Complex adaptive system

About: Complex adaptive system is a research topic. Over the lifetime, 3190 publications have been published within this topic receiving 111947 citations. The topic is also known as: Complex adaptive system, CAS.

Supply chain resilience: an adaptive cycle approach

Abstract: The purpose of this paper is to develop a conceptual framework for extending an understanding of resilience in complex adaptive system (CAS) such as supply chains using the adaptive cycle framework. The adaptive cycle framework may help explain change and the long term dynamics and resilience in supply chain networks. Adaptive cycles assume that dynamic systems such as supply chain networks go through stages of growth, development, collapse and reorientation. Adaptive cycles suggest that the resilience of a complex adaptive system such as supply chains are not fixed but expand and contract over time and resilience requires such systems to navigate each of the cycles’ four stages successfully.,This research uses the adaptive cycle framework to explain supply chain resilience (SCRES). It explores the phases of the adaptive cycle, its pathologies and key properties and links these to competences and behaviors that are important for system and SCRES. The study develops a conceptual framework linking adaptive cycles to SCRES. The goal is to extend dynamic theories of SCRES by borrowing from the adaptive cycle framework. We review the literature on the adaptive cycle framework, its properties and link these to SCRES.,The key insight is that the adaptive cycle concept can broaden our understanding of SCRES beyond focal scales, including cross-scale resilience. As a framework, the adaptive cycle can explain the mechanisms that support or prevent resilience in supply chains. Adaptive cycles may also give us new insights into the sort of competences required to avoid stagnation, promote system renewal as resilience expands and contracts over time.,The adaptive cycle may move our discussion of resilience beyond engineering and ecological resilience to include evolutionary resilience. While the first two presently dominates our theorizing on SCRES, evolutionary resilience may be more insightful than both are. Adaptive cycles capture the idea of change, adaptation and transformation and allow us to explore cross-scale resilience.,Knowing how to prepare for and overcoming key pathologies associated with each stage of the adaptive cycle can broaden our repertoire of strategies for managing SCRES across time. Human agency is important for preventing systems from crossing critical thresholds into imminent collapse. More importantly, disruptions may present an opportunity for innovation and renewal for building more resilience supply chains.,This research is one of the few studies that have applied the adaptive cycle concept to SCRES and extends our understanding of the dynamic structure of SCRES

Implementation of Integrated Care in Singapore: A Complex Adaptive System Perspective.

Abstract: Background: Integrated care that focuses on organising healthcare services around people and their communities rather than their diseases is promoted as the strategy to overcome the challenges associated with growing complexity in healthcare needs, demand for healthcare services and inadequate supply of services due to fragmentation in the provision of services. While conceptually appears to be simple, integrated care is made up of multicomponent delivery strategies targeting various levels of the healthcare system while engaging various stakeholders in their execution. Methods: We applied the complex adaptive system (CAS) perspective to two different initiatives that exemplify approaches towards integrating care in Singapore: the Regional Health System (RHS) model, implemented across healthcare institutions at the national level, and CARITAS Integrated Dementia Care implemented in the northern region of Singapore. We adopted an inductive approach in our analysis in which we studied the RHS and CARITAS Integrated Dementia Care according to the components of the CAS. We applied the typical characteristics of CAS: (i) diverse, interdependent and semi-autonomous actors (ii) self-organizing capacity and simple rules (iii) relationship with the bigger system, emergent behaviour and non-linearity in our analysis of key drivers behind the implementation of both the RHS and CARITAS integrated dementia care. Results: By considering the RHS and CARITAS as whole networks each comprising of interacting and adaptive components instead of separate entities within a bigger system, the CAS provided a new mind-set in surfacing issues associated to the implementation of these integrated care networks. In addition to important actors, systems, it informed understanding of relationships and dependencies between different parts of the network – revealing the lack of homogeneity, conformity and difficulties in designing any optimal system in advance given the many moving parts. Conclusions: Drawing on the two examples of integrated care networks, this paper highlights the significance of effective collaboration built on a common focus, responsiveness to emergent behaviours, simple rules, the ability to self-organize and adapt in response to unexpected situations in further development of integrated care in the Singapore context and beyond.

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.

Ecological Dynamics: A Theoretical Framework for Understanding Sport Performance, Physical Education and Physical Activity

Abstract: This paper focuses on the role of ecological dynamics as a theoretical framework for analysing performance of athletes and sports teams as complex adaptive systems. It combines key concepts from ecological psychology and nonlinear dynamical system theory, seeking to enhance understanding of performance and learning contexts in sport, to aid the acquisition and transfer of adaptive human behaviours. In ecological psychology the continuous regulation of human behaviour is predicated on the role of information that emerges from the individual–environment system to guide activity. The information sources that constrain performance behaviours are affordances, which provide invitations for action offered by each individual’s perception of functional relations with a performance environment. This information-based approach has been enhanced with the integration of tools and concepts from nonlinear dynamics to explain how information is cyclically related to the dynamics of a performance environment. Dynamical systems theory addresses the emergence of coordination tendencies that exist between and within components and levels of complex neurobiological systems. Ecological dynamics identifies key properties of expertise in sport predicated on the performer–environment relationship as the appropriate scale of analysis. This paper introduces the key properties of expert movement systems that include multi- and meta-stability, the functional role of adaptive movement variability, redundancy, degeneracy and the attunement to affordances. Additionally, we discuss the concept of representative design, which in an ecological dynamics framework underpins the organisation of experimental and learning environments so that observations and acquired skills can be linked to emergent functional behaviours in a specific performance context.