Showing papers on "Complex adaptive system published in 2022"

A complex systems approach to aging biology

Abstract: Having made substantial progress understanding molecules, cells, genes and pathways, aging biology research is now moving toward integration of these parts, attempting to understand how their joint dynamics may contribute to aging. Such a shift of perspective requires the adoption of a formal complex systems framework, a transition being facilitated by large-scale data collection and new analytical tools. Here, we provide a theoretical framework to orient researchers around key concepts for this transition, notably emergence, interaction networks and resilience. Drawing on evolutionary theory, network theory and principles of homeostasis, we propose that organismal function is accomplished by the integration of regulatory mechanisms at multiple hierarchical scales, and that the disruption of this ensemble causes the phenotypic and functional manifestations of aging. We present key examples at scales ranging from sub-organismal biology to clinical geriatrics, outlining how this approach can potentially enrich our understanding of aging.

The ENCOMPASS framework: a practical guide for the evaluation of public health programmes in complex adaptive systems

Abstract: Systems thinking embraces the complexity of public health problems, including childhood overweight and obesity. It aids in understanding how factors are interrelated, and it can be targeted to produce favourable changes in a system. There is a growing call for systems approaches in public health research, yet limited practical guidance is available on how to evaluate public health programmes within complex adaptive systems. The aim of this paper is to present an evaluation framework that supports researchers in designing systems evaluations in a comprehensive and practical way.We searched the literature for existing public health systems evaluation studies. Key characteristics on how to conduct a systems evaluation were extracted and compared across studies. Next, we overlaid the identified characteristics to the context of the Lifestyle Innovations Based on Youth Knowledge and Experience (LIKE) programme evaluation and analyzed which characteristics were essential to carry out the LIKE evaluation. This resulted in the Evaluation of Programmes in Complex Adaptive Systems (ENCOMPASS) framework.The ENCOMPASS framework includes five iterative stages: (1) adopting a system dynamics perspective on the overall evaluation design; (2) defining the system boundaries; (3) understanding the pre-existing system to inform system changes; (4) monitoring dynamic programme output at different system levels; and (5) measuring programme outcome and impact in terms of system changes.The value of ENCOMPASS lies in the integration of key characteristics from existing systems evaluation studies, as well as in its practical, applied focus. It can be employed in evaluating public health programmes in complex adaptive systems. Furthermore, ENCOMPASS provides guidance for the entire evaluation process, all the way from understanding the system to developing actions to change it and to measuring system changes. By the nature of systems thinking, the ENCOMPASS framework will likely evolve further over time, as the field expands with more completed studies.

Qualitative systems mapping for complex public health problems: A practical guide

Abstract: Systems mapping methods are increasingly used to study complex public health issues. Visualizing the causal relationships within a complex adaptive system allows for more than developing a holistic and multi-perspective overview of the situation. It is also a way of understanding the emergent, self-organizing dynamics of a system and how they can be influenced. This article describes a concrete approach for developing and analysing a systems map of a complex public health issue drawing on well-accepted methods from the field of social science while incorporating the principles of systems thinking and transdisciplinarity. Using our case study on HIV drug resistance in sub-Saharan Africa as an example, this article provides a practical guideline on how to map a public health problem as a complex adaptive system in order to uncover the drivers, feedback-loops and other dynamics behind the problem. Qualitative systems mapping can help researchers and policy makers to gain deeper insights in the root causes of the problem and identify complexity-informed intervention points.

Circular economy business models as resilient complex adaptive systems

Abstract: Broad consensus seems to have emerged on the circular economy as a plausible and desirable solution to build prosperity while respecting ecological boundaries. However, its implementation in industry is slow paced. Whilst the systemic nature of the innovation required and barriers to implementation in complex sustainability transitions partially explain why this is the case, reflecting on the contribution of the growing scholarly literature on circular business models to orient management practice is also relevant. In fact, despite the existence of a fairly voluminous scholarly literature on the subject, practitioners are either uncertain or struggling about how to implement circular economy strategies and models. Using an integrative research approach to theory building and drawing on systems theory, this article proposes a resilient complex adaptive system view of circular business models. The resulting framework is a stepping-stone to overcoming conceptual ambiguities and construct fallacies in the way circular business models are typified.

