Showing papers on "Complex adaptive system published in 2008"

Governance and Complexity—Emerging Issues for Governance Theory

Abstract: Unexpected epidemics, abrupt catastrophic shifts in biophysical systems, and economic crises that cascade across national borders and regions are events that challenge the steering capacity of governance at all political levels. This article seeks to extend the applicability of governance theory by developing hypotheses about how different governance types can be expected to handle processes of change characterized by nonlinear dynamics, threshold effects, cascades, and limited predictability. The first part of the article argues the relevance of a complex adaptive system approach and goes on to review how well governance theory acknowledges the intriguing behavior of complex adaptive systems. In the second part, we develop a typology of governance systems based on their adaptive capacities. Finally, we investigate how combinations of governance systems on different levels buffer or weaken the capacity to govern complex adaptive systems.

Resilience, Robustness, and Marine Ecosystem-based Management

Abstract: Marine ecosystems provide essential services to humans, yet these services have been diminished, and their future sustainability endangered, by human patterns of exploitation that threaten system robustness and resilience. Marine ecosystems are complex adaptive systems composed of individual agents that interact with one another to produce collective effects, integrating scales from individual behaviors to the dynamics of whole systems. In such systems, small changes can be magnified through nonlinear interactions, facilitating regime shifts and collapses. Protection of the services these ecosystems provide must therefore maintain the adaptive capacities of these systems by preserving a balance among heterogeneity, modularity, and redundancy, tightening feedback loops to provide incentives for sound stewardship. The challenge for management is to increase incentives to individuals, and tighten reward loops, in ways that will strengthen the robustness and resilience of these systems and preserve their ability to provide ecosystem services for generations to come.

Embracing Chaos and Complexity: A Quantum Change for Public Health

Abstract: Public health research and practice have been guided by a cognitive, rational paradigm where inputs produce linear, predictable changes in outputs. However, the conceptual and statistical assumptions underlying this paradigm may be flawed. In particular, this perspective does not adequately account for nonlinear and quantum influences on human behavior. We propose that health behavior change is better understood through the lens of chaos theory and complex adaptive systems. Key relevant principles include that behavior change (1) is often a quantum event; (2) can resemble a chaotic process that is sensitive to initial conditions, highly variable, and difficult to predict; and (3) occurs within a complex adaptive system with multiple components, where results are often greater than the sum of their parts.

Sustainability Indicators for Tourism Destinations: A Complex Adaptive Systems Approach Using Systemic Indicator Systems

Abstract: This article discusses the necessity for complementing linear sustainability assessment tools, which disregard the complex and dynamic nature of tourism, with complex adaptive systems (CASs) approaches. A methodological framework for the selection and evaluation of sustainability indicators for tourism destinations, the systemic indicator system (SIS), is proposed; this framework takes the interrelatedness of sociocultural, economic and environmental issues into account. The SIS methodology is tested using a case study of a holiday eco-village project near Lamington National Park in Queensland, Australia. The results show that tourism destinations need to be viewed and studied as CASs, and that sustainability indicator systems need to be applied in the context of an adaptive management approach. Special attention is given to the capability of the SIS methodology as a decision aid for resort developers and planners to improve the effectiveness of measures for pollution prevention and mitigation.

Requirements for Adaptive Water Management

Abstract: Numerous arguments have been put forward regarding the need for a major change in water resources management. In particular increasing awareness of the impacts of climate change has lead to the insight that water management must be become more flexible in order to deal with uncertainties and surprise. This paper argues for a paradigm shift through the development and implementation of integrated and adaptive water management approaches. Adaptive management is defined here as a systematic process for improving management policies and practices by learning from the outcomes of implemented management strategies.

“Smart parts” supply networks as complex adaptive systems: analysis and implications

Abstract: Purpose – The purpose of this paper is to critically analyze whether supply networks may be validly treated as complex adaptive systems (CAS). Finding this to be true, the paper turns into the latest concerns of complexity science like Pareto distributions to explain well‐known phenomena of extreme events in logistics, like the bullwhip effect. It aims to introduce a possible solution to handle these effects.Design/methodology/approach – The method is a comparative analysis of current literature in the fields of logistics and complexity science. The discussion of CAS in supply networks is updated to include recent complexity research on power laws, non‐linear dynamics, extreme events, Pareto distribution, and long tails.Findings – Based on recent findings of complexity science, the paper concludes that it is valid to call supply networks CAS. It then finds that supply networks are vulnerable to all the nonlinear and extreme dynamics found in CAS within the business world. These possible outcomes have to b...

