Showing papers on "Complex adaptive system published in 2019"

Capturing emergent phenomena in social-ecological systems: an analytical framework

Abstract: Social-ecological systems (SES) are complex adaptive systems. Social-ecological system phenomena, such as regime shifts, transformations, or traps, emerge from interactions among and between human ...

A more dynamic understanding of human behaviour for the Anthropocene

Abstract: Human behaviour is of profound significance in shaping pathways towards sustainability. Yet, the approach to understanding human behaviour in many fields remains reliant on overly simplistic models. For a better understanding of the interface between human behaviour and sustainability, we take work in behavioural economics and cognitive psychology as a starting point, but argue for an expansion of this work by adopting a more dynamic and systemic understanding of human behaviour, that is, as part of complex adaptive systems. A complex adaptive systems approach allows us to capture behaviour as ‘enculturated’ and ‘enearthed’, co-evolving with socio–cultural and biophysical contexts. Connecting human behaviour and context through a complex adaptive systems lens is critical to inform environmental governance and management for sustainability, and ultimately to better understand the dynamics of the Anthropocene itself. To understand and address sustainability problems, a complex model of human behaviour is proposed, one that co-evolves with their context, as opposed to simpler models.

Developing Creativity to Enhance Human Potential in Sport: A Wicked Transdisciplinary Challenge

Abstract: The challenge of developing creativity to enhance human potential is conceptualized as a multifaceted wicked problem due to the countless interactions between people and environments that constitute human development, athletic skill, and creative moments. To better comprehend the inter-relatedness of ecologies and human behaviors, there have been increasing calls for transdisciplinary approaches and holistic ecological models. In this paper we explore an ecological dynamics rationale for creativity, highlighting the conceptual adjacency of key concepts from transdisciplinarity, dynamic systems theory, ecological psychology and social-cognitive psychology. Our aim is to extend the scope of ecological dynamics and contextualize the application of non-linear pedagogy in sport. Foregrounding the role of sociocultural constraints on creative behaviors, we characterize the athlete-environment system as an ecological niche that arises from, and simultaneously co-creates, a form of life. We elaborate the notion that creative moments, skill and more generally talent in sport, are not traits possessed by individuals alone, but rather can be conceived as properties of the athlete-environment system shaped by changing constraints. This re-conceptualization supports a pedagogical approach predicated on notions of athletes and sports teams as complex adaptive systems. In such systems, continuous non-linear interactions between system components support the exploration of fluent and flexibly creative performance solutions by athletes and sports teams. The implications for practice suggest that cultivating a constellation of constraints can facilitate adaptive exploration of novel affordances (opportunities/invitation for action), fostering creative moments and supporting creative development in athletes. Future models or frameworks for practice contend that pedagogies should emerge from, and evolve in, interaction with the sociocultural context in which practitioners and athletes are embedded.

Global food safety as a complex adaptive system: Key concepts and future prospects

Abstract: Background Over the last few decades the food production, distribution and consumption chains have become complex as a result of globalisation and food travelling over large distances. The food supply chain is a multi-layered structure with multiple interactions across and within the hierarchical levels across the entire food system. As unwanted factors and food safety behaviours could lead to global food poisoning catastrophes, it is important to adopt a systems approach to gain a whole-system perspective of the global food system. Scope and approach In this review the importance of adopting a complex systems approach towards the global food system and a possible systems analysis method that would help capture this perspective are described. This study emphasizes the importance of adopting a proactive approach, starting with identifying the similarities between the characteristics of complex systems and the food system and the importance and benefits of adopting a whole system approach in the global food system. Key findings and conclusions Adopting a complex systems approach to the global food system is of paramount relevance as this would help further understand the interconnectivity of food systems and how multifaceted factors across systemic levels play a major role in achieving food safety. Using a systems analysis model such as the Systems-Theoretic Accident Models and Processes (STAMP) model provides the ability to tackle the limitations of event chain models and analyse the complex interactions among various components in the complex food system. It is the need of the hour to study food systems at micro and macro-levels and develop a model that would have the ability to identify food safety related issues across the global food system.

