Showing papers on "Complex adaptive system published in 2010"
TL;DR: A brief introduction to ABMS is provided, the main concepts and foundations are illustrated, some recent applications across a variety of disciplines are discussed, and methods and toolkits for developing agent models are identified.
Abstract: Agent-based modelling and simulation (ABMS) is a relatively new approach to modelling systems composed of autonomous, interacting agents. Agent-based modelling is a way to model the dynamics of complex systems and complex adaptive systems. Such systems often self-organize themselves and create emergent order. Agent-based models also include models of behaviour (human or otherwise) and are used to observe the collective effects of agent behaviours and interactions. The development of agent modelling tools, the availability of micro-data, and advances in computation have made possible a growing number of agent-based applications across a variety of domains and disciplines. This article provides a brief introduction to ABMS, illustrates the main concepts and foundations, discusses some recent applications across a variety of disciplines, and identifies methods and toolkits for developing agent models.
1,597 citations
TL;DR: An eight-dimensional model specifically designed to address the sociotechnical challenges involved in design, development, implementation, use and evaluation of HIT within complex adaptive healthcare systems is introduced.
Abstract: Conceptual models have been developed to address challenges inherent in studying health information technology (HIT). This chapter introduces an 8-dimensional model specifically designed to address the socio-technical challenges involved in design, development, implementation, use, and evaluation of HIT within complex adaptive healthcare systems. The 8 dimensions are not independent, sequential, or hierarchical, but rather are interdependent and interrelated concepts similar to compositions of other complex adaptive systems. Hardware and software computing infrastructure refers to equipment and software used to power, support, and operate clinical applications and devices. Clinical content refers to textual or numeric data and images that constitute the “language” of clinical applications. The human computer interface includes all aspects of the computer that users can see, touch, or hear as they interact with it. People refers to everyone who interacts in some way with the system, from developers to end-users, including potential patient-users. Workflow and communication are the processes or steps involved in assuring that patient care tasks are carried out effectively. Two additional dimensions of the model are internal organizational features (e.g., environment, policies, procedures, and culture) and external rules and regulations, both of which may facilitate or constrain many aspects of the preceding dimensions. The final dimension is measurement and monitoring, which refers to the process of measuring and evaluating both intended and unintended consequences of HIT implementation and use. We illustrate how our model has been successfully applied in real-world complex adaptive settings to understand and improve HIT applications at various stages of development and implementation.
579 citations
Book•
01 Nov 2010
TL;DR: Scott Page explains how diversity underpins system level robustness, allowing for multiple responses to external shocks and internal adaptations; how it provides the seeds for large events by creating outliers that fuel tipping points; and how it drives novelty and innovation.
Abstract: This book provides an introduction to the role of diversity in complex adaptive systems. A complex system--such as an economy or a tropical ecosystem--consists of interacting adaptive entities that produce dynamic patterns and structures. Diversity plays a different role in a complex system than it does in an equilibrium system, where it often merely produces variation around the mean for performance measures. In complex adaptive systems, diversity makes fundamental contributions to system performance. Scott Page gives a concise primer on how diversity happens, how it is maintained, and how it affects complex systems. He explains how diversity underpins system level robustness, allowing for multiple responses to external shocks and internal adaptations; how it provides the seeds for large events by creating outliers that fuel tipping points; and how it drives novelty and innovation. Page looks at the different kinds of diversity--variations within and across types, and distinct community compositions and interaction structures--and covers the evolution of diversity within complex systems and the factors that determine the amount of maintained diversity within a system.Provides a concise and accessible introduction Shows how diversity underpins robustness and fuels tipping points Covers all types of diversity The essential primer on diversity in complex adaptive systems
482 citations
TL;DR: In this paper, the authors apply this approach to sustainable farming by conceptualizing a farm as being part of a set of systems spanning several spatial scales and including agro-ecological, economic and political-social domains.
Abstract: Research on sustainability in agriculture often focuses on reducing the environmental impacts of production systems. However, environmentally friendly production methods may not be sufficient to ensure the long-term economic and social sustainability of a farm. Taking a systems approach to sustainable farming, we turn to resilience thinking with its focus on the interdependence of social and ecological systems. We apply this approach to farming by conceptualizing a farm as being part of a set of systems spanning several spatial scales and including agro-ecological, economic and political-social domains. These subsystems interact and are subjected to their own complex dynamics. Within such a complex adaptive system, farm sustainability can only be achieved through adaptability and change. To be ready for the inevitable periods of turbulent change, a farmer needs to retain diversity and redundancy to ensure adaptability. Resilience is thus more likely to emerge when farmers hone the capacity to transform th...