Social-ecological resilience and socio-technical transitions: critical issues for sustainability governance

Abstract: Technology contributes both positively and negatively to the resilience of social-ecological systems, but is not considered in depth in that literature. A technology-focused literature on sociotechnical transitions shares some of the complex adaptive systems sensibilities of social-ecological systems research. It is considered by others to provide a bridging opportunity to share lessons concerning the governance of both. We contend that lessons must not be restricted to advocacy of flexible, learning-oriented approaches, but must also be open to the critical challenges that confront these approaches. Here, we focus on the critical lessons arising from reactions to a transition management approach to governing transitions to sustainable socio-technical regimes. Moreover, we suggest it is important to bear in mind the different problems each literature addresses, and be cautious about transposing lessons between the two. Nevertheless, questions for transition management about who governs, whose system framings count, and whose sustainability gets prioritised are pertinent to social-ecological systems research. They suggest an agenda that explores critically the kinds of resilience that are helpful or unhelpful, and for whom, and with what social purposes in mind.

Society as a Complex Adaptive System

Abstract: Originally published as Buckley, W. (1 968). "Society as a complex adaptive system," in W. Buckley (ed.), Modern Systems Research for the Behavioral Scientist, Chicago, IL: Aldine Publishing Company. Reprinted with kind permission. Although the phrase "complex adaptive system" is one usually thought to have been coined at the Santa Fe Institute sometime during the 1990s, we can see by the title of this classic paper that the systemsoriented social thinker Walter Buckley had already been using the phrase "complex adaptive system" as early as 1968 and with pretty much the same connotations as it is used today. Thus, similar to how the phrase is contemporarily employed, Buckley explicitly crafted "complex adaptive system" to counter an equilibriumbased, "closed" view of systems which he felt was endemic at the time of his writing this paper. The idea that the dynamics of social systems were dominated by an equilibriumseeking tendency had become entrenched in social thought ever since the great economist Vilfredo Pareto (who, interestingly enough, had also introduced early speculations on power-law type distributions which are so popular today in complexity circles) had enunciated it strongly in his early version of sociology in the late nineteenth century. For Pareto, as was true among most economists at the time (and, as hard to believe as it is, is still so), equilibriumseeking dynamics were at the core of economic theory (for a discussion of the idea of equilibrium-dominating in social and psychological systems, see Goldstein, 1990, 1995). According to Laurence Henderson (1935), himself an early "general" systems theorist from within the discipline of physiology (and from which Walter Cannon had derived his own notion of physiological "homeostasis"), Pareto's thesis at the Polytechnic School of Turin was on the mathematical theory of equilibrium in elastic solids. Pareto had it that a social system was bound by equilibrium, as in any mechanical system so constructed, which meant that the system would automatically return to its former state after any sort of perturbation of its key variables (within a certain amount; see the Appendix below for Henderson's mathematical formulation of this understanding of equilibrium). Henderson also indicated how close Pareto's equilibrium model of social systems was to the equilibrium model of physical chemistry put forward and made a keystone of that discipline Le Chatelier. It was against interpretations of social dynamics as being dominated by equilibrium that Buckley offered his inspired exposition of complex adaptive systems. Unlike a system governed by a propensity to return to equilibrium after being disturbed, and in so doing losing structure as entropy increased, Buckley's complex adaptive systems built-up structure as they adapted in the face of new internal and external interactions. Buckley's classic paper "Society as a Complex Adaptive System" (Buckley, 1968) can be seen as providing a useful bridge between the interests of complexity scientists and those of social entrepreneurs as they struggle to apply the concepts of complex adaptive systems to societal (social) change and innovation. The paper exemplifies the early sociological formulation of the concepts of complexity and system-adaptation in the context of social value creation and societal change. Buckley's career as an American sociologist spanned the micro-meso-macro social divides by bringing a pragmatic understanding to complex social contexts that both social entrepreneurs and complexity scientists will appreciate. In general, Walter F. Buckley (1922-2006) is considered a pioneer in the field of modern social systems, sociology, and sociocybernetics. His early academic career resulted in the publication of Sociology: A Modern Systems Theory (1967) in which he constructed a foundation for a very contemporary-sounding dynamic, morphogenic conceptualization of coevolving social structures that was not dependent on the ideas of equilibrium- or homeostasis-seeking processes. …

Emergent Strategic Management and Planning Mechanisms in Complex Adaptive Systems