Understanding entrepreneurial ecosystems using complex adaptive systems theory: getting the big picture for economic development, practice, and policy

Abstract: ABSTRACT This paper demonstrates how the theory of complex adaptive systems (CAS) and entrepreneurial ecosystems (EE) can be synthesized to create a comprehensive framework for understanding EEs as comprising dynamic and diverse actors, factors, and interdependencies. We adapt four elements common to CAS and propose a context-specific framework for explaining EEs through people, place, purpose, and process to provide insights for policy, development, and regulatory interventions. Motivated by the challenge to develop a practical and parsimonious framework for comprehensive EE analysis, we present a case study using a CAS approach to illustrate the nature of EEs as dynamic, interconnected social systems and identify opportunities for economic development interventions. The study offers a novel framework for system-level EE analysis, and in doing so, it contributes to entrepreneurial economic development, research, policy, and practice.

A novel perspective of Australian primary care dietetics: Insights from an exploratory study using complex adaptive systems theory

Abstract: Abstract Aims Effective quality improvement strategies are essential to enhancing outcomes of dietetic care. Interventions informed by complex adaptive systems theory have demonstrated effectiveness in other healthcare settings. This study aimed to explore primary care dietetics practice using complex adaptive systems theory and to identify factors that individuals across the healthcare system can examine and address to improve the quality of dietetic care. Methods Qualitative analysis of semi‐structured interviews of healthcare consumers and professionals involved in the provision of dietetic care. Data collection and analysis was guided by a complexity‐informed conceptual framework. The Framework Method was used to code transcripts and identify themes describing primary care dietetics. Results Twenty‐three consumers and 26 primary care professionals participated. Participants described dietetic care as being delivered by individuals organised into formal and informal systems that were influenced by the wider environment, including legal, economic, and socio‐cultural systems. Dietitians described interactions with consumers as a learning opportunity and sought education, mentoring, or supervision to address knowledge and skill gaps. Relationships underpinned transfer of information between individuals. Conclusion Complex adaptive systems theory proved to be a useful conceptual framework for primary care dietetics. Factors identified at the macro (e.g., funding), meso (e.g., professional networks), and micro (e.g., consumer education) levels should be examined and addressed to improve the quality of dietetic care.

The Future of Burn Care From a Complexity Science Perspective

Abstract: Abstract Health care is undergoing a profound technological and digital transformation and has become increasingly complex. It is important for burns professionals and researchers to adapt to these developments which may require new ways of thinking and subsequent new strategies. As Einstein has put it: “We must learn to see the world anew.” The relatively new scientific discipline “Complexity science” can give more direction to this and is the metaphorical open door that should not go unnoticed in view of the burn care of the future. Complexity science studies “why the whole is more than the sum of the parts.” It studies how multiple separate components interact with each other and their environment and how these interactions lead to “behavior of the system.” Biological systems are always part of smaller and larger systems and exhibit the behavior of adaptivity, hence the name complex adaptive systems. From the perspective of complexity science, a severe burn injury is an extreme disruption of the “human body system.” But this disruption also applies to the systems at the organ and cellular levels. All these systems follow the principles of complex systems. Awareness of the scaling process at multilevel helps to understand and manage the complex situation when dealing with severe burn cases. This paper aims to create awareness of the concept of complexity and to demonstrate the value and possibilities of complexity science methods and tools for the future of burn care through examples from preclinical, clinical, and organizational perspectives in burn care.