365 citations
TL;DR: In this paper, a review of the literature and analysis of the understanding of the subject of ecosystem based management is presented, and it has been concluded that to understand marine ecosystem-based management one must consider ecosystems as complex adaptive systems which can show changes at higher levels from actions and processes occurring at lower levels.
340 citations
TL;DR: A qualitative study examining the implementation of health promoting schools programs in primary schools in Sydney, Australia confirmed that schools do exhibit most, but not all of the characteristics of social complex adaptive systems, and exhibit significant differences with artificial and natural systems.
252 citations
TL;DR: In this article, a conceptual framework for the analysis of social learning processes in sustainability appraisals is presented, and an empirical application of the framework by use of data obtained from three energy and natural resource management case studies around Europe.
242 citations
Book•
31 Aug 2010
TL;DR: The economic crisis is also a crisis for economic theory as mentioned in this paper, which suggests a way of analysing the economy which takes this point of view and suggests that the economy should be considered as a complex adaptive system in which the agents constantly react to, influence and are influenced by, the other individuals in the economy.
Abstract: The economic crisis is also a crisis for economic theory. Most analyses of the evolution of the crisis invoke three themes, contagion, networks and trust, yet none of these play a major role in standard macroeconomic models. What is needed is a theory in which these aspects are central. The direct interaction between individuals, firms and banks does not simply produce imperfections in the functioning of the economy but is the very basis of the functioning of a modern economy. This book suggests a way of analysing the economy which takes this point of view. The economy should be considered as a complex adaptive system in which the agents constantly react to, influence and are influenced by, the other individuals in the economy. In such systems which are familiar from statistical physics and biology for example, the behaviour of the aggregate cannot be deduced from the behaviour of the average, or "representative" individual. Just as the organised activity of an ants' nest cannot be understood from the behaviour of a "representative ant" so macroeconomic phenomena should not be assimilated to those associated with the "representative agent". This book provides examples where this can clearly be seen. The examples range from Schelling's model of segregation, to contributions to public goods, the evolution of buyer seller relations in fish markets, to financial models based on the foraging behaviour of ants. The message of the book is that coordination rather than efficiency is the central problem in economics. How do the myriads of individual choices and decisions come to be coordinated? How does the economy or a market, "self organise" and how does this sometimes result in major upheavals, or to use the phrase from physics, "phase transitions"? The sort of system described in this book is not in equilibrium in the standard sense, it is constantly changing and moving from state to state and its very structure is always being modified. The economy is not a ship sailing on a well-defined trajectory which occasionally gets knocked off course. It is more like the slime described in the book "emergence", constantly reorganising itself so as to slide collectively in directions which are neither understood nor necessarily desired by its components.
214 citations
Book•
01 Jan 2010
TL;DR: A collection of the most important articles on the subject of ecological resilience is presented in this paper, which is an invaluable resource for students and scholars in ecology, wildlife ecology, conservation biology, sustainability, environmental science, public policy, and related fields.
Abstract: This title presents the evolution of resilience theory in seminal papers and commentary. Ecological resilience provides a theoretical foundation for understanding how complex systems adapt to and recover from localized disturbances like hurricanes, fires, pest outbreaks, and floods, as well as large-scale perturbations such as climate change. Ecologists have developed resilience theory over the past three decades in an effort to explain surprising and nonlinear dynamics of complex adaptive systems. Resilience theory is especially important to environmental scientists for its role in underpinning adaptive management approaches to ecosystem and resource management. "Foundations of Ecological Resilience" is a collection of the most important articles on the subject of ecological resilience - those writings that have defined and developed basic concepts in the field and help explain its importance and meaning for scientists and researchers. The book's three sections cover articles that have shaped or defined the concepts and theories of resilience, including key papers that broke new conceptual ground and contributed novel ideas to the field; examples that demonstrate ecological resilience in a range of ecosystems; and, articles that present practical methods for understanding and managing nonlinear ecosystem dynamics. "Foundations of Ecological Resilience" is an important contribution to our collective understanding of resilience and an invaluable resource for students and scholars in ecology, wildlife ecology, conservation biology, sustainability, environmental science, public policy, and related fields.