Abstract: Complexity theory demonstrates that there are fundamental conceptual difficulties in the concepts of ‘planning' in any open system which contains a significant level of decentralization of decision making. This paper presents a revised conceptual framework for strategic management in the public domain, consistent with the restrictions on ‘system predictability' inherent in complex adaptive systems – a strategic shaping and ‘meta-planning' role, rather than strategic planning. The article illustrates how this reconceptualized role can be applied in a case study of Best Value (BV) in local government in the UK from 1997 onwards. It shows how the behaviours and strategies of agents owed at least as much to emergent complex interactions within the policy system as to the cognitive processes occurring in any one agency. This underlines the weaknesses of over-elaborate analysis of single agency interventions into public policy, strategy or governance within policy systems whose interactions are only pa...

The Allure of Machinic Life: Cybernetics, Artificial Life, and the New AI

Abstract: In The Allure of Machinic Life, John Johnston examines new forms of nascent life that emerge through technical interactions within human-constructed environments--"machinic life"--in the sciences of cybernetics, artificial life, and artificial intelligence. With the development of such research initiatives as the evolution of digital organisms, computer immune systems, artificial protocells, evolutionary robotics, and swarm systems, Johnston argues, machinic life has achieved a complexity and autonomy worthy of study in its own right. Drawing on the publications of scientists as well as a range of work in contemporary philosophy and cultural theory, but always with the primary focus on the "objects at hand"--the machines, programs, and processes that constitute machinic life--Johnston shows how they come about, how they operate, and how they are already changing. This understanding is a necessary first step, he further argues, that must precede speculation about the meaning and cultural implications of these new forms of life. Developing the concept of the "computational assemblage" (a machine and its associated discourse) as a framework to identify both resemblances and differences in form and function, Johnston offers a conceptual history of each of the three sciences. He considers the new theory of machines proposed by cybernetics from several perspectives, including Lacanian psychoanalysis and "machinic philosophy." He examines the history of the new science of artificial life and its relation to theories of evolution, emergence, and complex adaptive systems (as illustrated by a series of experiments carried out on various software platforms). He describes the history of artificial intelligence as a series of unfolding conceptual conflicts--decodings and recodings--leading to a "new AI" that is strongly influenced by artificial life. Finally, in examining the role played by neuroscience in several contemporary research initiatives, he shows how further success in the building of intelligent machines will most likely result from progress in our understanding of how the human brain actually works.

Management Strategies for Complex Adaptive Systems Sensemaking, Learning, and Improvisation

Abstract: Misspecification of the nature of organizations may be a major reason for difficulty in achieving performance improvement. Organizations are often viewed as machine-like, but complexity science suggests that organizations should be viewed as complex adaptive systems. I identify the characteristics of complex adaptive systems and give examples of management errors that may be made when these characteristics are ignored. Command, control and planning are presented as managerial tasks that come to the fore when a machine view of organizations dominates thinking. When we treat organizations as complex adaptive systems the focus of managerial activity changes, and sensemaking, learning and improvisation become appropriate strategies for performance improvement. Each of these is defined and described. A modest research agenda is presented.

Managerial applications of corporate social responsibility and systems thinking for achieving sustainability outcomes

Abstract: There is a gap between organizations' intentions to adopt corporate social responsibility (CSR) policies and their provision of a clear strategy and management tools for practically realizing such intentions. In particular, the literature to date has not yet developed a pragmatic, descriptive summary of firms' designs for CSR adoption, along with a practical menu of ways to implement their designs in organizational systems. To address these gaps, this paper aims to make three principle contributions. First, it defines CSR, sustainability and their relationship in practical terms. Second, it develops a typology of CSR standpoints that incorporates a number of other classifications. Third, it offers a menu of practical methods and measurement metrics based on interpretive and complex adaptive systems perspectives. The result is a hands-on guide to the process of achieving sustainability goals and objectives from a variety of ideological positions and systems designs, thereby contributing to both managerial practice and sustainability theory. Copyright © 2008 John Wiley & Sons, Ltd.

Complexity, Management and the Dynamics of Change: Challenges for Practice

Abstract: Synopsis In this profoundly important text, Elizabeth McMillan shows how the insights of complexity science can allow today's managers to embrace the challenges and uncertainty of the twenty-first century, and successfully oversee organizational change and development. Complexity science refers to the study of complex adaptive systems. These can absorb information, learn and then intelligently adapt in response to environmental changes. This book brings these ideas into an important new arena by: outlining the historical relationship between science and organizations; reviewing current perspectives on organizational change and best practice; citing real-life examples of the use of complexity science ideas; and discussing issues which may arise when using ideas from complexity.Written in an accessible style to bridge the gap from scientific theory to commercial applicability, this ground breaking text shows how organizations can become more effective, democratic and sustainable through complexity science. It is a key text for all students of business and management, and all practitioners working in the field.