Seeing the forest and not the trees: Learning from nature’s circular economy

Abstract: Managing for triple bottom line (TBL) by creating economic, ecological and social value is increasingly on the business agenda. However, it is challenging to address non-economic issues because businesses are designed to maximize profit and are less aligned with global ecological and social challenges. Shifting from linear supply chain thinking to interconnected, circular, ecosystem thinking could offer insights into addressing these challenges. Looking at time-tested patterns and strategies from natural ecosystems that operate using, reusing, and repurposing materials and components in a way that is sustainable, may allow for innovative and effective solutions for businesses to begin addressing these global challenges. Biomimicry, an approach to innovation that seeks solutions to human challenges by emulating nature, can inspire evolutionary and structural aspects of business ecosystems. Biomimetic insights related to mycorrhizal (root-fungus) networks are used as a foundation of this research. This research draws on network theory and complex adaptive systems (CAS) to translate the biomimetic language to the language of networked business systems. Based on literature and interview data gathered from five businesses, biomimetic principles were developed that can guide businesses as they transition from linear, wasteful chains to circular business value systems. In particular, business ecosystems require more participants in the roles of ‘scavengers’ and ‘decomposers’ and an underlying infrastructure, that helps to manage information and material flows in an integrated way.

Understanding complexity - the palliative care situation as a complex adaptive system.

Abstract: The concept of complexity is used in palliative care (PC) to describe the nature of patients’ situations and the extent of resulting needs and care demands. However, the term or concept is not clearly defined and operationalised with respect to its particular application in PC. As a complex problem, a care situation in PC is characterized by reciprocal, nonlinear relations and uncertainties. Dealing with complex problems necessitates problem-solving methods tailored to specific situations. The theory of complex adaptive systems (CAS) provides a framework for locating problems and solutions. This study aims to describe criteria contributing to complexity of PC situations from the professionals’ view and to develop a conceptual framework to improve understanding of the concept of “complexity” and related elements of a PC situation by locating the complex problem “PC situation” in a CAS. Qualitative interview study with 42 semi-structured expert (clinical/economical/political) interviews. Data was analysed using the framework method. The thematic framework was developed inductively. Categories were reviewed, subsumed and connected considering CAS theory. The CAS of a PC situation consists of three subsystems: patient, social system, and team. Agents in the "system patient" are allocated to further subsystems on patient level: physical, psycho-spiritual, and socio-cultural. The "social system" and the "system team" are composed of social agents, who affect the CAS as carriers of characteristics, roles, and relationships. Environmental factors interact with the care situation from outside the system. Agents within subsystems and subsystems themselves interact on all hierarchical system levels and shape the system behaviour of a PC situation. This paper provides a conceptual framework and comprehensive understanding of complexity in PC. The systemic view can help to understand and shape situations and dynamics of individual care situations; on higher hierarchical level, it can support an understanding and framework for the development of care structures and concepts. The framework provides a foundation for the development of a model to differentiate PC situations by complexity of patients and care needs. To enable an operationalisation and classification of complexity, relevant outcome measures mirroring the identified system elements should be identified and implemented in clinical practice.

Doing complexity leadership theory: How agile coaches at Spotify practise enabling leadership

Abstract: Complexity leadership theory (CLT) is about balancing formal and informal organisation to leverage dynamics of Complex Adaptive Systems (CAS) and produce learning, creativity, and adaptation in org ...