181 citations
TL;DR: A relationship-centered practice development approach to understand practice and to aid in fostering practice development to advance key attributes of primary care that include access to first-contact care, comprehensive care, coordination of care, and a personal relationship over time is presented.
Abstract: PURPOSE Numerous primary care practice development efforts, many related to the patient-centered medical home (PCMH), are emerging across the United States with few guides available to inform them. This article presents a relation- ship-centered practice development approach to understand practice and to aid in fostering practice development to advance key attributes of primary care that include access to fi rst-contact care, comprehensive care, coordination of care, and a personal relationship over time. METHODS Informed by complexity theory and relational theories of organiza- tional learning, we built on discoveries from the American Academy of Family Physicians' National Demonstration Project (NDP) and 15 years of research to understand and improve primary care practice. RESULTS Primary care practices can fruitfully be understood as complex adaptive systems consisting of a core (a practice's key resources, organizational structure, and functional processes), adaptive reserve (practice features that enhance resil- ience, such as relationships), and attentiveness to the local environment. The effectiveness of these attributes represents the practice's internal capability. With adequate motivation, healthy, thriving practices advance along a pathway of slow, continuous developmental change with occasional rapid periods of trans- formation as they evolve better fi ts with their environment. Practice development is enhanced through systematically using strategies that involve setting direction and boundaries, implementing sensing systems, focusing on creative tensions, and fostering learning conversations. CONCLUSIONS Successful practice development begins with changes that strengthen practices' core, build adaptive reserve, and expand attentiveness to the local environment. Development progresses toward transformation through enhancing primary care attributes.
173 citations
TL;DR: There are seven tools policymakers should follow to create adaptive policies based on over a dozen case studies on public policies relating to agriculture and water resources management in Canada and India, which are elaborates on as a pragmatic guide for policymakers who find themselves working in highly complex, dynamic, and uncertain settings.
TL;DR: In this article, the authors describe a self-organisation approach to curriculum based on complex adaptive systems, where knowledge is not constructed separately in the mind of the knower, but, rather, it emerges; it is co-created during the exchange in an authentic recursive transactive process.
Abstract: CONTEXT The world of medical education is more complex than ever and there seems to be no end in sight. Complexity science is particularly relevant as medical education embraces a movement towards more authentic curricula focusing on integration, interactive small-group learning, and early and sustained clinical and community experiences. DISCUSSION A medical school as a whole, and the expression of its curriculum through the interactions, exchanges and learning that take place within and outside of it, is a complex system. Complexity science, a derivative of the natural sciences, is the study of the dynamics, conditions and consequences of interactions. It addresses the nature of the conditions favourable to change and transformation (learning). CONCLUSIONS The core process of complexity, self-organisation, requires a system that is open and far from equilibrium, with ill-defined boundaries and a large number of non-linear interactions involving short-loop feedback. In such a system, knowledge does not exist objectively 'out there'; rather, it exists as a result of the exchange between participants, an action that becomes knowing. Understanding is placed between participants rather than being contained in one or the other. Knowledge is not constructed separately in the mind of the knower, but, rather, it emerges; it is co-created during the exchange in an authentic recursive transactive process. Learning and knowing become adaptive responses to continuously evolving circumstances. An approach to curriculum based on self-organisation is characterised as rich, recursive, relational and rigorous and it illuminates how a curriculum can be understood as a complex adaptive system. The perspective of complexity applied to medical education broadens and enriches research questions relevant to health professions education. It focuses our attention onto how we are together as human beings. How we respond to and frame the issues of learning and understanding that challenge contemporary medicine and, by extension, medical education, in a complex and rapidly changing world can have profound effects on the preparedness of tomorrow's health professionals and their impact on society.
TL;DR: In this paper, a study of California's water planning and management process, known as CALFED, offers insights into governance strategies that can deal with adaptive management of environmental resources in ways that conventional bureaucratic procedures cannot.
Abstract: A study of California’s water planning and management process, known as CALFED, offers insights into governance strategies that can deal with adaptive management of environmental resources in ways that conventional bureaucratic procedures cannot. CALFED created an informal policy-making system, engaging multiple agencies and stakeholders. The research is built on data from 5 years of field work that included interviews with participants, review of documents, and observation of meetings. We argue that CALFED can be seen as a self-organizing complex adaptive network (CAN) in which interactions were generally guided by collaborative heuristics. The case demonstrates several innovative governance practices, including new practices and norms for interactions among the agents, a distributed structure of information and decision making, a nonlinear planning method, self-organizing system behavior, and adaptation. An example of a resulting policy innovation, a method to provide real-time environmental use of water while protecting a reliable supply of water for agricultural and urban interests, is described. We outline how ideas about complex adaptive network governance differ from ideas about traditional governance. These differences result in ongoing tension and turbulence as they do for other self-organizing governance processes that operate in a context of traditional governance.