The meaning of integrated care: a systems approach.

Abstract: Introduction: Organizations can be regarded as systems. The traditional model of systems views them as machines. This seems to be insufficient when it comes to understanding and organizing complex tasks. To better understand integrated care we should approach organizations as constantly changing living organisms, where many agents are interconnected in so-called Complex Adaptive Systems (CAS). Theory and discussion: The term “complex” emphasizes that the necessary competence to perform a task is not owned by any one part, but comes as a result of co-operation within the system. “Adaptive” means that system change occurs through successive adaptations. A CAS consists of several subsystems called agents, which act in dependence of one another. Examples would be the ant-hill, the human immune defence, the financial market and the surgical operating theatre team. Studying a CAS, the focus is on the interaction and communication between agents. Although these thoughts are not new, the CAS-approach has not yet been widely applied to the management of integrated care. This helps the management to understand why the traditional top down way of managing, following the machine model thinking, may meet with problems in interdependent organizations with complex tasks. Conclusion: When we perceive health and social services as CASs we should gain more insight into the processes that go on within and between organizations and how top management, for example within a hospital, in fact executes its steering function.

Connecting the Dots: Applying Complexity Theory, Knowledge Management and Social Network Analysis to Policy Implementation

Abstract: INTRODUCTION It has been more than 25 years since the publication of Lipsky's Street Level Bureaucracy (1980), and while his work is cited repeatedly in studies of policy implementation, little theoretical work has been done to deepen our understanding of the fundamental mechanisms that lead to the emergence of behaviors resulting in implementation success or failure. This article brings together complexity theory as a language for understanding, and social network analysis (SNA) as a method for examining policy implementation, while extending the work of (Mischen, 2007) that treats policy implementation as the outcome of knowledge management. The "Dots" Several authors have made important connections between complexity theory and network analysis (Carroll & Burton, 2000; Costa, Rodrigues, Travieso, & Villas Boas, 2007), network analysis and policy implementation (Choi & Brower, 2006), policy implementation and knowledge management (Mischen, 2007; Sandfort, 1999), and knowledge management and complexity theory (Bardzki & Reid, 2004; McElroy, 2003; Ruggles & Little, 2000; Tasaka, 2002), but there has been no attempt to integrate all four concepts. Additionally, while complexity theory has been applied to the public sector (Elliot & Kiel, 1999; Morcol, 2002; Rhodes & MacKechnie, 2003) there are no studies that apply complexity theory specifically to policy implementation. Likewise, network analysis has been used extensively to study intraorganizational behavior, but has not been linked to the study of knowledge management in particular. Successful knowledge management is critical to successful policy implementation. Choo (1998) describes a "knowing organization" as one that is able to successfully manage the sensemaking, knowledge creation and decision making processes of an organization. As noted by both Lipsky (1980) and Pressman and Wildavsky (1984), implementation is the outcome of a decision-making process. In a street-level bureaucracy, large numbers of frontline workers make decisions concurrently concerning clients. While "first generation" knowledge management (KM) studies focused largely on the role of information technology, more recent KM scholars have argued that knowledge develops and is shared by complex adaptive systems (Bardzki & Reid, 2004; McElroy, 2003; Ruggles & Little, 2000; Tasaka, 2002) and should be integrated with theories of organizational learning (Easterby-Smith & Lyles, 2003). A complex adaptive system (CAS) is one in which a large number of moderately connected and interdependent agents co-evolve when they find themselves far-from-equilibrium. For new structures and order to be created, the system must be pushed away from an equilibrium condition, otherwise changes will be temporary and as the system will revert to its stable state (Mitleton-Kelly, 2003). Through feedback loops, these agents self-organize and create behavioral "paths" within a limited space of possibilities. What emerges is a pattern of behavior that is influenced greatly by the historicity and locality of the system. In other words, agents adapt to their environments by learning, which is a social process. McElroy (2003) argues that complexity theory provides the missing theory of how cognition happens in social systems, which has been lacking from both knowledge management and organizational learning theory. Organizations and interorganizational networks are social systems because they involve interactions between agents. Various systems--everything from neural networks to ant colonies--have been studied from a complexity theory perspective (Kauffman, 1995; Waldrop, 1992). Social networks differ from other biological networks and processes (Newman & Park, 2003) because social networks involve a dense level of historicity: humans remember the past. Therefore, the ability of individuals to adapt their behavior as a result of learning from the past allows adaptations in human systems to occur at a much quicker pace than other systems (Holland, 1995). …

