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Showing papers on "Complex adaptive system published in 2011"


Journal Article
Ning Nan1
TL;DR: A theoretical framework drawing on the concepts and the analytical tool of complex adaptive systems (CAS) theory is built that encodes a bottom-up IT use process into three interrelated elements: agents that consist of the basic entities of actions in an ITUse process, interactions that refer to the mutually adaptive behaviors of agents, and an environment that represents the social organizational contexts of IT use.
Abstract: Although information systems researchers have long recognized the possibility for collective- level information technology use patterns and outcomes to emerge from individual-level IT use behaviors, few have explored the key properties and mechanisms involved in this bottom-up IT use process. This paper seeks to build a theoretical framework drawing on the concepts and the analytical tool of complex adaptive systems (CAS) theory. The paper presents a CAS model of IT use that encodes a bottom-up IT use process into three interrelated elements: agents that consist of the basic entities of actions in an IT use process, interactions that refer to the mutually adaptive behaviors of agents, and an environment that represents the social organizational contexts of IT use. Agent-based modeling is introduced as the analytical tool for computationally representing and examining the CAS model of IT use. The operationability of the CAS model and the analytical tool are demonstrated through a theory-building exercise translating an interpretive case study of IT use to a specific version of the CAS model. While Orlikowski (1996) raised questions regarding the impacts of employee learning, IT flexibility, and workplace rigidity on IT-based organization transformation, the CAS model indicates that these factors in individual-level actions do not have a direct causal linkage with organizational- level IT use patterns and outcomes. This theory-building exercise manifests the intriguing nature of the bottom-up IT use process: collective-level IT use patterns and outcomes are the logical and yet often unintended or unforeseeable consequences of individual-level behaviors. The CAS model of IT use offers opportunities for expanding the theoretical and methodological scope of the IT use literature.

221 citations


Journal ArticleDOI
TL;DR: It was found that the VSM and the CAS approaches offer internally consistent and complementary insights to address issues of self‐organisation and adaptive management for sustainability improvement and some guidance is offered to both researchers and practitioners interested in using complex systems theories in action research‐oriented projects, regarding the usability and applicability of both approaches.
Abstract: – The purpose of this research is to explore core contributions from two different approaches to complexity management in organisations aiming to improve their sustainability,: the Viable Systems Model (VSM), and the Complex Adaptive Systems (CAS). It is proposed to perform this by summarising the main insights each approach offers to understanding organisational transformations aiming to improve sustainability; and by presenting examples of applied research on each case and reflecting on the learning emerging from them., – An action science approach was followed: the conceptual framework used in each case was first presented, which then illustrates its application through a case study; at the first one the VSM framework supports an organisational transformation towards sustainability in a community; the second one is a quantitative case study of intended greening of two firms in the supermarket industry, taken from a CAS perspective. The learning from each case study on how they support/explain organisational learning in transformations towards more sustainable organisations was illustrated., – It wase found that the VSM and the CAS approaches offer internally consistent and complementary insights to address issues of self‐organisation and adaptive management for sustainability improvement: while CAS explains empowerment of bottom‐up learning processes in organisations, VSM enables a learning context where self‐organised networks can co‐evolve for improved sustainability., – The main aspects of both theories and examples of their explanatory power to support learning in practical applications in organisations were introduced. The initial findings indicate that it will be worth studying in greater depth the contributions to organisational learning from both conceptual models and more widely comparing their applications and insights., – The paper offers some guidance to both researchers and practitioners interested in using complex systems theories in action research‐oriented projects, regarding the usability and applicability of both approaches., – It is considered that, by better understanding organisational ability to adapt and self‐regulate on crucial issues for sustainability, it may help to develop one path through the ongoing socio‐ecological crisis. While much has been written about sustainability initiatives and governance from conventional perspectives, much less is known about how a complex systems framework may help to address one's pressing sustainability needs. These issues from two innovative complexity approaches as well as the value of using them in action research were illustrated.