TL;DR: In this article, the authors explored the use of complex adaptive systems theory in development policy analysis using a case study drawn from recent events in Uganda, where the changes that took place in the farming system in Soroti district during an outbreak of African cassava mosaic virus disease (ACMVD) and the subsequent decline in cassava production - the main staple food in the area.
Abstract: This paper explores the use of complex adaptive systems theory in development policy analysis using a case study drawn from recent events in Uganda. It documents the changes that took place in the farming system in Soroti district during an outbreak of African cassava mosaic virus disease (ACMVD) and the subsequent decline in cassava production - the main staple food in the area. Resultant adaptation impacts are analysed across cropping, biological, economic and social systems each of which operate as an interlinked sub-system. The policy implications of this story suggest a policy agenda that recognises adaptation capacity as the life blood of complex adaptive systems. Since these types of systems are found in all realms of human activity, it follows that strengthening this capacity is a key developmental priority that requires linking together new configurations of actors and resources to tackle an ever-changing set of contexts.
TL;DR: The aim of this article is to bring to the attention that model design is an essential as well as an integral part of system design, and presents a constructive approach to systematically design, build and test models of CI systems.
TL;DR: It is argued here that conceptualizing schools and districts as complex adaptive systems, composed of many networked parts that give rise to emergent patterns through their interactions, holds promise for understanding such important problems.
Abstract: Education researchers have struggled for decades with questions such as “why are troubled schools so difficult to improve?” or “why is the achievement gap so hard to close?” We argue here that conceptualizing schools and districts as complex adaptive systems, composed of many networked parts that give rise to emergent patterns through their interactions ( 1 ), holds promise for understanding such important problems. Although there has been considerable research on the use of complex systems ideas and methods to help students learn science content ( 2 ), only recently have researchers begun to apply these tools to issues of educational policy.
01 Jan 2010
TL;DR: This research survey highlights that most of the existing interdependence modeling strategies are not competing but rather complementary approaches, which can provide a vehicle for immediate innovative studies on coupled infrastructures, such as stochastic interDependence, cascading failures across systems, and the establishment of risk mitigation principles.
Abstract: National security, economic prosperity, and the quality of life of today’s societies depend on the continuous and reliable operation of interdependent infrastructures. Models to capture the performance and operation of these systems have been developed to support planning, maintenance, and retrofit decision making from multiple view points, including infrastructure owners or investors, private and public users, and government entities that ensure reliability, economic vitality and security. The study of interdependent infrastructures is challenging due to heterogeneous quality and insufficient data availability and the need to account for their spatial and temporal aspects of complex supply-demand operation. Research and implementation studies have attempted to address interdependence modeling through various techniques, such as Agent Based simulation, Input- Output Inoperability, system reliability theory, nonlinear dynamics, and graph theory. These studies are mainly targeted at understanding infrastructure behavior and response to disruptions through single modeling techniques. However, hybrid modeling techniques, multi-scale analyses, and other realizable innovative approaches are lacking, in part because few studies have characterized existing models into a single source to provide a current state of the field, elucidate connections across existing studies, and synthesize a directive for future research. This chapter introduces a conceptualization of current research that integrates the multiple ideas in the field of infrastructure interdependencies into a unified hierarchical structure that navigates through research advances from early papers in the1980’s to date. The body of knowledge is categorized according to several attributes identified in the field, such as mathematical method, modeling objective, scale of analysis, quality and quantity of input data, targeted discipline, and end user type. The hierarchical conceptualization approach synthesizes available data and is expected to ease the research and application process of interdependencies concepts by finding differences and commonalities in data collection, analyses techniques, and desired outputs. This research survey highlights that most of the existing interdependence modeling strategies are not competing but rather complementary approaches, which can provide a vehicle for immediate innovative studies on coupled infrastructures, such as stochastic interdependence, cascading failures across systems, and the establishment of risk mitigation principles. New linkages across existing research can facilitate implementation and dissemination of results, inform areas of data collection, enable benchmark models for validation predictions and model comparisons, and point to long term broader and emergent unresolved research issues in infrastructure interdependence research, possibly including smart technologies, bio-inspiration, sustainability, scalability of analysis algorithms, and dimension reduction of network abstractions.
