chains, or supply networks (SNs), exist in a multitude of different topologies, yet little is known concerning how such topologies grow, evolve, and adapt over time. To study this complex phenomenon, we begin by identifying some primary topological structures that SNs may form. Then, to investigate the evolution of such structures, a theory-based framework is developed that combines aspects of complex adaptive systems theory, industrial growth theory, network theory, market structure, and game theory. This framework specifies categories of rules that may evoke different behaviors in the two fundamental components of any adaptive SN, i.e., the environment and the Arms in that environment. The framework is implemented as a multiparadigm simulation utilizing software agents and it joins discrete-time with discrete-event simulation formalisms. This methodology allows the spontaneous generation of network structures so that it is possible to examine the potential factors behind the evolution of different SN topologies. Using data and parameters extracted from 80 years of the U.S. automobile industry, we have been able to "grow" a wide range of SN topologies and preliminary results show that certain environmental and firm-level factors may impact the eventual evolution of such structures.

Complex adaptive systems and nursing.

Abstract: Complex adaptive systems and nursing There have been numerous references to complexity theory and complex systems in the recent healthcare literature, including nursing. However, exaggerated claims have (in my view) been made about how they can be applied to health service delivery, and there is a widespread tendency to misunderstand some of the concepts associated with complexity thinking (usually justified by describing the misconception as a metaphor). These concepts can be extended to systems and structures in healthcare organisations but, at this stage in the development of complexity science, only in a modest and very cautious way. In this paper I first outline some of the key ideas in the theory of complex adaptive systems, and then suggest that they have been distorted by a series of influential articles in the medical literature. I go on to present a simple case study of my own and undertake a complexity analysis of it. In the conclusion I suggest that we should beware of some outdated ideas being trotted out in the guise of complexity — an exciting and diverse area of enquiry that those old ideas do not, in fact, resemble.

Business ecosystem as a perspective for studying th e relations between firms and their business networks

Abstract: In this paper we try to mature the business ecosyst ems concept as a research perspective for studying the relation between firms and their busin ess networks. As economic activities are changing from dominantly stand-alone to networked, new perspectives are needed to study these relationships. The business ecosystem metaphor provides an interesting starting point for such a perspective. We provide an overview of current rese arch on business ecosystems and we define the aspects that are core to a business ecosystem persp ective, namely, the firms, the network, performance and governance. We examine how these core aspects can be further developed building on (social) network theory, biological ecosystem th eory and complex adaptive system theory. Finally, we proposed to integrate these core aspect s into a comprehensive complexity logic.

Nasdaq Market Simulation: Insights on a Major Market from the Science of Complex Adaptive Systems

Abstract: This pioneering book describes the applications of agent-based modeling to financial markets. It presents a new paradigm for finance, where markets are treated as complex systems whose behavior emerges as a result of interactions of market participants, market institutions, and market rules. This includes both a presentation of the conceptual model and its software implementation. It also summarises the result of the profound research on the successful practical application of this new approach to answer questions regarding the Nasdaq Stock Market s decimalization that was implemented in 2001. The book presents conceptual foundations for modeling markets as complex systems. It describes the agent-based model of the Nasdaq stock market, including strategies used by market-makers and investors, market participants interactions, and impacts of rules and regulations. It includes analyses of simulation behavior, comparison with the behaviors observed in the real-world markets (existence of fat tails, spread clustering, etc.), and predictions about possible outcomes of decimalization. A framework for calibrating the market behavior and individual market-makers strategies to historical data is also presented.

Complexity Thinking and Evolutionary Economic Geography

Abstract: Thus far, most of the work towards the construction of an evolutionary economic geography has drawn upon a particular version of evolutionary economics, namely the Nelson-Winter framework, which blends Darwinian concepts and metaphors (especially variety, selection, novelty and inheritance) and elements of a behavioural theory of the firm. Much less attention has been directed to an alternative conception based on complexity theory, yet in recent years complexity theory has increasingly been concerned with the general attributes of evolutionary natural and social systems. In this paper we explore the idea of the economic landscape as a complex adaptive system. We identify several key notions of what is being called the new ‘complexity economics’, and examine whether and in what ways these can be used to help inform an evolutionary perspective for understanding the uneven development and adaptive transformation of the economic landscape.

Multi-view SDI Assessment Framework

Abstract: When developing Spatial Data Infrastructures (SDI) initiatives it is increasingly important to assess their outcomes in order to justify the resources spent on those infrastructures. Many researchers throughout the world have been struggling with the issue of assessing SDIs. The task is difficult due to complex, dynamic and constantly evolving nature of SDI. As SDI can be treated as a Complex Adaptive System, the assessment should include strategies for evaluating those kinds of systems. One strategy is to use multiple assessment approaches and methods. The general evaluation research and experience provide additional motives for adopting such a strategy. We present the multi-view framework for assessing SDI initiatives around the world, and argue that the strength of this assessment design lies in its flexibility, its multidisciplinary view on SDI and a reduced bias in the assessment results. The multi-view framework contains methods that not only evaluate SDI performance, but also deepen our knowledge about SDI functioning, and may assist in its development. The article presents the assessment framework and describes its theoretical grounding in complexity theory and evaluation research. The application of the framework is beyond the scope of this paper.