Enabling educational innovation through complexity leadership? Perspectives from four Dutch universities

Abstract: Abstract Leadership in higher can influence the structurally embedding of educational technologies in higher education institutions. However, HEIs are complex pluralistic organizational environments with loosely coupled systems, diffused power and goal ambiguity which makes governance of educational innovations a wicked problem in which they have to balance dynamic complex interactions while also setting out a clear vision and enacting this vision towards organizational goals. This paper analyses four qualitative case studies with a focus on the choices made by leaders in four Dutch universities that aim to contribute to organisational educational innovation. We investigated the data through the lens of complexity leadership theory in which three types of leadership play an important role: administrative leadership (i.e. top-down oriented), adaptive leadership (i.e. bottom-up oriented) and enabling leadership that emerges as a leadership type between administrative and adaptive leadership and contributes to governing innovation in complex environments. This study sheds light on how, in the case of HEIs as complex environments, leaders made strategic choices and followed up on them to enable the innovative potential of the organisation.

Simulation-Based Optimization: Implications of Complex Adaptive Systems and Deep Uncertainty

Abstract: Within the modeling and simulation community, simulation-based optimization has often been successfully used to improve productivity and business processes. However, the increased importance of using simulation to better understand complex adaptive systems and address operations research questions characterized by deep uncertainty, such as the need for policy support within socio-technical systems, leads to the necessity to revisit the way simulation can be applied in this new area. Similar observations can be made for complex adaptive systems that constantly change their behavior, which is reflected in a continually changing solution space. Deep uncertainty describes problems with inadequate or incomplete information about the system and the outcomes of interest. Complex adaptive systems under deep uncertainty must integrate the search for robust solutions by conducting exploratory modeling and analysis. This article visits both domains, shows what the new challenges are, and provides a framework to apply methods from operational research and complexity science to address them. With such extensions, simulation-based approaches will be able to support these new areas as well, although optimal solutions may no longer be obtainable. Instead, robust and sufficient solutions will become the objective of optimization processes.

A Perturbed Peace: Applying Complexity Theory to UN Peacekeeping

Abstract: ABSTRACT This article explores the application of complexity theory to UN peacekeeping. To date, peacekeeping has been dominated by linear models of change, assuming that conflict settings can be addressed by elite-driven peace processes, gradual improvements to state institutional capacity, and development programming. However, this article argues that complexity theory offers a far more accurate and useful lens through which to view the work of peacekeeping: conflict settings represent complex, interdependent socio-political systems with emergent qualities giving them the capacity to self-organize via feedback loops and other adaptive activity. Self-organization means such systems are highly resistant to attempts to change behaviour via top-down or input-output approaches. In fact, peacekeeping itself is endogenous to the systems it is trying to change, often displaying the same kinds of self-organization typical of complex systems elsewhere. Drawing on experience working and conducting fieldwork in the UN peacekeping mission in Democratic Republic of the Congo, this article argues that UN peacekeeping operations should view themselves as actors within the complex conflict ecosystem, looking to enable transformational change from within, rather than impose liberal Western models from without.

On the Timescales of Embodied Intelligence for Autonomous Adaptive Systems

Abstract: Embodiment is a crucial concept for the autonomy and adaptivity of systems working in the physical world with high degrees of uncertainty and complexity. The physical bodies of autonomous adaptive systems heavily influence the information flow from the environment to the central processing (and vice versa), requiring us to consider the full triad of brain, body, and environment to investigate intelligent behavior. This article provides a structured review of embodied intelligence with a special emphasis on the concept of timescales and their role in self-organization and the emergence of complex behavior. We classify embodied interactions into three types—cross-timescale matching, separation, and nontemporal sequences—and discuss how these interactions were studied in the past as well as how they can contribute to the systematic investigation of complex autonomous and adaptive systems in both biological and artificial entities. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Toward a non‐organizational theory of human resource management? A complex adaptive systems perspective on the human resource management ecosystem in (con)temporary organizing

Abstract: The emergence of the temporary organization has ushered in a new logic of organizing accompanied by paradigm-shifting challenges with respect to how the evolving nature of work, workers, and collective effort are to be understood. To capture the complexity inherent in this new order, and to broaden our focus from the organization to the enfolding ecosystem within which temporary organizing must be situated and understood, we engage in problematization to develop a multi-level framework for theorizing the contemporary human resource management ecosystem. Curating insights from complexity science, we conceptualize this ecosystem as a complex adaptive one and we propose a framework that integrates key structural (open boundaries and relational constitution), emergent (contextual and complex causality), and temporal (dynamic and adaptive) properties. To deepen lines of inquiry around these defining elements, we advance a series of propositions for testing, and we outline a range of theoretical, methodological, and practical implications that arise from our work.