TL;DR: A strategy for the development of interactive media scenarios to help communicate uncertainties and complexities in coupled human and natural systems, and is suitable for participatory work in live settings as well as on-line, from a local to a global scale.
01 Jan 2010
TL;DR: In this paper, the resilience approach is used as the basis for a reconceptualization of the traditional notions of natural resources and management, and the main elements of this approach include attention to drivers and change processes, treating social-ecological systems as complex adaptive systems characterized by cycles and uncertainty.
Abstract: Conventional notions of 'natural resources' and 'management' are problematic because of their history, and they need to be reconceptualised. The term 'resource' carries a sense of 'free goods', human-centric use and com - modification of nature; it can be revised to include the protection of ecosystem services for human well-being. The term 'management' implies domination of nature, efficiency, simplification, and expert-knows-best, command-and-control approaches. It similarly needs a makeover to emphasize stewardship, pluralism, collaboration, partnerships and adaptive governance, balancing efficiency objec - tives against ecological and social objectives. Resilience is a recurring theme in discussions of shifting perspectives in resource management, and I argue that it can be used as the basis of such a reconceptualization. The main elements of the resilience approach include attention to drivers and change processes, treating social-ecological systems as complex adaptive systems characterized by cycles and uncertainty, and social systems and ecosystems as coupled and co-evolving. It is a good fit for contemporary resource management highlighting property rights, participation, interaction of institutions at multiple levels, and experimentation as in adaptive management and interactive governance.
Journal Article•
TL;DR: Common concepts pertaining to self-organizing complex adaptive systems are outlined as a general approach to understanding resilience across biological, psychological, and social scales and four data analytic techniques from NDS are compared and contrasted to provide information about some common processes underlying resilience.
Abstract: Theory and methodology from nonlinear dynamical systems (NDS) may provide considerable advantage to health scientists as well as health care professionals. For instance, NDS methodologies and topics in health care share a focus upon the potentially complex interactions of biological, psychological and social factors over time. Nevertheless, a number of challenges remain in creating the necessary bridges in understanding to allow researchers to apply NDS techniques and to enable practitioners to use the resulting evidence to improve patient care. This article aims to provide such a bridge. First, common concepts pertaining to self-organizing complex adaptive systems are outlined as a general approach to understanding resilience across biological, psychological, and social scales. Next, four data analytic techniques from NDS are compared and contrasted with respect to the information they may provide about some common processes underlying resilience. These techniques are: time-series analysis, state-space grids, catastrophe modeling, and network modeling. Implications for health scientists and practitioners are discussed.
TL;DR: Adopting an adaptive leadership framework in the practice of medicine will require adaptive work on the part, but it promises to improve the doctor-patient relationship, increase the authors' effectiveness as healers and reduce unnecessary health care utilization.
Abstract: Rationale, aims and objectives This paper applies the concepts of ‘adaptive leadership’, as developed by Ron Heifetz, MD, to the practice of medicine. Methods Literature review and theory development. Results Patients are complex adaptive systems facing both adaptive and technical health challenges. Technical health challenges are amenable to the simple or complicated expertmediated technical interventions that are common in modern medicine, but complex adaptive challenges can only be addressed by patients doing the adaptive work to learn new attitudes, beliefs and behaviours. In medicine, we often make the mistake of offering technical interventions in lieu of supporting patients’ adaptive work. This error can result in poor clinical outcomes and wasted resources. Expecting simple or complicated technical ‘solutions’ to resolve complex adaptive health challenges is a failure of adaptive leadership and violates Ashby’s law of requisite variety. Adaptive leadership behaviours correspond to and complement doctor practices that have been shown to improve health outcomes and doctor–patient communication. Conclusions Adopting an adaptive leadership framework in the practice of medicine will require adaptive work on our part, but it promises to improve the doctor–patient relationship, increase our effectiveness as healers and reduce unnecessary health care utilization.
Journal Article•
TL;DR: The complexity in delivering patient care is addressed by reviewing recent research on the work of nursing and explaining the concept of RN stacking, and four important activities for supporting RN decision making and establishing a healthy work environment are considered.
