Creating an organizational space for learning

This paper will explore the concept of resilience from its roots in ecology to the application of this ecological concept of resilience to social and community resilience in the context of climate change. In this context, resilience is seen as a property of complex adaptive communities rather than of individuals. This paper will explore how this ecological concept of resilience has been taken up both by climate adaptation research and by the Transition Town movement. This ecological concept of resilience is at odds with the individualism of both psychological and economic approaches to resilience in relation to climate change.

BackgroundIrrational use of antibiotics is proving to be a major concern to the health systems globally. This results in antibiotics resistance and increases health care costs. In Iran, despite many years of research, appreciable efforts, and policymaking to avoid irrational use of antibiotics, yet indicators show suboptimal use of antibiotics, pointing to an urgent need for adopting alternative approaches to further understand the problem and to offer new solutions. Applying the Complex Adaptive Systems (CAS) theory, to explore and research health systems and their challenges has become popular. Therefore, this study aimed to better understand the complexity of the irrational use of antibiotics in Iran and to propose potential solutions.MethodThis research utilized a CAS observatory tool to qualitatively collect and analyse data. Twenty interviews and two Focus Group discussions were conducted. The data was enriched with policy document reviews to fully understand the system. MAXQDA software was used to organize and analyze the data.ResultWe could identify several diverse and heterogeneous, yet highly interdependent agents operating at different levels in the antibiotics use system in Iran. The network structure and its adaptive emergent behavior, information flow, governing rules, feedback and values of the system, and the way they interact were identified. The findings described antibiotics use as emergent behavior that is formed by an interplay of many factors and agents over time. According to this study, insufficient and ineffective interaction and information flow regarding antibiotics between agents are among key causes of irrational antibiotics use in Iran. Results showed that effective rules to minimize irrational use of antibiotics are missing or can be easily disobeyed. The gaps and weaknesses of the system which need redesigning or modification were recognized as well.ConclusionThe study suggests re-engineering the system by implementing several system-level changes including establishing strong, timely, and effective interactions between identified stakeholders, which facilitate information flow and provision of on-time feedback, and create win-win rules in a participatory manner with stakeholders and the distributed control system.

Background: This article draws on the literature relating to game-centred approaches (GCAs), such as Teaching Games for Understanding, and dynamical systems views of motor learning to demonstrate a convergence of ideas around games as complex adaptive learning systems. This convergence is organized under the title ‘complexity thinking’ and gives rise to a comprehensive model of game-based learning that addresses theoretical and practitioner considerations relevant to researchers and teachers. Complexity thinking is also partnered with an ecological integration value orientation to reinforce the dominant purposes of game-based learning in physical education. Key concepts: The study of game-based learning from a complexity thinking perspective relies on the foundational alignment of game characteristics with those of complex learning systems. Both complex learning systems and games are (a) comprised of co-dependent agents, (b) self-organizing, (c) open to disturbance, (d) sites of co-emergent learning, (e) open to varying experiences or interpretations of time, and (f) able to evolve their structures in response to feedback. Considering games as learning systems opens the door to consideration of the system being as sustainable and adaptable as it can. Sustainability, adaptation potential, and engagement levels emerge from the ‘game as learning system’ discussion in order to provide insight into the functioning of the game. High levels of engagement and sustainability are the presented goals for teachers working from a complexity thinking perspective. A number of key concepts from systems literature, such as attractors, affordances, attunement, and disturbances, are discussed as identifiable and manipulatable dimensions of game-based learning. Implications for the PE profession: Physical educators are well positioned to notice learning as it emerges and to construct environments that focus learning without forcing learning. Complexity thinking concepts such as flow, coupling, engagement, attractors, affordances, attunement, and disturbance, in combination with the pedagogical principles advocated by GCAs, provide a robust set of analytical and teaching tools. It is to be hoped that a deepening of understanding of how game forms and game play lead to learning during games will improve the quality of learning experiences in games and foster increasing and prolonged engagement by students.