Implications of Panarchy for ecosystem service research: the role of system dynamics in service delivery

Abstract: . Panarchy illustrates the dynamic nature of social-ecological systems and their nestedness and interconnectedness through time and space. Although there have been great advances in ecosystem service (ES) research, it has only rarely integrated dynamic interaction of components in social-ecological systems (SES). We explore how Panarchy theory, and especially its detailed reflections on change and system dynamics, could help ES research to better capture the dynamics of change into its fundamental assumptions. We do this by outlining four main conclusions of Panarchy theory: multiple states, the adaptive cycle, variances of the adaptive cycle, and change and persistence for sustainability. We illustrate how these aspects can be incorporated in ES research and conclude with recommendations for the field.

Agent-Based Simulation for Service and Social Systems and Large-Scale Social Simulation Framework

Abstract: Because of the dynamic and heterogeneous interactions among human beings with their bounded rationality, a service system discussed in Service Science, Management, and Engineering (SSME) is recognized as a complex adaptive system to which quantitative scientific analysis is difficult to apply. In this chapter, we introduce a computational approach for such complex adaptive systems called agent-based simulation. Since the 1990s, agent-based simulation has gained significance as a tool to reproduce complex stock market interactions by modeling human traders as software agents. Recently, agent-based social simulations are utilized to support the decision-making of city planners for various real social issues. For this purpose, we have developed a large-scale social simulation framework “X10-based Agent Simulation on Distributed Infrastructure (XASDI).” In this chapter, we will introduce our earlier work with a small number of agents and then describe the large-scale social simulation framework and its applications.KeywordsAgent-based SimulationSocial simulationXASDI frameworkService systemSSME

Navigating adaptive cycles to understand destination complex evolutionary process

Abstract: There is a recent surge to unfold the tourism destination's intrinsic nature as a complex adaptive system, such as the dynamic and scale interactions among tourism system components and its environment. As the world gets more uncertain, it becomes more critical to understand how dynamic and complex interactions shape the destination's resilience and its evolution process. Yet, such is under-explored. Taking the East Suburb Coconut Trees scenic area in Hainan (ESCT), China, as a case, this study adopts adaptive cycle heuristics to shed light on the critical evolution mechanisms. This study shows that ESCT had undergone two adaptive cycles, suffered three shocks, and experienced interaction mode from external enterprises-led to interdependent development mode and, finally, local-oriented mode. During this process, the destination's resilience changed from vulnerable to absorptive and, finally, rigid. There is no reorganization stage between the two cycles, which resulted in a limited increase in the destination's resilience. The increasing local involvement built absorptive capability but also locked the destination into a rigidity trap in the long term. This study is the first to reveal the role of resilience in understanding complex system interactions and the destination evolution process. Practical implications for resilient destination management are provided.

African primary healthcare as complex adaptive system.

Abstract: Bureaucratic African governments need to trust their health workers and populations on the way to the Africa Agenda 2063. Small defined populations cared for by a team with an appropriate mix of healthcare workers (from public and private sectors) and delivered in a comprehensive, continuous, coordinated manner can be the complex adaptive system to deliver better PHC and health for all in Africa.