Information Technology as the Basis for Transformation into a Digital Society and Industry 5.0

Abstract: Currently, the industry is transforming the physical world of real things into their “virtual copies”. This transformation is a key element of industry 4.0. Due to the high requirements of end users to the individualization of the purchased product industry 5.0 is becoming increasingly popular concept, which implies the penetration of artificial intelligence into the human life to increase the level of human capabilities. The article discusses the state and prospects of development of technologies that contribute in the process of the transition from industry 4.0 to industry 5.0. The conditional pyramid of technologies which Association is capable to provide this transition is presented. New types of distributed computers, Internet of everything, multi-agent systems and technologies, ontology and knowledge bases, theory of complex adaptive systems, emergent intelligence, evergetic and enterprise architecture are considered as the main components for the transition. Boundary calculations in the context of management of data coming from the Internet of things will affect almost all companies in the economy and the public sector. They will cover the scope of activities from the automation of throughput control and data collection on the quality of goods, monitoring of vehicle traffic and ending with the robotization of factories. The article presents an analysis of modern and promising technologies necessary for the organization of the digital industry in enterprises, and determining the set of necessary technologies that ensure the transition from the current state of the industry to Industry 4.0 and then to Industry 5.0. It also presents a formal description of industry 4.0 and industry 5.0, which makes it possible to present the problem as a mathematical problem that has a solution. Complex formal description of the enterprise, based on the methodology of its architecture, allows to increase the efficiency of business information support in the industry 5.0. This is necessary for the organization of the digital industry in enterprises and to determine how to ensure the transition from the current state of the industry to industry 5.0. Applying this approach to industry 4.0, then to Industry 5.0, will measure the cost of this transition and make it effective.

Successful Healthcare Improvements From Translating Evidence in complex systems (SHIFT-Evidence): simple rules to guide practice and research.

Abstract: Background Evidence translation and improvement research indicate that healthcare contexts are complex systems, characterized by uncertainty and surprise, which often defy orchestrated intervention attempts. This article reflects on the implications of complexity on attempts to translate evidence, and on a newly published framework for Successful Healthcare Improvements From Translating Evidence in complex systems (SHIFT-Evidence). Discussion SHIFT-Evidence positions the challenge of evidence translation within the complex and evolving context of healthcare, and recognizes the wider issues practitioners routinely face. It is empirically grounded, and designed to be comprehensive, practically relevant and actionable. SHIFT-evidence is summarized by three principles designed to be intuitive and memorable: 'act scientifically and pragmatically'; 'embrace complexity'; and 'engage and empower'. Common challenges and strategies to overcome them are summarized in 12 'simple rules' that provide actionable guidance. Conclusion SHIFT-Evidence provides a practical tool to guide practice and research of evidence translation and improvement within complex dynamic healthcare settings. Implications are that improvement initiatives and research study designs need to take into account the unique initial conditions in each local setting; conduct needs to respond to unpredictable effects and address dependent problems; and evaluation needs to be sensitive to evolving priorities and the emergent range of activities required to achieve improvement.

Power in global governance: an expanded typology from global health.

Abstract: The exercise of power permeates global governance processes, making power a critical concept for understanding, explaining, and influencing the intersection of global governance and health. This article briefly presents and discusses three well-established conceptualizations of power—Dahl’s, Bourdieu’s, and Barnett and Duvall’s—from different disciplines, finding that each is important for understanding global governance but none is sufficient. The conceptualization of power itself needs to be expanded to include the multiple ways in which one actor can influence the thinking or actions of others. I further argue that global governance processes exhibit features of complex adaptive systems, the analysis of which requires taking into account multiple types of power. Building on established frameworks, the article then offers an expanded typology of eight kinds of power: physical, economic, structural, institutional, moral, discursive, expert, and network. The typology is derived from and illustrated by examples from global health, but may be applicable to global governance more broadly. Finally, one seemingly contradictory – and cautiously optimistic – conclusion emerges from this typology: multiple types of power can mutually reinforce tremendous power disparities in global health; but at the same time, such disparities are not necessarily absolute or immutable. Further research on the complex interaction of multiple types of power is needed for a better understanding of global governance and health.

The Role of Hypernetworks as a Multilevel Methodology for Modelling and Understanding Dynamics of Team Sports Performance.