133 citations


Journal ArticleDOI
TL;DR: In this article, the authors outline a number of propositions that might serve as a basis for a theory of marketing systems, and draw on historical research into the evolution of exchange and on examples of markets and exchange practices from marketing, anthropology, sociology, and economics.
Abstract: Purpose – As specialisation takes root in human communities, the economics of scale and of diversity come into play. Scale leads to product markets, specialised firms, channels, and to industries. Diversity generates peasant markets, shopping malls, and business eco‐systems. These outcomes are all examples of marketing systems, and are typical of the patterns that emerge, grow, adapt and evolve in complex transaction flows. Marketing systems are multi‐level, path dependent, dynamic systems, embedded within a social matrix, and interacting with institutional and knowledge environments. The purpose of this paper is to outline a number of propositions that might serve as a basis for a theory of marketing systems.Design/methodology/approach – The paper draws on historical research into the evolution of exchange and on examples of markets and exchange practices from marketing, anthropology, sociology, and economics. It utilises results from complex adaptive systems theory, from the networks and markets literat...

128 citations


Journal ArticleDOI
TL;DR: Examining global health governance through the frame of complexity theory offers insight into the current dynamics of governance, and while providing a framework for making meaning of the whole, opens up ways of accessing this complexity through local points of engagement.
Abstract: The transition from international to global health reflects the rapid growth in the numbers and nature of stakeholders in health, as well as the constant change embodied in the process of globalisation itself. This paper argues that global health governance shares the characteristics of complex adaptive systems, with its multiple and diverse players, and their polyvalent and constantly evolving relationships, and rich and dynamic interactions. The sheer quantum of initiatives, the multiple networks through which stakeholders (re)configure their influence, the range of contexts in which development for health is played out – all compound the complexity of this system. This paper maps out the characteristics of complex adaptive systems as they apply to global health governance, linking them to developments in the past two decades, and the multiple responses to these changes. Examining global health governance through the frame of complexity theory offers insight into the current dynamics of governance, and ...

99 citations


Journal ArticleDOI
TL;DR: In this article, the relation of individual perceptual, conscious, and self-regulatory processes to the generation of requisite complexity in formal and informal leaders is examined and the implications of these issues for understanding leader adaptation and development are also discussed.
Abstract: This paper examines the relation of individual perceptual, conscious, and self-regulatory processes to the generation of requisite complexity in formal and informal leaders. Requisite complexity is a complex adaptive systems concept that pertains to the ability of a system to adjust to the requirements of a changing environment by achieving equivalent levels of complexity. We maintain that requisite complexity has both static and dynamic aspects that involve four domains (general, social, self, and affective complexity), with each being more or less important for leaders depending upon the task requirements they face. Dynamic complexity draws on these static components and also creates new aspects of complexity through the interaction of mental processes. The implications of these issues for understanding leader adaptation and development are also discussed.

95 citations


Journal ArticleDOI
TL;DR: In this paper, the authority boundaries are studied as mechanism design problems, where authority is allocated optimally to achieve social goals; as problems in positive political theory, because the authority distribution creates competitive interests; and as an institutional design problem, where the boundaries are maintained by safeguards.
Abstract: This article highlights political science's interest in the distribution of authority between federal and state governments. The authority boundaries are studied (a) as mechanism design problems, where authority is allocated optimally to achieve social goals; (b) as problems in positive political theory, because the authority distribution creates competitive interests; (c) as an institutional design problem, where the boundaries are maintained by safeguards; and (d) as a complex adaptive system, where the boundaries evolve in response to the interaction of diverse agents. The article concludes with a suggestion that as dynamic models of constitutional evolution develop, reflecting the bottom-up process and the responsiveness to the cultural community, federal constitutional design may transform from optimality studies to feasibility studies.