Bioeconomy is a complex economic system, the functioning of which leads to the emergence of a synergy effect due to the effective combination of natural resources and technologies along with the market-based, social, and political components. In a bioeconomic system, established links are formed between traditional industries based on the use of fossil natural resources and modern ones that have not previously intersected. As a result, one industry uses by-products of another industry as raw materials, thus forming a closed production cycle. The purpose of the article is to develop an author’s vision of the conceptual foundations to substantiate the sustainability of the bioeconomic system, taking into account its specific characteristics, modern challenges and potential of the country. The article reveals the features of transformations of socioeconomic systems into a complex adaptive bioeconomic system in a dynamic perspective. The complexity and complicacy of transformation management lies in the relationship and interaction of the elements of the system, as well as between the very system and its environment. A theoretical analysis of the evolution of the concept of «bioeconomy» is carried out and its basic properties are determined. The interpretation of the bioeconomy as a complex adaptive system that ensures the achievement of sustainable development goals is substantiated. Based on empirical data from the State Statistics Service of Ukraine and the European Commission, potential sectors of the bioeconomic sector of Ukraine have been identified, and the dynamics of the contribution of potential sectors of Ukraine’s economy to the national economy has been analyzed according to the main indicators: generation of value added and creation of jobs. Based on the theoretical and analytical research, it is proved that bioeconomy, as a complex system combining several sectors of the economy, can adapt to changes occurring in the environment.

Complex adaptive systems (CAS) have been identified as being hard to comprehend, composed of multiple interacting components acting interdependently with overlapping functions aimed at adapting to external/environmental forces. The current theoretical model utilized the natural functions of teams, viewing teams as a complex adaptive system, to develop the structure of the theory of complex adaptive team systems (CATS). The CATS model was formulated around the components of complexity theory (interactions, nonlinearity, interdependency, heterogeneity, complex systems, emergence, self-organizing, and adaptability) to show its utility across multiple domains (the role of leadership, organizational learning, organizational change, collective cognitive structures, innovation, cross-business-unit collaborations). In theorizing the CATS model, a new level of analysis was implemented, the interactions between agents as a move toward emergence in complex systems. The CATS model ultimately provides a model for organizations/institutions to drive knowledge creation and innovation while operating in today's complexity.

Rising healthcare costs are major concerns in most high-income countries. Yet, political measures to reduce costs have so far remained futile and have damaged the best interests of patients and citizen. We therefore explored the possibilities to analyze healthcare systems as a socially constructed complex adaptive system (CAS) and found that by their very nature such CAS tend not to respond as expected to top-down interventions. As CAS have emergent behaviors, the focus on their drivers – purpose, economy and behavioral norms – requires particular attention. First, the importance of understanding the purpose of health care as improvement of health and its experience has been emphasized by two recent complementary re-definitions of health and disease. The economic models underpinning today’s healthcare – profit maximization – have shifted the focus away from its main purpose. Second, although economic considerations are important, they must serve and not dominate the provision of healthcare delivery. Third, expected health professionals’ behavioral norms – to first consider the health and wellbeing of patients – have been codified in the universally accepted Declaration of Geneva 2017. Considering these three aspects it becomes clear that complex adaptive healthcare systems need mindful top-down/bottom-up leadership that supports the nature of innovation for health care driven by local needs. The systemic focus on improving people’s health will then result in significant cost reductions.

Although many books and conference reports have considered the changeability of a complex adaptive system (CAS), no in-depth study has assessed how changes impact a CAS or the relationships among the CAS changeability parameters of agility, flexibility, robustness, and adaptability. This study analyzes the impact of CAS changeability when an external agent requires a change and analyzes how such a change affects the evolution of the CAS. We start by reviewing the general concepts of changeability and CAS, followed by an analysis of their relationship. A model using an extension of learning classifier system (XCSF) is presented and evaluated to meet the objectives of this research to: 1) accurately assess the impact of changeability on telecommunication-based CAS components and their evolution; and 2) gain insight into the impact of changes on CAS for the purpose of improving the engineering of such systems in the future. The relationship between changeability and fitness, which is an important CAS performance measure, is included. CAS simulations using the XCSF model are compared with data from a telecommunication company over the past few years; the comparison suggests that the XCSF approach may be useful for improving CAS engineering.