A Spiral of Innovation Framework for Social Entrepreneurship: Social Innovation at the Generational Divide in an Indigenous Context

Abstract: This paper explores the notion of social innovation as it arises in indigenous communities In particular, we consider entrepreneurial activity in Maori communities where innovation arises through the interaction of the young opportunity seeking entrepreneur (potiki) and the elder Statesperson (rangatira) To explore this behavior in more detail we draw on a neoSchumpeterian understanding of innovation as self-organization: new combinations are seen as "the deliberate formation and re-formation of cooperating groups" (Foster, 2000: 319) We consider social entrepreneurship in the form of indigenous entrepreneurship, in particular Maori entrepreneurship Indigenous entrepreneurship operates at the intersection of social and economic entrepreneurship (Anderson et ah, 2006) It incorporates both social and economic entrepreneurial activity and explicitly acknowledges the particular historical and cultural context from which they arise (Tapsell & Woods, 2007) We discuss Maori entrepreneurship as a complex adaptive system and provide an illustrative example of one social entrepreneurship venture: Maori Maps Based on this discussion we suggest that innovation can usefully be thought of as a double spiral combining the twin flows of opportunity and heritage Introduction Defining social entrepreneurship has proven to be a challenging task (see Massetti; Seitanidi; and Trexler all in this volume as well as: Cheli, 2007; Roberts & Woods 2005; Austin et al, 2006; Dorado, 2006) However, two things are common across the plethora of definitions emerging over the past two decades: 1) an underlying drive to create social value; and, 2) activity characterized by change and the creation of something new rather than the replication of existing enterprises or processes (Austin et al, 2006) Given that change and innovation are inextricably woven within complexity thinking, complexity science makes sense as a relevant perspective to take when engaging in entrepreneurial research (McKelvey, 2004: 314) It also provides an opportunity to connect social entrepreneurship to the theoretical foundations of economic entrepreneurship In particular, we suggest that a neo-Schumpeterian understanding of innovation as self-organization creates a rich avenue from which to explore social entrepreneurship and innovation Hence, for the purposes of this paper we wish to focus on those aspects of complexity science that assist our understanding of how innovation can occur as self-organization within a social context To do this we first provide some brief background on complexity science and Schumpeterian thinking as it relates to self-organization and complex adaptive systems We then discuss complex adaptive systems with reference to interactions that occur within a social structure The specific structure that we explore is the Maori tribal community and the interactions between the potiki (young opportunity seeker) and the rangatira (chiefly elder) that lead to social innovation We then discuss the emergence of "Maori Maps" as an example of social innovation Here opportunity, as sought by potiki within the context of tribal heritage, shapes the path to innovation We suggest that innovation can usefully be thought of as a recurring double spiral, the "Spiral of Innovation," which in Maori is symbolically represented by the double spiral of creation (Takarangi), incorporating opportunity and heritage Background A complex system comprises numerous agents interacting according to particular rules; the system is adaptive in that agents through their interactions coadapt, colearn and coevolve (Holland, 1995; Maguire & McKelvey, 1999) Complex adaptive systems (CAS) are "neural like networks of interacting, interdependent agents who are bonded in a cooperative dynamic by common goals, outlook, rules etc" (Uhl-Bien et al, 2007: 299) They have multiple, overlapping hierarchies and are linked together in a dynamic interactive network …

Intelligent Complex Adaptive Systems

Abstract: The universe is a massive system of systems -- for example, ecological systems, social systems, commodity and stock markets. These systems are complex, constantly adapting to their environment, and many are essential to the very existence of human beings. To fully understand these systems, complex adaptive systems research uses systemic inquiry to build multi-level and multidisciplinary representations of reality to study these systems. Applications of Complex Adaptive Systems provides a global view of the most up-to-date research on the strategies, applications, practice, and implications of complex adaptive systems, to better understand the various critical systems that surround human life. Researchers working in the field of complex adaptive systems and related fields such as machine learning and artificial intelligence, multi-agent systems, and data mining, as well as professionals in related applications such as defense, bioinformatics, and sociology will find this book an indispensable, state-of-the-art reference.