Adaptive Governance: An Introduction and Implications for Public Policy

Abstract: Adaptive governance is a concept from institutional theory that has recently emerged from the study of management arrangements for environmental assets and common pool resources in complex adaptive systems. Adaptive governance is defined as 'the evolution of rules and norms that better promotes the satisfaction of underlying human needs and preferences given changes in understanding, objectives, and the social, economic and environmental context'. This establishes an idealised reference point for examining the dynamics of institutional change - akin to the concept of market failure within economics - and provides a useful framework for identifying impediments to desirable changes and developing effective remedies for these impediments.

Complexity in practice

Abstract: Theories of social practice point to a wide domain of largely tacit social accommodations as the source from which the dynamic structures of social practices are sedimented. The strategy-as-practice initiative seeks to use these insights to widen our appreciation of the origins and evolution of strategy in organizations. This ar ticle suggests that this domain, and its components, can be substantively and literally represented as a complex adaptive system. Complexity gives access to a considerable body of theor y on the emergent orders that may arise from social practice, and on the evolution of social order over time. These carry impor tant implications for the scope of practitioners' agency in leading strategic change, for the locus of strategy in organizations, and for the design of research strategies to investigate these complex phenomena.

Thinking systems need systems thinking

Abstract: After describing machine and complex adaptive systems (CASs), we define thinking system as a CAS with two additional, unique characteristics: (1) having goal(s) separate from survival, and (2) having the capability to structure its own learning and to innovate purposefully. Thinking systems always learn. Healthcare can be considered a paradigm of the thinking system and is repeatedly plagued with unintended, adverse outcomes, particularly fixes that fail. Systems thinking can dissolve such dysfunction in healthcare and by extension in any thinking system. Specific recommendations follow from this rationale. Copyright © 2007 John Wiley & Sons, Ltd.

The state of methods and tools for social systems change.

Abstract: The last decade or so has seen an increase in the rate of attention to systems change and the application of multiple theories to study and influence change in systems. This article considers how these theories, described in other articles in this issues, plus theories about complex adaptive systems open opportunities for us to continue to expand our repertoire of tools and methods to address systems change. These conceptual frameworks, tools, and methods are expected to help us increase our capacity to study and influence both planned and self-organizing systems change. New tools and methods have emerged and others are needed to help us continue to explore and influence the complex social systems within which we operate.

Implementing managerial innovations in primary care: can we rank change drivers in complex adaptive organizations?

Abstract: Background: There has been much innovation in primary care in the past few decades. Although external and systemic constraints for health care organizations are relevant for their managerial evolution, there is also evidence that organizations operating under the same external pressures reach different levels of maturity. Purposes: Which of the internal drivers available explain and foster change? Is it possible to rank change drivers by looking at their rate of efficacy in order to define a general change management path in the relationship between managers and physicians? The study is a hypothesis-generating work, designed to discuss a framework, consistent with the complex adaptive systems literature, for more effective internal change management approaches. Methods: We employed a qualitative approach to conduct a multiple case study in order to directly observe the evidence and to ask "key change players" for their perceptions. We studied different organizations all subject to the same external constraints in order to focus on the effects of internal change drivers. Findings: According to key players' opinions, the main drivers for managerial development are characteristics of the actors involved: their motivation, leadership, and commitment; the quality of relationships among the main actors; and how the resources dedicated to manage change are used. Given these criteria, any organizational strategy and goal seems to be achievable. This is consistent with the suggestions coming from the complex adaptive system literature. Managerial Implications: Managers have to consider the management of the relationship with professionals as the key success factor for implementing change. Managerial leadership has to be diffused in the organization both in the vertical and horizontal dimensions. Innovations need a medium or long-term perspective to become widely applied, and this requires a strong commitment which is related to managerial stability. Resources for innovation are to be considered a critical driver for fostering the relationship between managers and professionals.

The Telecommunications Economy and Regulation as Coevolving Complex Adaptive Systems: Implications for Federalism