Abstract: Despite its importance in many academic fields, traditional scientific methodologies struggle to cope with analysis of interactions in many complex adaptive systems, including team sports. Inherent features of such systems (e.g. emergent behaviours) require a more holistic approach to measurement and analysis for understanding system properties. Complexity sciences encompass a holistic approach to research on collective adaptive systems, which integrates concepts and tools from other theories and methods (e.g. ecological dynamics and social network analysis) to explain functioning of such systems in their natural environments. Multilevel networks and hypernetworks comprise novel and potent methodological tools for assessing team dynamics at more sophisticated levels of analysis, increasing their potential to impact on competitive performance in team sports. Here, we discuss how concepts and tools derived from studies of multilevel networks and hypernetworks have the potential for revealing key properties of sports teams as complex, adaptive social systems. This type of analysis can provide valuable information on team performance, which can be used by coaches, sport scientists and performance analysts for enhancing practice and training. We examine the relevance of network sciences, as a sub-discipline of complexity sciences, for studying the dynamics of relational structures of sports teams during practice and competition. Specifically, we explore the benefits of implementing multilevel networks, in contrast to traditional network techniques, highlighting future research possibilities. We conclude by recommending methods for enhancing the applicability of hypernetworks in analysing team dynamics at multiple levels.

The Building Blocks of Religious Systems: Approaching Religion as a Complex Adaptive System

Abstract: Religions consist of cognitive, neurological, affective, behavioral, and developmental traits that form a complex adaptive system. The underlying adaptive goal of religious systems is to foster cooperation and social coordination within communities. The workings of religious systems are intricate, and even convoluted, but at their core, they maintain eight primary interdependent building blocks: authority, meaning, moral obligation, myth, ritual, sacred, supernatural agents, and taboo. These features exhibit independent phylogenetic histories, but at some point in human history, they began to regularly coalesce across human populations. Religious systems, which require energy like all systems, are fueled by ritual behaviors. Ritual’s interconnections with the other core building blocks produce individual-level effects, including physiological and affective responses, which in turn yield group-level effects such as shared cognitive schema, ethos, symbolic meaning, and identity. These group-level effects result in a sense of communal order and produce social norms, most importantly, norms that encourage cooperative and coordinated behaviors among community members. Further investments in ritual, which sustain the religious system, depend upon the success of these collective behaviors. Specifically, religious systems maintain positive and negative feedback loops that inform individuals about the system’s success, or lack thereof, in terms of collective outputs, mating opportunities, reproduction, and health outcomes. When cooperation fails, or mating, reproduction, or health suffer, the religious system will generally adapt to its current environmental conditions accordingly, sometimes subtly without notice among adherents and sometimes through significant revivals that reinvigorate ritual participation. Religious systems that are unable to adapt cease to function as living social institutions that bring order to individual lives.

The Fundamentals of Complex Adaptive Systems

Abstract: Complex Adaptive Systems (CAS) is a framework for studying, explaining, and understanding systems of agents that collectively combine to form emergent, global level properties. These agents can be nearly anything, from ants or bees, to brain cells, to water particles in a weather pattern, to groups of cars or people in a city or town. These agents produce emergent patterns via correlated feedbacks throughout the system, feedbacks that create and fortify a basin of attraction: a persistent pattern of behavior that itself is outside of equilibrium. There is also an ever-growing understanding that similar features in complex systems across a diversity of domains may indicate similar fundamental principles at work, and as such there is often utility in using the key features of one system to gain insight into the workings of seemingly distinct fields. Here we also include a brief review of multiple models that attempt to do exactly this, including some of our previous work. Though there is not complete agreement on all aspects and definitions in this field, this introduction also summarizes our understanding of what defines a CAS, including the concepts of complexity, agents, adaptation, feedbacks, emergence, and self-organization; and places this definition and its key features in a historical context. Finally we briefly discuss two of the common biases often found that the tools of CAS can help counteract: the hierarchical bias, assuming a strong top-down organization; and the complexity bias, the tendency to assign complicated features to agents that turn out to be quite simple.