Applications of Complex Adaptive Systems

Abstract: The universe is a massive system of systems -- for example, ecological systems, social systems, commodity and stock markets These systems are complex, constantly adapting to their environment, and many are essential to the very existence of human beings To fully understand these systems, complex adaptive systems research uses systemic inquiry to build multi-level and multidisciplinary representations of reality to study these systems Applications of Complex Adaptive Systems provides a global view of the most up-to-date research on the strategies, applications, practice, and implications of complex adaptive systems, to better understand the various critical systems that surround human life Researchers working in the field of complex adaptive systems and related fields such as machine learning and artificial intelligence, multi-agent systems, and data mining, as well as professionals in related applications such as defense, bioinformatics, and sociology will find this book an indispensable, state-of-the-art reference

Adaptive Responsibilities: Nonlinear Interactions in Cross Sector Social Partnerships

Abstract: This paper presents an instance of failed large scale social innovation from a cross sector social partnership even though the partnership seemed to succeed in its narrow mission The mechanisms that led to less than complete success can shed light on the reasons behind the failure of social change mechanisms The case study presented is between a non-profit organization and a business It demonstrates that when the strategic intent of the social actors is prescriptive, it imprisons the possibilities for fundamental change This limitation is due to the pre-defined relatively narrow responsibilities associated with different individual or social agents The paper is calling to move beyond reactive and proactive responsibilities and to shift towards accepting adaptive responsibilities that require a multidimensional understanding towards all three levels of analysis, micro, meso and macro Adaptive responsibilities is an empowering approach based on the coevolution of organizational actors It holds the seeds of reciprocal multi-level change Introduction The growing intensity of relations between non-profit organizations and businesses (Gray, 1989; Young, 1999; Austin, 2000; Googins & Rochlin, 2000) due to the need for sharing both tangible and intangible resources (Seitanidi, 2007) has resulted in increased interactions across diverse social sectors At the same time, the growing prominence of the concept of corporate social responsibility (CSR) (Crane & Matten, 2007; Moon, 2004) has elicited a vigorous debate regarding the responsibilities of each sector in addressing social problems (Seitanidi, 2005) as well as an increase in interactions across the sectors thereby propelling non-profit organization-business (NPO-BUS) partnerships as one of the key mechanisms for delivering solutions to social problems (Heap, 1998; Mohiddin, 1998; Folwer, 2000; Googins & Rochlin, 2000; Brehm, 2001; Drew, 2003; Hemphil & Vorontas, 2003) The intersection of these sectors has served to create a useful test arena wherein researchers can explore the potential benefits of interactions between hybrid non-profit and for-profit business models which has important implications for social entrepreneurial projects In the past social problems and forprofit actions were conceived mono-dimensionally and, accordingly, only the responsibility of the single sector in question Although social problems were typically held to be the responsibility of the public sector, gradually the non-profit sector took on some of these responsibilities either proactively or as a result of the wider public sector's desire to 'hive off those responsibilities that were perceived as high risk or high cost (Bovaird et al, 2002: 421) More recently, with the emergence of CSR as an emerging cultural norm, actors within the for-profit sector have begun to capitalise on the positive reputational benefits of taking on some of the responsibility for social problems Indeed, the failure of single-sector solutions has made quite evident that social problems such as poverty, HIV/AIDS and environmental degradation are complex issues that often cannot be solved by social agents within one social sector alone Instead, many social problems require multi-sector solutions which require increased levels of interactions among previously disconnected groups Accordingly, new social processes are emerging such as cross-sector social partnerships and social entrepreneurship This paper presents case study data from an NPO-BUS partnership in order to draw lessons for social entrepreneurship in general Social entrepreneurship and cross sector social partnerships as complex adaptive systems Social entrepreneurship (SE) is a hybrid form of social process (Dees, 1998; and Trexler, in this volume) which combine the unique characteristics of the for-profit, non-profit and government sectors depending upon the situation and the history of organizing activities …

Transformation from "Carbon Valley" to a "Post-Carbon Society" in a Climate Change Hot Spot: the Coalfields of the Hunter Valley, New South Wales, Australia