91 citations


Journal ArticleDOI
TL;DR: The health promotion field during the past 25 years has developed a mosaic of research results and intervention strategies, richly colored by a broad, integrative view of key dimension of individual health.
Abstract: The launch of the American Journal of Health Promotion blessed the field with a broad conceptual framework, now refined to include physical, emotional, social, spiritual, and intellectual dimensions of health. Throughout the years, this framework has become increasingly nuanced as research and practice have woven the rich fabric of what we know as health promotion today. However, although the multidimensionality of health promotion is firmly established, we still have lacked a shared understanding of the realities of multilevel influence and the value in multilevel intervention. The basic concept is well accepted, as illustrated, for example, by the Stokol’ social ecological model or the Bronfenbrenner developmental ecology model. Recently, there has been growing interest in systems thinking as a framework to guide science and strategy for a more comprehensive, integrated way of addressing individual, group, organization, community, and societal factors that influence health behavior. A serious shift to systems thinking for health promotion would require fundamental reworking of our usual ways of thinking, working, and evaluating. In 2001, the Institute of Medicine (IOM) produced a landmark report called Crossing the Quality Chasm, in which it endorsed the idea that health care systems are complex adaptive systems (CAS). As health promotion shifts to greater attention to multilevel influences and systems change strategy, CAS principles must be considered. The IOM report followed an important publication in 1998 and was accompanied by a series of publications in the British Medical Journal, which advocated the same emphasis on adopting the CAS lens to better understand how to improve and transform health systems. The IOM report was very important, as it was the first high-level consensus report that endorsed the CAS lens. What all of these publications emphasized is the dual nature of CAS: that they are at one and the same time complex and unpredictable, yet amenable to guided transformation by applying simple rules, as long as these rules are applied with the requisite flexibility to allow for adaptation processes. Health promotion issues are increasingly described as complex problems, deeply embedded within the fabric of society; consider, for example, obesity and chronic disease. Complex problems require intervention at many different system levels and the engagement of actors and organizations across levels ranging from the home, school, and work environments to communities, regions, and entire countries. This multi-level, multi-actor view is at the heart of systems thinking. Key features of complex systems that need to be taken into account in health promotion intervention and evaluation include the following: they are self-organizing and constantly adapting to change; they are driven by interactions between systems components and governed by feedback; and they are nonlinear and often unpredictable, with changes on one part of the system producing unexpected changes in other parts. As a consequence of these features, they often are program and policy resistant. This is not the way most of us in health promotion think about the needs and design of our interventions. A fundamental mind shift is needed, as well as major investments in theory, research methods, practice, and policy. Areas of particular importance for further development include interorganizational partnerships, networks, leadership, and integrated strategic communications. To summarize, the health promotion field during the past 25 years has developed a mosaic of research results and intervention strategies, richly colored by a broad, integrative view of key dimension of individual health. What is most needed now is a complementary view of how best to foster and support systems thinking for a more comprehensive, integrated, and dynamic framework for population approaches to health for all.

84 citations


Journal ArticleDOI
TL;DR: Using Complexity Science, population health outcomes can be viewed as an emergent property of CAS, which has numerous dynamic non-linear interactions among its interconnected sub-systems or agents.
Abstract: The mechanistic interpretation of reality can be traced to the influential work by Rene Descartes and Sir Isaac Newton. Their theories were able to accurately predict most physical phenomena relating to motion, optics and gravity. This paradigm had at least three principles and approaches: reductionism, linearity and hierarchy. These ideas appear to have influenced social scientists and the discourse on population health. In contrast, Complexity Science takes a more holistic view of systems. It views natural systems as being 'open', with fuzzy borders, constantly adapting to cope with pressures from the environment. These are called Complex Adaptive Systems (CAS). The sub-systems within it lack stable hierarchies, and the roles of agency keep changing. The interactions with the environment and among sub-systems are non-linear interactions and lead to self-organisation and emergent properties. Theoretical frameworks such as epi+demos+cracy and the ecosocial approach to health have implicitly used some of these concepts of interacting dynamic sub-systems. Using Complexity Science we can view population health outcomes as an emergent property of CAS, which has numerous dynamic non-linear interactions among its interconnected sub-systems or agents. In order to appreciate these sub-systems and determinants, one should acquire a basic knowledge of diverse disciplines and interact with experts from different disciplines. Strategies to improve health should be multi-pronged, and take into account the diversity of actors, determinants and contexts. The dynamic nature of the system requires that the interventions are constantly monitored to provide early feedback to a flexible system that takes quick corrections.