Constructing a Consensus on Language Evolution? Convergences and Differences Between Biolinguistic and Usage-Based Approaches.

Abstract: Two of the main theoretical approaches to the evolution of language are biolinguistics and usage-based approaches. Both are often conceptualized as belonging to seemingly irreconcilable "camps." Biolinguistic approaches assume that the ability to acquire language is based on a language-specific genetic foundation. Usage-based approaches, on the other hand, stress the importance of domain-general cognitive capacities, social cognition, and interaction. However, there have been a number of recent developments in both paradigms which suggest that biolinguistic and usage-based approaches are actually moving closer together. For example, theoretical advancements such as evo-devo and complex adaptive system theory have gained traction in the language sciences, leading to changed conceptions of issues like the relative influence of "nature" and "nurture." In this paper, we outline points of convergence between current minimalist biolinguistic and usage-based approaches regarding four contentious issues: (1) modularity and domain specificity; (2) innateness and development; (3) cultural and biological evolution; and (4) knowledge of language and its description. We show that across both paradigms, researchers have come to increasingly embrace more complex views of these issues. They also have come to appreciate the view that biological and cultural evolution are closely intertwined, which lead to an increased amount of common ground between minimalist biolinguistics and usage-based approaches.

Integrated decision-making framework for urban freight logistics policy-making

Abstract: The urban freight logistics policy-making process takes place in a complex environment and presents numerous challenges, such as difficult trade-offs between the objectives of various stakeholders, unclear problem ownership, and a lack of data on and awareness of urban freight issues. Furthermore, the complex interactions and power dynamics between different stakeholders introduce additional difficulties when attempting to predict the effects of different policies. In this study, we extend the current perspective on urban logistics decision-making by adopting a Complex Adaptive System (CAS) perspective. This allows us to better interpret the behaviors of urban logistics stakeholders and elucidate some of the most pressing challenges encountered in urban logistics policy-making. Building on the extant urban logistics and CAS literature, we establish an integrative decision-making framework that aims at increasing the success of urban logistics policies. Finally, we apply our framework to a case study in order to illustrate the operationalization of the proposed CAS perspective in an empirical setting on urban logistics policy-making.

Aquatic–terrestrial linkages as complex systems: Insights and advances from network models

Abstract: Ecosystems at the land–water interface are linked through networks of species interactions and are excellent examples of complex adaptive systems. Here, we discuss how ecological networks c...

The Game between Game Theory and Gaming Simulations: Design Choices

Abstract: Background. The abstraction of complex systems, which is required by default when modelling gaming simulations, is a convoluted and time-consuming process. For gaming simulations to be efficient an...

Can Complexity-Thinking Methods Contribute to Improving Occupational Safety in Industry 4.0? A Review of Safety Analysis Methods and Their Concepts

Abstract: With the introduction of Industry 4.0, occupational health and safety finds itself confronted with new types of hazards. Many Industry 4.0 innovations involve increased machine intelligence. These properties make socio-technical work in Industry 4.0 applications inherently more complex. At the same time, system failure can become more opaque to its users. This paper reviews and assesses safety analysis methods as the breakdown of interaction coupling in socio-technical systems on the one hand, and the degree of failure tractability on the other hand; the latter being used as a proxy for complexity. Previous literature confirms that traditional health and safety risk assessment methods are unable or are ‘ill-equipped’ to deal with these system properties. This paper studies the need to introduce new paradigms and safety methods related to complexity thinking with theories borrowed from the study of complex adaptive systems, all to assess the arena of abruptly changing hazards introduced by Industry 4.0. At the same time, this review makes clear that there is no one-solution-fits-all method. Occupational health and safety (OHS) covers many different hazard types and will need a combination of old, new and yet-to-be-developed safety assessment methods.