Resilience and complex adaptive systems:a perspective on healthcare

Abstract: Purpose. The term “healthcare system resilience” is becoming topical in policy planning documents around the world, increasingly in the context of the COVID-19 pandemic. This research aimed to explore the role of the contextual framework in the research on resilience and prevailing aspects of the healthcare system’s resilience. Design / methodology / approach. The research hypothesised on the increasing relevance of the concept of resilience in the healthcare system as demonstrated by scientific literature; on determining elements that characterise the interrelationship between the domains of the healthcare system and the concept of resilience; and on the role of the contextual framework in creating an awareness of the concept of resilience in the healthcare system. The hypotheses were verified by the literature review on the PubMed, Web of Science, and Scopus databases. Findings. The concept of resilience was introduced to the healthcare system literature from the ecological sciences through an increased understanding of the healthcare system as a complex adaptive system (CAS). The perception of the nature of the healthcare system in the context of a CAS, viewing it as a complex, dynamic part of the socio-economic system, operating in circumstances of high uncertainty, provides additional opportunities for understanding the healthcare system’s functioning, governance and decision-making. Originality / value. This study identified a research gap in the practical implementation of the CAS approach in the healthcare system on the highest level of governance. A CAS contains a multitude of characteristics and elements that could assist in attaining a more nuanced understanding of healthcare system resilience. Significantly, the inherent characteristics of a CAS, such as flexibility and an adaptive nature, which seem to undermine the stability of the system, actually create the core of this system’s resilience, and these aspects merit increased attention. Further research could be devoted to the investigation of healthcare system resilience in the context of healthcare system reforms. Keywords: healthcare system, contextual framework, organization, governance, ecological approach, networks

Knowledge Complexity and Collective Intelligence Development in Technology Based-Firms

Abstract: This document addresses the issue of collective intelligence, complex knowledge, and complexity theory applied to technology-based organizations. For this, a review of the literature on the subject of complexity theory, complex knowledge, collective intelligence, and technology-based organizations is made. An analysis of four approaches to complexity theory that help improve the study of organizations from the consideration of turbulent and changing environments that require a high capacity for adaptation, innovation, and rapid assimilation of change will be developed. Finally, there is a need to innovate in the study of companies and to consider them epistemologically as independent entities that make up a complex adaptive system and that, in essence, are grouped together to consolidate their ability to adapt and adjust to market change and survival.

Learning and Adaptation in Polycentric Transport Governance: The Case of the Dutch Brabant Accessibility Agenda

Abstract: The future of urban-regional transport crucially depends on the ability of transport governance systems to adapt. Polycentric theory claims that the presence of polycentric attributes and conditions enables governance systems to learn and adapt. However, an analysis of the Dutch Brabant Accessibility Agenda shows that their presence says little about the adaptive capacity of transport governance systems because learning and adaptation are influenced by dependencies. To optimize the adaptive capacity of transport governance systems, it is therefore vital to acknowledge both the diverse ways in how they learn and adapt, and the dependencies that shape these processes.

Globalization as Adaptive Complexity: Learning from Failure

Abstract: Abstract Our modern global civilization has been facilitated by increasingly technologically-advanced, interconnected, and interdependent systems. These systems have been constructed at an ever-increasing scale and level of complexity without an awareness of the risky mechanisms inherent in their design. At first glance, one may find few similarities between our modern globalized present and ancient civilizations. When we see past civilizations as complex adaptive systems, however, we can begin to recognize patterns, structures, and dynamics that have remained consistent through the centuries. Mechanisms like tipping points, feedback loops, contagions, cascades, synchronous failures, and cycles that can be responsible for systemic collapse are fundamental characteristics of any complex adaptive system, and can therefore serve as an effective common denominator from which to examine collapses through the ages. We argue for an analytical framework that incorporates these systemic characteristics for the study of historical collapse with the belief that these common mechanisms will help illuminate and expose relevant vulnerabilities in historical systems. In the end, we hope to learn from past societies and civilizations and allow our modern systems to benefit from lessons of systemic failures that historians may share with us. We believe these insights could inform how we see our systemic vulnerabilities and help to build a more resilient future.