84 citations


Journal ArticleDOI
TL;DR: It is reported that, as long as the ratio of the two resources for allocation is biased enough, the formation of a typically sized herd can help the system to reach the balanced state.
Abstract: In order to survive, self-serving agents in various kinds of complex adaptive systems (CASs) must compete against others for sharing limited resources with biased or unbiased distribution by conducting strategic behaviors. This competition can globally result in the balance of resource allocation. As a result, most of the agents and species can survive well. However, it is a common belief that the formation of a herd in a CAS will cause excess volatility, which can ruin the balance of resource allocation in the CAS. Here this belief is challenged with the results obtained from a modeled resource-allocation system. Based on this system, we designed and conducted a series of computer-aided human experiments including herd behavior. We also performed agent-based simulations and theoretical analyses, in order to confirm the experimental observations and reveal the underlying mechanism. We report that, as long as the ratio of the two resources for allocation is biased enough, the formation of a typically sized herd can help the system to reach the balanced state. This resource ratio also serves as the critical point for a class of phase transition identified herein, which can be used to discover the role change of herd behavior, from a ruinous one to a helpful one. This work is also of value to some fields, ranging from management and social science, to ecology and evolution, and to physics.

81 citations


Journal ArticleDOI
TL;DR: Key elements and characteristics of complex adaptive systems (CAS) relevant to implementing clinical governance are identified, drawing on lessons from quality improvement programmes and the use of informatics in primary care.
Abstract: Objective To identify key elements and characteristics of complex adaptive systems (CAS) relevant to implementing clinical governance, drawing on lessons from quality improvement programmes and the use of informatics in primary care. Method The research strategy includes a literature review to develop theoretical models of clinical governance of quality improvement in primary care organisations (PCOs) and a survey of PCOs. Results Complex adaptive system theories are a valuable tool to help make sense of natural phenomena, which include human responses to problem solving within the sampled PCOs. The research commenced with a survey; 76% (n16) of respondents preferred to support the implementation of clinical governance initiatives guided by outputs from general practice electronic health records. There was considerable variation in the way in which consultation data was captured, recorded and organised. Incentivised information sharing led to consensus on coding policies and models of data recording ahead of national contractual requirements. Informatics was acknowledged as a mechanism to link electronic health record outputs, quality improvement and resources. Investment in informatics was identified as a development priority in order to embed clinical governance principles in practice. Conclusions Complex adaptive system theory usefully describes evolutionary change processes, providing insight into how the origins of quality assurance were predicated on rational reductionism and linearity. New forms of governance do not neutralise previous models, but add further dimensions to them. Clinical governance models have moved from deterministic and 'objective' factors to incorporate cultural aspects with feedback about quality enabled by informatics. The socio-technical lessons highlighted should inform healthcare management.

70 citations


Journal ArticleDOI
TL;DR: This article presents five trade-offs identified to date that define boundary conditions on all macrocognitive work systems and illustrates how the known empirical generalizations about the performance of human work systems can be systematically organized by theTrade-offs.
Abstract: Articulating the laws of cognitive work has been a continuing theme in this department. A number of the articles represent an effort to move toward a unified theory of "macrocognitive work systems." These are complex adaptive systems designed to support near-continuous interdependencies among humans and intelligent machines to carry out functions such as sensemaking, replanning, mental projection to the future, and coordination. The effort to identify empirical generalizations and use them to construct a formal theory has led us to the identification of a number of fundamental trade-offs that place boundary conditions on all macrocognitive work systems. This article presents five trade-offs identified to date that define these boundary conditions. It also illustrates how the known empirical generalizations about the performance of human work systems can be systematically organized by the trade-offs.