Abstract: This paper examines the possibilities for transformation of a climate-change hot spot—the coal-producing Hunter Region of New South Wales, Australia—using complex adaptive systems (CAS) theory. It uses CAS theory to understand the role of coal in the region's history and efforts to strengthen the ecological, economic, and social resilience of the region's coal industry in the face of demands for a shift from fossil fuel dependency to clean, renewable energy and genuine resilience and sustainability. It uses CAS theory to understand ways in which the resilience of two alternative futures, labeled "Carbon Valley" and "Post-Carbon Society" (Heinberg 2004), might evolve. The paper discusses ways in which changes implemented through the efforts of local communities at local, smaller scales of the nested systems seek to influence the evolution of adaptive cycles of the system at the local, national, and global scales. It identifies the influences of "attractors," defined as factors driving the evolution of the system, that are influential across the panarchy. These include climate change threats, markets, regulatory regimes, political alliances, and local concerns about the environmental and social impacts of the Hunter's coal dependency. These factors are weakening the apparent resilience of the coal industry, which is being propped up by the coal industry corporations, labor unions, and governments to maintain coal dependency in the Carbon Valley. Moreover, they are creating an alternative basin of attraction in which a Post-Carbon Society might emerge from the system's evolutionary processes.

Mental life. A naturalized approach to the autonomy of cognitive agents

Abstract: Recent advances in modelling complex adaptive systems through computer simulation have reconfigured the way in which mechanistic explanations can conceptualize the mind. The goal of the thesis is to make explicit the construction of a modelfor Minds as a complex generative organization. For doing so, and under the difficulties of current approaches to specify cognitive systems as distinct from generic computational or dynamical ones, the construction of a model for minds departs from a minimalist, universal and naturalized conception of agency. Three conditions are state to provide a satisfactory account of agency: self-generated individuality, normativity and causal-asymmetry. A morphophylogenetic approach is proposed whereby increasingly complex models of agency are generated from the bottom-up. The morphophylogenetic reconstruction starts with the origins of life as the emergence of a self-encapsulated chemical network capable to maintain and repair itself. The autonomous organization of living organisms is shown to be capable to satisfy the three conditions for agency. Taking biological autonomy as a departure point the thesis covers the main organizational evolutionary transitions of agency that lead to bilaterian organisms. A number of case studies (E. coli, A. digitale and C. elegans) are provided to illustrate different aspects of such transitions until adaptive behaviour (made possible by multicellular organisms endowed with a nervous systems and mechanically articulated bodies) is precisely defined and its modelling process made explicit. The mechanisms underlying biologically adaptive behaviour are evaluated to test whether they are capable to provide a satisfactory model for minds. A number of problems are found and made explicit for the project of grounding intentionality in biological (metabolic) organization. An alternative research avenue is proposed in which it is the autonomy of behaviour (and not that of its underlying infrastructure) what serves to naturalize intentional agency. It is argued that under certain body and environmental conditions the nervous system will evolve making possible more plastic, flexible and integrated (Le. more complex) behaviour. In turn, complex behaviour makes possible the emergence of a new level of normativity and functionality in living beings, that provided by the developmental history of neural organization, leading to a progressive autonomy of sensorimotor interactions and generating what might be called Mental Life. To characterize it we introduce the notion of neurodynamic sensorimotor structures as the main components of cognitive organization. Mentallife is an open process by which dynamic structures appear nested on a self-sustaining web of stability dependencies. The mind has a life of its own: a self-maintaining dynamic organization that remains open to its world in order to maintain its coherency and identity. We defend that the appearance of an open process of sensorimotor interactions sustained by the nervous system and normatively regulated by its bioregulatory embodiment (an emotional world) gives rise to cognitive phenomena, embedded on but distinct from biological organization. Metal life constitutes a mechanistic generative model for minds and provides a number of new insights on the way in which cognitive and mindful properties could be conceptualized and modelled in contemporary cognitive science and philosophy of mind.

The class as a learning entity (complex adaptive system): An idea from complexity science and educational research

Abstract: Educational theorists are making increasing use of the metaphors and concepts of complexity thinking in their discourses. In particular, Professors Brent Davis, Elaine Simmt, and Dennis Sumara have written extensively about using complexity thinking to shift attention from the individual student as the locus of learning (cognizing agent) to the social collective—the class—as the locus of learning. In this model, the class (students and teacher) is (potentially) a complex adaptive system. The students and teacher remain complex adaptive systems in their own right, but through dynamic local interactions there is the possibility of emergent behaviours indicative of learning that transcends that of the individuals within the class. The social collective we know as a class becomes an instance of the Aristotlean adage, “The whole is greater than the sum of its parts.” (With the coda that we cannot understand the whole by merely understanding the components.) Davis, Simmt, and Sumara have segued from complexity-informed descriptions of educational collectives to discussions about facilitating the self-organization of classes into complex adaptive systems – learning systems, in their language. In this paper, I discuss complex adaptive systems and look at how Davis, Simmt, and Sumara developed their thesis that the class collective, rather than individual student, is the appropriate level to investigate learning and teaching. We conclude by addressing some of the possibilities and challenges inherent in such a redescription of communities of learners.