Abstract: I. INTRODUCTION II. LIMITS OF THE PRESENT POLICY PARADIGM FOR SUSTAINABLE POLICIES III. TOWARD A NEW PARADIGM FOR SUSTAINABLE POLICIES A. General Constraints and Properties of Sustainable Policies B. Relations of Telecommunications Policy to Complexity Theory 1. Complexity Theory 2. Economic Sectors and Policymaking Systems as Coevolving Complex Adaptive Systems C. General Implications for Sustainable Telecommunications Policies from a Complex Systems Perspective IV. FEDERALISM AS AN INNOVATIVE AND DYNAMIC POLICYMAKING SYSTEM V. HISTORICAL EVOLUTION OF FEDERALISM IN THE U.S. VI. PRESSURES FOR A NEW FEDERALISM MODEL IN THE U.S. VII. USING COMPLEXITY THEORY FOR EVOLUTION OF A NEW FEDERALISM MODEL A. Recognizing Federalism as a Patching Algorithm B. Modifying Federalism for Environmental Regulation C. Comparing Models of Policy Reform D. Using Adaptive Decision-Making Tools for Policymaking in General VIII. TOWARD A REVISION OF FEDERALISM FOR SUSTAINABLE TELECOMMUNICATIONS POLICY I. INTRODUCTION In numerous articles and papers, I have stressed in varying ways that sustainable regulatory telecommunications policies require simultaneous satisfaction of economic viability and political feasibility constraints, and that satisfaction of these constraints is becoming more challenging for regulatory regimes based on competition rather than monopoly. Some articles have examined the sustainability of specific regulatory policies, such as universal service, (1) rate rebalancing, (2) and the effects of detariffing on liability rules. (3) Others have broadened the scope of inquiry, looking at sustainability problems arising from fundamental attributes of the U.S. governance structure, (4) including efforts to retrench from public utility regulation (5) and to resist extension of common carriage obligations to broadband access services. (6) Throughout this research, I have sought to provide the foundation for a more general analytical framework for designing sustainable telecommunications policies based primarily on legal and economic analyses and incorporation of models and insights from the political science literature. Most recently, I have sought to further enhance this framework by incorporating insights from complexity theory. Within the general academic community, there is a growing recognition that complexity theory, originally developed in the physical sciences, may also be applicable to the social sciences. Complexity theory is based on the distinctive properties of complex systems and provides a different paradigm for understanding and interacting with complex systems. Complexity theory is already influencing research concerning sustainable environmental policies, (7) and recent research is examining its potential application to communications policies. (8) In research foundational to this Article, Bauer and I assert that complexity theory should be used to improve our understanding of the requirements for sustainable telecommunications policies. (9) More specifically, Bauer and I assert that if the telecommunications sector and the legal/policymaking institutions are viewed as coevolving and complex adaptive systems, then there are important implications for regulatory policy. One implication is that law and regulation will have a diminishing capacity to achieve specifically desired outcomes but will retain influence over possible, usually unpredictable, trajectories of sector performance. Instead, greater focus must be placed on how to design policies and policymaking processes that are more suitable for interacting with, interpreting, and responding to the telecommunications sector over time. In other words, greater attention must be paid to the adaptability of policies and the policymaking processes themselves as they evolve with the telecommunications sector. …

Complex systems, governance and policy administration consequences*

Abstract: This paper combines insights from literature on complex systems theory and the conjunctive state, applies them to new challenges facing public administrators in metropolitan areas, and tests them in a case study of the Peace Officers Association of Los Angeles County (POALAC). The argument is advanced that administrative networks, shared governance, and co-production of public services developed in the conjunctive state are real-world exemplars of the emergent properties of complex adaptive systems (CAS). As the production of social capital and public trust of government decline in response to the increasing inability of hierarchical, topdown, command-and-control institutions to solve complex societal problems, the fundamental nature of associations and relations among citizens, policy makers, civic leaders, and government is changing in metropolitan areas as government slowly shifts toward governance. The case study of POALAC reveals a coordinated networked administrative response to the complexity of regional law enforcement consistent with theoretical predictions. Introduction This paper explores how complex metropolitan systems are evolving through the creation of administrative networks, and how those networks influence public administration and policy formation through the work of public administrators. It draws on previous research (Bogason, 2000; Meek & Newell, 2005; Morcol, 2002; Newell & Meek, 1997) to establish a synthesis of complex systems theories from which we develop central tenets that ground an understanding of complex urban systems. It then sketches out how these conditions have influenced the recent movement toward shared governance in urban environments. The paper embraces the "conjunctive state" (Frederickson, 1999) as a central feature of public administration. The interplay of administrative conjunction with policy deliberation and administration is then explored through a case study of the collective responses of police officers in Los Angeles county to what is referred to as the "disarticulated state." One concern of the paper is to examine the characteristic policy deliberation and administration that evolves from complex conditions, and the consequences of such deliberations for public administrators. Collective activities among public administrators - administrative conjunction - greatly influence policy administration. What is yet to be explored in both the policy and administrative networkliteratures are consequences ofadministrative conjunction that are a product of complex jurisdictional interdependences as well as a contributor to complex urban system management. The very condition of complexity that draws administrators to work collectively is reflective of their deliberation and collective action. Such influence also has administrative consequences. The goal of this paper is to examine these consequences and highlight their implications for advancing complexity thinking for innovation in public administration. The paper opens with a review of selected literature on complexity theory and its relevance for public administration, followed by characterization of metropolitan environments as "disarticulated states" full of complexity and self-organization. These forms of collective activities are then discussed within the context of public management network theory. Finally, the paper examines a case study analysis of the POALAC network in order to highlight the central policy administrative consequences that evolve out of conjunctive practices. Complex systems theory, while developed in the natural sciences, has much to offer the social sciences. While our previous work provided a cautious assessment of the applicability of various complex systems theories to human behavior (Newell & Meek, 2000), this paper provides a summary of findings from recent literature on complex systems that can be applied to the recent movement toward shared governance in urban environments - the socalled conjunctive state. …