Transdisciplinary multistage system modeling: migrant entrepreneurship in the digital economy

Abstract: PurposeThe dynamics of modern life lead to societal changes that affect innovation systems. Entrepreneurship is an important driver for fostering adaptive capacities of innovation systems in such uncertain and complex environments. This study aims to gain a detailed understanding of how (innovative) entrepreneurship can promote innovation systems, leading to more sustainable societies. A particular focus is placed on migrant entrepreneurship in the digital economy, as a concrete implication of innovative entrepreneurship, and its role within the Austrian innovation system.Design/methodology/approachIn order to develop a shared system understanding from a scientific and practical perspective, transdisciplinary multistage system modeling was applied. The transdisciplinary discourse involved 14 experts, and several system models were iteratively co-created during the course of the research.FindingsThe main result demonstrates the interrelationship between the innovation system and migrant entrepreneurship in the digital economy, which includes six core reinforcing loops: (1) the mindsets of entrepreneurs, (2) the role of international collaboration, (3) the role of entrepreneurial education, the financial sphere in regard to (4) government and (5) private funding, as well as (6) the impact of formal procedures.Originality/valueThe authors present and discuss the relational dynamics of this complex phenomenon as well as the applied transdisciplinary approach, with the aim of identifying a potential way to improve the sustainable impact of (migrant) entrepreneurship considering the case of the Austrian innovation system.

An integrated complex adaptive governmental policy response to cyberthreats

Abstract: This article analyzes the policy options available to governments for addressing the very costly economic impacts of cybersecurity threats. It contributes to complexity thinking in public policy. Complexity involves self-organization, emergence, feedback loops, and adaptation. We show that these are present with cyberthreats. In contrast to plans that involve a series of linear steps to a specific outcome, complexity thinking recommends adaptive design, which creates processes that involve coordinated decentralized capacity for experimentation and resilience. These are illustrated with an examination of the 2007 nation-wide cyberattack on Estonia and the lessons learned from this attack.

Applying complex adaptive systems and risk society theory to understand energy transitions

Abstract: • South Australia is leading low carbon energy transitions in Australia. • Socio-technical transitions are complex, non-linear and follow multiple adaptive pathways. • Complex adaptive systems and risk society theory can be integrated to better understand transitions. • Bold leadership and innovative policy are required to navigate transitions in a reflexive modernity. • Governance can exploit crises to justify transition policy in response to future risk and uncertainty. Renewable energy transitions are occurring across the globe in response to climate change. Such socio-technical transitions are complex and non-linear. They require bold leadership and innovative policy, both in response to environmental risk and to navigate political, technical and socio-economic conditions. This paper integrates complex adaptive systems and risk society theory to inform a discussion on regional socio-technical transitions. South Australia is forging its own adaptive pathway, and in doing so, is leading energy transitions in Australia. Utilising the complex adaptive cycle to frame the state's renewable energy transition, the path can be seen to be evolving from a simple first modernity to a multi-dimensional second modernity. Socio-technical transitions are partly a by-product of responses to risk. While there is no single map for navigating societal transitions, this paper proposes that risk, in the context of risk society theory, is an important guiding dimension for understanding transformational change in socio-technical systems.

Viewing the global health system as a complex adaptive system – implications for research and practice

Abstract: The global health system (GHS) is ill-equipped to deal with the increasing number of transnational challenges. The GHS needs reform to enhance global resilience to future risks to health. In this article we argue that the starting point for any reform must be conceptualizing and studying the GHS as a complex adaptive system (CAS) with a large and escalating number of interconnected global health actors that learn and adapt their behaviours in response to each other and changes in their environment. The GHS can be viewed as a multi-scalar, nested health system comprising all national health systems together with the global health architecture, in which behaviours are influenced by cross-scale interactions. However, current methods cannot adequately capture the dynamism or complexity of the GHS or quantify the effects of challenges or potential reform options. We provide an overview of a selection of systems thinking and complexity science methods available to researchers and highlight the numerous policy insights their application could yield. We also discuss the challenges for researchers of applying these methods and for policy makers of digesting and acting upon them. We encourage application of a CAS approach to GHS research and policy making to help bolster resilience to future risks that transcend national boundaries and system scales.