Journal ArticleDOI
TL;DR: In this paper, the authors reflect on their own experience of an informal mentoring process in an academic context and find existing models inadequately describe their experience and propose a complex adaptive systems (CAS) perspective of the mentoring relationship.
Abstract: Mentoring theory and practice has evolved significantly during the past 40 years. Early mentoring models were characterized by the top-down flow of information and benefits to the protege. This framework was reconceptualized as a reciprocal model when scholars realized mentoring was a mutually beneficial process. Recently, in response to rapidly changing organizational and social environments, scholars have explored other models of mentoring such as developmental networks. However, as we, the authors, reflect on our own experience of an informal mentoring process in an academic context we find existing models inadequately describe our experience. The model that best fits our story is a complex adaptive systems (CAS) perspective of the mentoring relationship, and we offer this lens to reconfigure current models.

01 Jun 2011
TL;DR: It is argued that linear, categorical descriptions of classroom processes and interactions do not sufficiently explain the complex nature of classrooms, and cannot account for how classroom change occurs (or does not occur), over time.
Abstract: In this article, we describe and model the language classroom as a complex adaptive system (see Logan & Schumann, 2005). We argue that linear, categorical descriptions of classroom processes and interactions do not sufficiently explain the complex nature of classrooms, and cannot account for how classroom change occurs (or does not occur), over time. A relational model of classrooms is proposed which focuses on the relations between different elements (physical, environmental, cognitive, social) in the classroom and on how their interaction is crucial in understanding and describing classroom action.

Journal ArticleDOI
TL;DR: It is argued that the DPE framework helps to explain many complex phenomena, including perpetual novelty, modularity, scale-free networks and criticality, in particular, self-organized criticality and the adaptive cycle.
Abstract: Understanding the origins of complexity is a key challenge in many sciences. Although networks are known to underlie most systems, showing how they contribute to well-known phenomena remains an issue. Here, we show that recurrent phase transitions in network connectivity underlie emergent phenomena in many systems. We identify properties that are typical of systems in different connectivity phases, as well as characteristics commonly associated with the phase transitions. We synthesize these common features into a common framework, which we term dual-phase evolution (DPE). Using this framework, we review the literature from several disciplines to show that recurrent connectivity phase transitions underlie the complex properties of many biological, physical and human systems. We argue that the DPE framework helps to explain many complex phenomena, including perpetual novelty, modularity, scale-free networks and criticality. Our review concludes with a discussion of the way DPE relates to other frameworks, in particular, self-organized criticality and the adaptive cycle.

Journal ArticleDOI
TL;DR: A pilot study of a problem-based learning strategy guided by principles of complexity science in a community clinical nursing course results were higher than expected levels of student satisfaction, increased breadth and analysis of complex data, acknowledgment of community as complex adaptive systems, and overall higher level thinking skills than in previous years.
Abstract: Successful nurses function effectively with adaptability, improvability, and interconnectedness, and can see emerging and unpredictable complex problems. Preparing new nurses for complexity requires a significant change in prevalent but dated nursing education models for rising graduates. The science of complexity coupled with problem-based learning and peer review contributes a feasible framework for a constructivist learning environment to examine real-time systems data; explore uncertainty, inherent patterns, and ambiguity; and develop skills for unstructured problem solving. This article describes a pilot study of a problem-based learning strategy guided by principles of complexity science in a community clinical nursing course. Thirty-five senior nursing students participated during a 3-year period. Assessments included peer review, a final project paper, reflection, and a satisfaction survey. Results were higher than expected levels of student satisfaction, increased breadth and analysis of complex data, acknowledgment of community as complex adaptive systems, and overall higher level thinking skills than in previous years.

Posted Content
TL;DR: This work investigates an abstract conceptualisation of Digital Ecosystems from a computer science perspective and provides a conceptual framework for the cross pollination of ideas, concepts and understanding between different classes of ecosystems through the universally applicable principles of Complex Adaptive System modelling.
Abstract: We investigate an abstract conceptualisation of DigitalEcosystems from a computer science perspective. We then provide a conceptual framework for the cross pollination of ideas, concepts and understanding between different classes of ecosystems through the universally applicable principles of Complex Adaptive Systems (CAS) modelling. A framework to assist the cross-disciplinary collaboration of research into Digital Ecosystems, including Digital BusinessEcosystems (DBEs) and Digital Knowledge Ecosystems (DKEs). So, we have defined the key steps towards a theoretical framework for Digital Ecosystems, that is compatible with the diverse theoretical views prevalent. Therefore, a theoretical edifice that can unify the diverse efforts within Digital Ecosystems research.