The enterprises agglomerations are becoming an interesting study topic, so several authors are sure that the interactions and geographic proximity have a strong impact in the competition and innovation of the enterprises of the clusters (T. Altenburg and J. Meyer-Stamer), (P. Krugman, 1999), (M. Porter, 2004). So it is also possible to talk about "learning clusters", knowledge accumulated, and knowledge constructed in a collective form. For the study of these shapes of post-fordists production organizations and for the many variables that they present new frameworks are necessary, one of them is the complex adaptive systems theory. The model of the complex adaptive systems permits to evaluate multiple interactions between different agents and the impact of the agent's action in the system. This focus permits to find news and unexpected models from the interactions between the parts ofthe open systems. The present paper has the aim of studying: the dynamic interaction, the knowledge transfer, the learning, and the evolution of the Ica wine cluster in Peru with that model. In this context, the research questions are: what is the dynamic of the interactions between enterprises of the cluster?, how is the knowledge transferred?, how does the cluster learn?, and how is the technological evolution of this cluster? The methodology is the elaboration of a theoretical model that integrates the concepts of characteristics of the clusters and complex adaptive systems, then accordingly this theoretical model is elaborated a questionnaire, after that the questionnaire is applied to a wine and grape cluster, finally the main conclusions and recommendations are obtained. The results of the research will be an important document for the actions, strategic decisions and improvement of the interactions between cluster agents.

Arecent Institute of Medicine (IOM) report describes a chasm in health care quality that we must cross for patients to receive better care in the 21st century. The report calls for a “systems approach,” drawing on the rapid evolution of knowledge about complex adaptive systems.1 Understanding how complex adaptive systems work can give physicians insights to develop and modify health care systems. By describing a practical application of the ideas about complex adaptive systems to newborn care, we aim to help pediatricians prepare to lead in this field. A complex adaptive system is a collection of individual agents who have the freedom to act, but because the agents are interconnected, action by any agent changes the context for other agents in the system. One familiar example is the buyers in a stock market. In the last century, it was usual to see organizations as mechanical systems: in mechanical systems, if we know what each part of a system does, we can predict perfectly how the whole will respond in a given situation. This is obviously not true of the stock market. A complex adaptive system may display sudden unpredictable shifts in behavior caused by interactions among agents. An essential first step in improving the US health care system is to recognize that its member organizations and individuals, with sublevels nested within and interconnected to each other, make up a complex adaptive system. One of the key attributes of a complex adaptive system is that orderly behavior can emerge among many agents who are acting independently but who share a common drive. For instance, ants, driven to survive, create intricate buildings and foraging systems without any planning by a chief executive ant. So do humans. The citizens of New York City share a drive to eat; with no single individual …

School‐improvement initiatives are implemented with admirable goals, often requiring substantial human and material resources. However, many fail to be sustainable beyond short‐term funding cycles or the enthusiasm of local initiators. Typically, implementation and improvement are viewed linearly and as static end‐products that fail to consider that schools are complex adaptive systems (CAS) that are continuously and recursively challenged with change. To investigate sustainable school‐improvement within CAS, we used PRISMA‐SR guidelines to conduct a scoping review of peer‐reviewed journal articles extracted from six databases using keywords synonymous with ‘ complex or adaptive system ’ , ‘ sustain ’ , ‘ school ’ and ‘ initiative ’ . The search process yielded 1146 articles but only 16 of those articles met our inclusion/exclusion criteria that specified that authors present an integrated view of sustainable implementation in schools conceptualised as CAS. Within the selected 16 articles, key components for sustainability in schools described as CAS included access to adequate funding and resources, engagement and involvement of stakeholders, the ability of stakeholders to adapt to change, formation of collaborative partnerships, and the development of supportive policies and procedures. Some important issues arose, such as the tendency of the ‘whole school approach’ to be reduced to information dissemination activities that do not adequately deal with components of complex systems, and the increasing recognition that older implementation models that seek ‘institutionalisation’ fail to appreciate that sustainability is a process, not an end goal. This scoping review highlights the need to recognise the complexity and adaptivity of school systems for successful and sustained implementation of school‐improvement initiatives.