Abstract: This article describes the complex work of registered nurses (RNs) in current healthcare settings and presents strategies for promoting healthy work environments in the midst of this complexity. First it addresses the complexity in delivering patient care by reviewing recent research on the work of nursing and explaining the concept of RN stacking. Then it considers four important activities for supporting RN decision making and establishing a healthy work environment, namely, "designing out" system barriers to care, designing and implementing appropriate technology, focusing on nursing direct care functions, and supporting the new RN. Citation: Ebright, P., (Jan. 31, 2010) "The Complex Work of RNs: Implications for Healthy Work Environments" OJIN: The Online Journal of Issues in Nursing Vol. 15, No. 1, Manuscript 4. DOI: 10.3912/OJIN.Vol15No01Man04 Keywords: cognitive work of nursing, complex adaptive system, complexity science, complex work environments, mindfulness, patient care assignments, prioritizing, RN stacking, RN work complexity, situation awareness, stacking, trade-off decisions, workflow management The complexity of nursing work has received increased attention since the Institute of Medicine (IOM) issued its report on medical errors in 2000. Healthcare providers and administrators are now focusing efforts on learning how industries other than healthcare deal with operation breakdowns and catastrophic failures related to errors, and how they increase the reliability of their processes to promote safety and quality (Weick & Sutcliffe, 2007). Research addressing the work of nursing has identified the marked complexity surrounding the delivery of care in our current healthcare environments, and has begun to understand why intended outcomes are often not achieved, even with excellent education programs and redesigned healthcare systems. Understanding the complexity (difficulty) of delivering nursing care is essential for making changes that effectively promote the healthy work environments advocated by the American Association of Critical Care Nurses (AACN, 2005). This article presents new understandings about the complex cognitive work (organizing, prioritizing, and making decisions) of nursing. This cognitive work, called "stacking," has many implications for the development of healthy work environments. To achieve the intended outcomes of healthy work environments, namely quality care, safe patient outcomes, and nurse recruitment and retention, it is necessary to direct attention to the invisible, cognitive work of nurses, i.e., work that promotes suitable work flow and care delivery, and to factors that support or complicate this invisible work. Failure to understand how registered nurses (RNs) make decisions in the context of actual care delivery will lead to the design of processes, environments, and technologies that increase the complexity of RN cognitive work. This failure in turn will lead to increased RN stress and dissatisfaction, decreased RN retention, and ultimately unsafe care. First, I will present the latest research findings describing the complexity of nursing decision making involved in the delivery of care. Next I will describe the implications of these research findings for promoting healthy work environments and the intended goals of quality care, safe patient outcomes, and nurse retention and recruitment. In conclusion I will address four important activities that will support the decision-making work of nurses, namely, (a) "designing out" system barriers to care, (b) designing and implementing technology, (c) focusing on the direct care function, and (d) supporting the new RN. The Complexity in Delivering Care This section will describe the complexity of delivering patient care. First it will present recent research on the work of nursing. Then it will discuss the concept and implications of a phenomenon called 'stacking. …
TL;DR: A two layer hybrid agent architecture to match the needs of future multi-dimensional warfare has an integrated simulation tool to simulate planning results from the cognitive layer via reactive agents and showed that results gained are valid in small unit combat.
Abstract: Today's armed forces, which have a new perspective of combat, are trying to use high-end technologies to improve their capabilities especially in combat and asymmetric warfare. Complexity is the real word to define the future war environment, which will need information about multi dimensional needs. With a continuous increase in the complexity and tempo on the modern battlefield; new demands are placed on rapid and precise information dissemination. The volume of information available to the user becomes larger while the time necessary for correctly interpreting and understanding this information becomes prohibitively smaller. Not only from an informational view but also from other perspectives land combat may be described - mathematically and physically - as a nonlinear dynamical system composed of many interacting semi autonomous and hierarchically organized agent continuously adapting to a changing environment. From this point of view agent based structures are good suited for modeling and simulating complex adaptive systems. This paper proposes a two layer hybrid agent architecture to match the needs of future multi-dimensional warfare. This architecture has an integrated simulation tool to simulate planning results from the cognitive layer via reactive agents. Our work showed us that results gained from this architecture are valid in small unit combat.
TL;DR: The authors discuss healthcare social networks as a hierarchy of embedded complex adaptive systems and the use of social network analysis tools as a means to understand complex communication patterns and reduce medical errors.
Abstract: As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 15th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, the authors discuss healthcare social networks as a hierarchy of embedded complex adaptive systems. The authors further examine the use of social network analysis tools as a means to understand complex communication patterns and reduce medical errors.