Smart City 5.0 as an Urban Ecosystem of Smart Services

Abstract: In this paper, Smart City is described as a live and constantly developing complex adaptive system operating in an uncertain environment with many participants and actors involved. The vision of the “Smart City 5.0” concept as an ecosystem of smart services based on multi-agent technology is presented. It is characterized by the cooperation of Artificial Intelligence systems and humans, and can harmoniously balance all spheres of life and contradictory interests of different city actors. In this concept, each smart service is presented by an autonomous agent. They can compete or cooperate with each other through a service bus and interact both vertically and horizontally on the basis of specialized protocols. Top-level services can be constructed as autonomous multi-agent systems of a lower level, where an agent can recursively reveal a new service for itself. The paper describes the design principals and the general architecture of the digital platform including the basic agent of smart service, the architecture and basic principles of smart city ontologies and knowledge base. The paper shows how the platform can support the decision-making life cycle for managing any urban object and the adaptive behaviour of Smart City 5.0 is compared with the fixed scenarios Smart City 4.0.

Exemplary Learning Environments for the Health Professions: A Vision.

Abstract: In this article, the authors propose a vision for exemplary learning environments in which everyone involved in health professions education and health care collaborates toward optimal health for individuals, populations, and communities. Learning environments in the health professions can be conceptualized as complex adaptive systems, defined as a collection of individual agents whose actions are interconnected and follow a set of shared "simple rules." Using principles from complex adaptive systems as a guiding framework for the proposed vision, the authors postulate that exemplary learning environments will follow four such simple rules: Health care and health professions education share a goal of improving health for individuals, populations, and communities; in exemplary learning environments, learning is work and work is learning; exemplary learning environments recognize that collaboration with integration of diverse perspectives is essential for success; and the organizations and agents in the learning environments learn about themselves and the greater system they are part of in order to achieve continuous improvement and innovation. For each of the simple rules, the authors describe the details of the vision and how the current state diverges from this vision. They provide actionable ideas about how to reach the vision using specific examples from the literature. In addition, they identify potential targets for assessment to monitor the success of learning environments, including outcome measures at the individual, team, institutional, and societal levels. Such measurements can ensure optimal alignment between health professions education and health care and inform ongoing improvement of learning environments.

Evidence‐based medicine—Not a panacea for the problems of a complex adaptive world

Abstract: The recent sacking of Peter Gotzsche from the Cochrane Collaboration Board raised strong responses and highlights the neglected issue about priorities-maintaining the reputation of the organization or vigorously debating the merits of scientific approaches to find answers to complex problems? The Cochrane approach hales the randomized trial (RCT) as the gold standard research approach and affirms that meta-analysis provides the ultimate proof (or platinum standard) to settle contentious issues confronting the clinician. However, most published medical research is wrong, and critics coined the acronym GIGO (garbage in, garbage out) as a meme to highlight the risks of blind faith in the hyped-up procedures of the EBM movement. This paper firstly explores the differences between the prevailing scientific method arising from the linear cause-and-effect assumption and the complex adaptive systems science methods arising from observations that most phenomena emerge from nonlinearity in networked systems. Most medical conditions are characterized by necessary features that by themselves are not sufficient to explain their nature and behaviour. Such nonlinear phenomena require modelling approaches rather than linear statistical and/or meta-analysis approaches to be understood. These considerations also highlight that research is largely stuck at the data and information levels of understanding which fails clinicians who depend on knowledge-the synthesis of information-to apply in an adaptive way in the clinical encounter. Clinicians are constantly confronted with the linked challenges of doing things right and doing the right thing for their patients. EBM and Cochrane with their restrictive approaches are the antithesis to a practice of medicine that is responsive to constantly changing patient needs. As such, the EBM/Cochrane crisis opens a window of opportunity to re-examine the nature of health, illness and disease, and the nature of health care and its systems for the benefits of its professionals and their patients. We are at the cusp of a paradigmatic shift towards an understanding a praxis of health care that takes account of its complexities.