Journal ArticleDOI
TL;DR: Vigorous and important directions in the study of ecosystems today include a growing focus on human-dominated landscapes and development of the concept of ecosystem services for human resource supply and well-being.
Abstract: Contents Summary 21 I. An organizational concept 22 II. An imperfect marriage 22 III. A type of complex adaptive system? 25 IV. A component of social–ecological systems 28 V. Conclusions and future research 30 Acknowledgements 31 References 32 Summary The ecosystem has served as a central organizational concept in ecology for nearly a half century and continues to evolve. As a level in the biotic hierarchy, ecosystems are often viewed as ecological communities integrated with their abiotic environments. This has always been imperfect because of a mismatch of scales between communities and ecosystem processes as they are made operational for field study. Complexity theory has long been forecasted to provide a renewed foundation for ecosystem theory but has been slow to do so. Partly this has arisen from a difficulty in translating theoretical tenets into operational terms for testing in field studies. Ecosystem science has become an important applied science for studying global change and human environmental impacts. Vigorous and important directions in the study of ecosystems today include a growing focus on human-dominated landscapes and development of the concept of ecosystem services for human resource supply and well-being. Today, terrestrial ecosystems are viewed less as well-defined entities or as a level in the biotic hierarchy. Instead, ecosystem processes are being increasingly viewed as the elements in a hierarchy. These occur alongside landscape processes and socioeconomic processes, which combine to form coupled social–ecological systems across a range of scales.

Journal ArticleDOI
TL;DR: The definitions of the most important concepts such as emergence and self-organisation from an engineer's perspective are reviewed, and different types of nature-inspired technology are analyzed.
Abstract: Complexity science has seen increasing interest in the recent years. Many engineers have discovered that traditional methods come to their limits when coping with complex adaptive systems or autonomous agents. To find alternatives, complexity science can be applied to engineering, resulting in a quickly growing field, referred to as complexity engineering. Most current efforts come either from scientists who are interested in bio-inspired methods and working in computer science or mobile robots, or they come from the area of systems engineering. This article reviews the definitions of the most important concepts such as emergence and self-organisation from an engineer's perspective, and analyses different types of nature-inspired technology. This is the first part of a set of two-articles on this topic; the second one provides a survey of currently existing approaches to complexity engineering, identifies challenges and gives directions for further research.

23 Sep 2011
TL;DR: In this paper, the CUSD2009 Team of approximately 200 students and faculty members, which designed and built a solar house over a 2-year period for an international competition with 19 other teams sponsored by the U.S. Department of Energy, used a multilevel approach consisting of coding the data through the lenses of two models and a theory.
Abstract: This research paper follows the theoretical paper, Group Development: A Complex Adaptive Systems Perspective (Edson, 2010) presented at the 54th Meeting of the International Society for the Systems Sciences in Waterloo, Canada. This case study explored resilience in a project team through analysis of group development from a complex adaptive systems perspective. Three research questions focused on the team’s consciousness of a need to change under adversity, its response through adaptive action, and its potential for innovation through creative destruction. The study used flexible design and mixed methods by applying grounded theory coding techniques to understand a retrospective case study. The subject was the CUSD2009 Team of approximately 200 students and faculty members, which designed and built a solar house over a 2-year period for an international competition with 19 other teams sponsored by the U.S. Department of Energy. Data analysis used a multilevel approach consisting of coding the data through the lenses of two models and a theory. Relationships between models of group development, the complex adaptive cycle, and complex adaptive systems theory were established theoretically and empirically. Results of the 3 research questions indicated that the team exhibited agency through the following: (a) collective consciousness of a need for change to maintain the team’s function toward the project goals, (b) collective action to make necessary changes, and (c) emergence of innovation through creative destruction entailing renegotiation of group norms in response to an adversity. The multilevel analysis culminated in an integrated systems perspective with conclusions about resilience in project teams, specifically the role of environmental feedback. Implications for future research using complex adaptive systems as a theoretical foundation for studying group development and resilience include organizational culture, inflection points, nested adaptive cycles, emergence of leadership, and emergence of innovation. This research contributes a deeper understanding of project team resilience in organizational systems such as companies, non-profits, governmental, and non-governmental entities by revealing the importance of environmental feedback and organizational learning to build adaptive capacity.