Modelling and knowledge transfer in complexity science

The causes of wellbeing and illbeing interact with feedback dynamics resulting in the same set of traits giving rise to a variety of health outcomes (multi-finality) and different traits giving rise to the same health outcome (equi-finality). As a result, a full understanding of health and its disorders must be in terms of a complex adaptive system of causes, rather than in terms of categorical diagnoses or sets of symptoms. The three domains of person-centered integrative diagnosis (PID) are considered here as interacting components of a complex adaptive system comprised of health status (functioning/wellness versus disability/disorder), experience of health (self-awareness/fulfillment versus misunderstanding/suffering) and contributors to health (protective versus risk factors). The PID domains thereby allow healthcare and health promotion to be understood in terms of measurable components of a complex adaptive system. Three major concepts of health are examined in detail to identify their dynamic origins: Psychological Maturity, Flourishing and Resilience. In humanistic psychology, psychological maturity (i.e. healthy personality, mental wellbeing) involves the development of high self-directedness, high co-operativeness and high self-transcendence, but self-transcendence is nevertheless devalued in individualistic and materialistic cultures except when people must face adversity and ultimate situations like suffering or the threat of death. Psychological Maturity develops through two complementary processes often labeled as Flourishing and Resilience. Flourishing is the development of one's potential to live optimally, especially as the result of favorable circumstances, whereas Resilience is positive adaptation to life despite adverse circumstances. As a result of the complex feedback dynamics between the processes of flourishing and resilience, each person is a unique individual who has a variety of paths for achieving positive health and wellbeing open to him or her. Person-centered health promotion and care can thereby be approached as a creative life project that can be conducted with the assistance of healthcare workers who are both therapeutic allies and well-informed experts.

Innovation dynamics are more and more considered to represent one of the most important processes in the development of modern economic systems. This perspective is at the root of the development of various innovation concepts. The systematic study of different systems of innovation has raised the awareness that each particular system has its own characteristics, and that it is not always possible to unilaterally define all the parameters that play a role in shaping innovation processes. The article describes the main obstacles facing public policy decision-making drawing on examples from innovation and research policy. It argues that Complex Adaptive Systems (CAS) research can teach us a series of useful lessons, especially those features necessitating the consideration of innovation systems as complex adaptive systems.

Natural complex adaptive systems are of particular scientific interest in many domains, as they may produce something new, like structures, patterns, or properties, that arise from the rules of self-organization. These novelties are emergent if they cannot be understood as any property of the components, but as a new property of the system. One of the leading methods to better understand complex adaptive systems is the use of their computational representation. In this paper, we make the case that emergence in computational complex adaptive systems can only be epistemological, as the constraints of computer functions do not allow for the creation of something new, as required for ontological emergence. As such, computer representations of complex adaptive systems are limited in producing emergence, but nonetheless useful to better understand the relationship between emergence and complex adaptive systems.

This chapter introduces an approach to facilitate the use of concepts and methodologies from Systems and Complexity Sciences into the realm of Health Sciences. Health care is a convoluted system with many interdependencies of people, resources, and processes. Recently the use of Systems and Complexity Sciences has been proposed as a viable methodology to better understand and manage the challenges in the healthcare system. Complex Adaptive Systems (CAS) is a branch of Systems and Complexity Sciences that brings a different perspective to lead the healthcare organization. We discuss the identification and application of CAS principles to the administration and leadership of the healthcare organization. The Emergency Department is utilized as a case study to identify and analyse the application of CAS concepts. The case study facilitates the understanding of the CAS concepts and their applicability to other healthcare organizations and departments.