TL;DR: The usefulness of theories of complex adaptive systems (CASs) in guiding research interpretation is suggested and how interpretation of research results might be shaped by the fact that HCOs are CASs is pointed out.
Abstract: Rationale Data about health care organizations (HCOs) are not useful until they are interpreted. Such interpretations are influenced by the theoretical lenses used by the researcher.
Objective Our purpose was to suggest the usefulness of theories of complex adaptive systems (CASs) in guiding research interpretation. Specifically, we addressed two questions: (1) What are the implications for interpreting research observations in HCOs of the fact that we are observing relationships among diverse agents? (2) What are the implications for interpreting research observations in HCOs of the fact that we are observing relationships among agents that learn?
Methods We defined diversity and learning and the implications of the non-linear relationships among agents from a CAS perspective. We then identified some common analytical practices that were problematic and may lead to conceptual and methodological errors. Then we described strategies for interpreting the results of research observations.
Conclusions We suggest that the task of interpreting research observations of HCOs could be improved if researchers take into account that the systems they study are CASs with non-linear relationships among diverse, learning agents. Our analysis points out how interpretation of research results might be shaped by the fact that HCOs are CASs. We described how learning is, in fact, the result of interactions among diverse agents and that learning can, by itself, reduce or increase agent diversity. We encouraged researchers to be persistent in their attempts to reason about complex systems and learn to attend not only to structures, but also to processes and functions of complex systems.
TL;DR: In this article, a meaning-based framework for knowledge workers is presented to understand the motivation of knowledge workers and an effective leadership model that suits that framework, which is based on three main characteristics: work orientation, need for a strong membership associatio...
Abstract: Purpose – The purpose of this paper is to present a meaning‐based framework to understand the motivation of knowledge workers and an effective leadership model that suits that framework.Design/methodology/approach – Definitions of knowledge worker, meaning, complex adaptive systems and leadership are provided. The concept of meaning in work is explored through the constructs of work orientation and identity. Based on that, a global meaning framework for knowledge workers is outlined. Additionally, the servant leadership model is detailed and analyzed in light of the global meaning framework for knowledge workers and the need for complex adaptive behavior in successful knowledge‐based organizations.Findings – The motivation of knowledge workers can be well understood from a meaning perspective, taking two constructs into account: work orientation and identity. The global meaning framework of knowledge workers is based on three main characteristics: work as a calling, need for a strong membership associatio...
TL;DR: This paper aims to explore how different actors of a value network co‐create emergent creativity, learning and adaptability in the presence of imposed administrative control and coordination.
Abstract: Purpose – Recent advances in the interactive technologies have transformed the way today's organizations and their different stakeholders learn. Now, because of the increasing learning requirements, neither these organizations nor their stakeholders can afford to be too self‐focused while learning; instead, they collaborate and learn together. Existing theories of learning are not sufficient to explain this complex learning “co‐creation”. Therefore, this paper aims to explore how different actors of a value network co‐create emergent creativity, learning and adaptability in the presence of imposed administrative control and coordination.Design/methodology/approach – The approach adopted in the paper draws on human complex adaptive systems (CAS) perspectives.Findings – Within the value networks, the emergent and informal constraints imposed by interdependent relationships coexist with the imposed administrative controls. Despite being valuable for planning and coordination, these administrative controls do...
TL;DR: The paper proposes a concept in adaptive ecosystem management, being founded on three general concepts: control theory is the backbone to keep system dynamics within an acceptable range even if external disturbances are acting, the underlying model is based on uncertainties, and if the real process can only be modeled incompletely.
TL;DR: In this paper, the authors explore the role of the "reflective adaptive process" in developing delivery interventions and suggest different evaluation methodologies to study the impact of such interventions on the performance of the entire system.
Abstract: Complexity science suggests that our current health care delivery system acts as a complex adaptive system (CAS). Such systems represent a dynamic and flexible network of individuals who can coevolve with their ever changing environment. The CAS performance fluctuates and its members' interactions continuously change over time in response to the stress generated by its surrounding environment. This paper will review the challenges of intervening and introducing a planned change into a complex adaptive health care delivery system. We explore the role of the "reflective adaptive process" in developing delivery interventions and suggest different evaluation methodologies to study the impact of such interventions on the performance of the entire system. We finally describe the implementation of a new program, the Aging Brain Care Medical Home as a case study of our proposed evaluation process.