Journal ArticleDOI
TL;DR: A survey of the currently existing approaches to complexity engineering is provided and challenges ahead are indicated.
Abstract: Complexity science has seen increasing interest in the recent years. Many engineers have discovered that traditional methods come to their limits when coping with complex adaptive systems or autonomous agents. To find alternatives, complexity science can be applied to engineering, resulting in a quickly growing field, referred to as complexity engineering. Most current efforts come either from scientists who are interested in bio-inspired methods and working in computer science or mobile robots, or they come from the area of systems engineering. This article is the second part of a set of two articles on this topic; the first one reviewed the definitions of the most important concepts such as emergence and self-organisation from an engineer's perspective, and analysed different types of nature-inspired technology. This article provides a survey of the currently existing approaches to complexity engineering. In the end, challenges ahead are indicated.

Journal ArticleDOI
TL;DR: In this paper, it is argued that the macroeconomic system and its components are complex adaptive systems and that this complexity must not be assumed away through the imposition of simplistic assumptions made for analytical convenience.
Abstract: In this article, the goal is to offer a new research agenda for evolutionary macroeconomics. The article commences with a broad review of the main ideas in the history of thought concerning the determinants of economic growth and an introduction to the evolutionary perspective. This is followed by a selective review of recent evolutionary approaches to macroeconomics. These approaches are found to be somewhat disconnected. It is argued that the ‘micro-meso-macro’ approach to economic evolution is capable of resolving this problem by offering an analytical framework in which macroeconomics can be built upon ‘meso-foundations’, not micro-foundations, as asserted in the mainstream. It is also stressed that the economic system and its components are complex adaptive systems and that this complexity must not be assumed away through the imposition of simplistic assumptions made for analytical convenience. It is explained that complex economic systems are, at base, energetic in character but differ from biological complex systems in the way that they collect, store and apply knowledge. It is argued that a focus upon stocks and flows of energy and knowledge in complex economic systems can yield an appropriate analytical framework for macroeconomics. It is explained how such a framework can be connected with key insights of both Schumpeter and Keynes that have been eliminated in modern macroeconomics. A macroeconomic framework that cannot be operationalized empirically is of limited usefulness so, in the last part of the article, an appropriate methodology for evolutionary macroeconomics is discussed.

Book ChapterDOI
01 Oct 2011
Abstract: Complex adaptive systems are the source of much intra-organizational conflict that will not be managed, let alone resolved. To foster learning, adaptation, and evolution in the workplace, organizations should capitalize on its functions and dysfunctions with mindfulness, improvisation, and reconfiguration.

Journal ArticleDOI
TL;DR: The cluster is presented as a complex adaptive system (CAS) that experiences self-organization through four critical features: landscape design, positive feedback, boundary constraints, and novel outcomes.

Journal ArticleDOI
James K. Hazy1
21 Jun 2011
TL;DR: In this article, the authors develop theory relating the process of leadership to the social processes that sustain an organization as a complex adaptive system, and examine how three distinct but complementary mechanisms interact to form a leadership metacapability that evolves in organisations.
Abstract: This article develops theory relating the process of leadership to the social processes that sustain an organisation as a complex adaptive system. It interprets current theory in a new light and describes dynamical interactions that relate mechanisms of leadership to the organisational capabilities that have succeeded in the environment. It examines how three distinct but complementary mechanisms interact to form a leadership metacapability that evolves in organisations to positively impact both performance and adaptation.