Emergence in Agent based Computational Social Science: conceptual, formal and diagrammatic analysis.

Abstract: This chapter provides a critical survey of emergence definitions both from a conceptual and formal standpoint. The notions of downward / backward causation and weak / strong emergence are specially discussed, for application to complex social system with cognitive agents. Particular attention is devoted to the formal definitions introduced by (Muller 2004) and (Bonabeau & Dessalles, 1997), which are operative in multi-agent frameworks and make sense from both cognitive and social point of view. A diagrammatic 4-Quadrant approach, allow us to understanding of complex phenomena along both interior/exterior and individual/collective dimension.

Law's Complexity - A Primer

Abstract: The legal system. It rolls easily off the tongues of lawyers like a single word - the legal system - as if we all know what it means. But what is the legal system? How does it behave? What are its boundaries? What is its input and output? How will it look in one year? In ten years? How should we use it to make change in some other aspect of social life? Why do answers to these questions make the legal system seem so complex? Would assembling a cogent, descriptively accurate theory of what makes the legal system complex help us to formulate more accurate and useful propositions about the legal system? I have to believe it would, and in my pursuit of such an explanation I have leaned heavily on the theory of complex adaptive systems - the study of systems comprised of a macroscopic, heterogeneous set of autonomous agents interacting and adapting in response to one another and to external environment inputs. At its deepest level, complex adaptive systems theory as applied to the legal system presents a rich and dynamic field of study. It asks whether the targets of law are complex adaptive systems, and if so what that means for law's design. It asks whether law itself, however we define its boundaries, is also a complex adaptive system, and if so what that means for law's design. And it asks how law and its regulatory targets co-evolve and what that means for law's design. This article orients those three questions within the context of complex adaptive systems theory. Part I provides a short primer on complex adaptive systems theory and suggests ways of usefully mapping it onto the legal system to expand our understanding of its behavior and properties. To make the case for the practical utility complex adaptive systems theory has for law, Part II explores a few of the major implications the theoretical foundation has for institutional and instrument design issues in law. I close by offering suggestions for next steps in the development of the theory of law's complexity.

Complexity and Emergence in Public Management

Abstract: This article reports on a three-year study of six urban regeneration projects in Northern Ireland and the Republic of Ireland in which a ‘complexity perspective’ was applied to the analysis and interpretation of decision making in the public domain. The goal of the research was to gain insight into the features that affect public sector outcomes and agent behaviour, particularly those that emerge over time and contribute to the unpredictability of complex projects. A Complex Adaptive Systems (CAS) analytic framework is applied to the cases, which draws on the concept of a ‘performance landscape’ and a policy ‘arena’ to identify patterns of emergent properties, including new super-agents, new rules and new schema. These properties impact on the decisions, factors and performance outcomes of the projects, the implications of which for public administration theory and practice are discussed in the conclusion.

Emergent Specialization in Biologically Inspired Collective Behavior Systems

Abstract: Specialization is observable in many complex adaptive systems and is thought by many to be a fundamental mechanism for achieving optimal efficiency within organizations operating within complex adaptive systems. This chapter presents a survey and critique of collective behavior systems designed using biologically inspired principles, where specialization that emerges as a result of system dynamics and is used problem solver or means to increase task performance. The chapter presents an argument for developing design methodologies and principles that facilitate emergent specialization in collective behavior systems. Open problems of current research and future research directions are highlighted for the purpose of encouraging the development of such emergent specialization design methodologies.

Application of complex adaptive systems to pricing of reproducible information goods

Abstract: Piracy of copyrighted information goods such as computer software, music recordings, and movies has received increased attention in the literature. Much of this research relied on mathematical modeling to analyze pricing policies, protection against piracy, and government policies. We use complex adaptive systems as an alternative methodology to analyze pricing decisions in an industry with products which can be pirated. This approach has been previously applied to pricing and can capture some aspects of the problem which are difficult to analyze using traditional mathematical modeling. The results indicate that advances in technology make a skimming strategy the least preferable approach for producers. Further, improvements in technology, more specifically data communications and the Internet, will erode the profitability of a skimming strategy. The analysis also indicates that complex adaptive systems may provide a useful method for analyzing problems in which interactions between participants in the systems, i.e. consumers, sellers, and regulating agencies, are important in determining the behavior of the system.