Journal Article
TL;DR: In this article, the authors propose a unified framework for the development, comparison, communication and validation of models across different scientific domains using agent-based and complex network-based modeling approaches.
Abstract: Literature on the modeling and simulation of complex adaptive systems (cas) has primarily advanced vertically in different scientific domains with scientists developing a variety of domain-specific approaches and applications. However, while cas researchers are inher-ently interested in an interdisciplinary comparison of models, to the best of our knowledge, there is currently no single unified framework for facilitating the development, comparison, communication and validation of models across different scientific domains. In this thesis, we propose first steps towards such a unified framework using a combination of agent-based and complex network-based modeling approaches and guidelines formulated in the form of a set of four levels of usage, which allow multidisciplinary researchers to adopt a suitable framework level on the basis of available data types, their research study objectives and expected outcomes, thus allowing them to better plan and conduct their respective re-search case studies.

Book ChapterDOI
01 Jan 2011
TL;DR: The unification consists of five basic trade-offs that bound the performance of all human adaptive systems, and an architecture for polycentric control or governance based on regulating margin of maneuver to be able to dynamically balance the conflicts, risks and pressures that arise from the fundamental trade-off.
Abstract: Investigations into complex adaptive systems (CAS) have identified multiple trade-offs that place hard limits on the behavior of adaptive systems of any type. Complexity theory continues to search for a formalization that can unify these trade-offs around one or a few fundamental ones, and explain how observed tradeoffs are derived from the most basic ones (Alderson and Doyle, 2010). Resilience Engineering (RE) also arose from the recognition that basic trade-offs placed hard limits on the safety performance of teams and organizations in the context of pressures for systems to be “faster, better, cheaper” (Woods, 2006; Hollnagel, 2009). Combining the results from CAS on physical complex systems with the results from RE on high risk, high consequence human designed systems leads to a potential unification. The unification consists of (a) five basic trade-offs that bound the performance of all human adaptive systems (Hoffman and Woods, 2011), and (b) an architecture for polycentric control or governance based on regulating margin of maneuver to be able to dynamically balance the conflicts, risks and pressures that arise from the fundamental trade-offs.

Book ChapterDOI
10 Nov 2011
TL;DR: In this article, the authors discuss the emerging network science approach to the study of complex adaptive systems and applies tools derived from statistical physics to the analysis of tourism destinations, and compare the parameters of these networks to networks from the literature and to randomly created networks.
Abstract: This chapter discusses the emerging network science approach to the study of complex adaptive systems and applies tools derived from statistical physics to the analysis of tourism destinations. The authors provide a brief history of network science and the characteristics of a network as well as different models such as small world and scale free networks, and dynamic properties such as resilience and information diffusion. The Italian resort island of Elba is used as a case study allowing comparison of the communication network of tourist organizations and the virtual network formed by the websites of these organizations. The study compares the parameters of these networks to networks from the literature and to randomly created networks. The analyses include computer simulations to assess the dynamic properties of these networks. The results indicate that the Elba tourism network has a low degree of collaboration between members. These findings provide a quantitative measure of network performance. In general, the application of network science to the study of social systems offers opportunities for better management of tourism destinations and complex social systems.

Journal ArticleDOI
TL;DR: In this article, the authors studied welfare issues associated with the management of a human-nature complex adaptive system with a threshold and a stochastic driver, and showed that the choice of control method depends in a highly non-linear way on biodiversity characteristics and that the socially optimal outcome may not be reachable using price instruments.

Journal Article
TL;DR: The paper explores whether this model can be used canonically and does so in the context of axiomatic hurdles that must be overcome if a practical mathematical theory of human organizing is to be realized.
Abstract: This paper presents a complexity science informed theory to describe how organizing forms emerge and foster innovation. The theory explores the bidirectional linkages between fine-grained interactions among human beings in a complex adaptive system and the emergent coarse-grained properties that characterize qualitatively distinct and yet stable organizing forms in social systems. By exploiting a mathematical foundation that has been successfully employed in analogous cases in the natural sciences, it opens the door to a rigorous theory of performance and adaptation in human systems by relating changing local rules of interaction to qualitative changes in emerging organizing forms. This process is mediated by evolving models of the system in the environment developed and shared among individuals. Finally, the paper explores whether this model can be used canonically and does so in the context of axiomatic hurdles that must be overcome if a practical mathematical theory of human organizing is to be realized.