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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

Decisions taken during the early design of adaptive façades involving kinetic, active and responsive envelope for complex commercial buildings have a substantial effect on inclusive building functioning and the comfort level of inhabitants. This study aims to present the application of an analytic network process (ANP) model indicating the order of priority for high performance criteria that must be taken into account in the assessment of the performance of adaptive façade systems for complex commercial buildings.

The nominal group technique (NGT) stimulating and refining group judgments are used to find and categorize relevant high performance attributes of the adaptive façade systems and their relative pair-wise significance scores. An ANP model is applied to prioritize these high performance objectives and criteria for the adaptive façade systems.

Embodied energy and CO₂ emission, sustainability, energy saving, daylight and operation maintenance were as the most likely and crucial high performance criteria. The criteria and the weights presented in this study could be used as guidelines for evaluating the performance of adaptive façade systems for commercial buildings in planning and design phases.

This research primarily provides the required actions and evaluations for design managers in accomplishing a high performance adaptive façade system, with the support of an ANP method. Before beginning the adaptive façade system of a building design process, the design manager must determine the significance of each of these attributes as high performance primacies will affect the results all through the entire design process.

In this research, a relatively innovative, systematic and practical approach is proposed to sustain the decision-making procedure for evaluation of the high performance criteria of adaptive façade systems in complex commercial buildings.

The purpose of this paper is to investigate necessary cybernetic structures that allow complex adaptive systems to develop system‐specific behavior.

Following Holland's concept of “adaptive agents”, it is argued that the development of system‐specific forms of goal‐oriented behavior requires a decision to deviate from some default behavior and to trigger any new one, and a mechanism to evaluate the goal‐orientation of this new behavior. Using a functional approach cybernetic structures are developed that are able to carry out these two tasks. Then these structures are added as subsystems to the structure of a simple one‐level adaptive system.

The paper finds that a hierarchical adaptive system can recognize with a higher level controller, if lower level decisions lead to an insufficient degree of goal‐approximation and can use preprogrammed higher level decisions to intervene on the lower level to trigger new system‐specific actions. An additional controller can evaluate the “success” achieved with these new actions and can select the “best” actions found, i.e. the behavior leading to the highest degree of goal‐approximation.

The paper shows necessary cybernetic structures that are seen as core of all complex adaptive systems able to develop system‐specific behavior. It is suggested that the underlying basic concept of “success” understood as a degree of goal‐approximation holds for any adaptive, learning or otherwise improving endeavor.

The paper is the second in a series of three on a cybernetic theory distinguishing system capable of preprogrammed adaptation, system‐specific adaptation, and learning. It shows necessary cybernetic structures that a system can develop individual actions.

The purpose of this paper is to deepen the understanding of adaptive governance, which is advocated for as a manner to deal with dramatic changes in society and/or environment. To re-think the possible contributions of organizations and organization theory, to adaptive governance.

Based on social systems theory this study makes a distinction between “governance organizations” and “governance communities.” Organizations are conceptualized as the decision machines which organize and (co-)steer governance. Communities are seen as the social environments against which the governance system orients its operations. This study considers the adaptive mechanisms of organizations and reflect on the roles of organizations to enhance adaptive governance in communities and societies.

Diverse types of organizations can link or couple in different ways to communities in their social environment. Such links can enhance the coordinative capacity of the governance system and can also spur innovation to enable adaptation. Yet, linking with communities can also slow down responses to change and complexify the processes of deliberation in governance. Not all adaptive mechanisms available to organizations can be used in communicating with communities or can be institutionalized, but the continuous innovation in the field of organizations can inspire continuous testing of small-scale adaptive mechanisms at higher levels. Society can thus enhance its adaptive capacity by managing the role of organizations.

The harnessing of insights in organization theory and systems theory for improving understanding of adaptive governance. The finding that both experiment and coordination at societal level are needed, toward adaptive governance, and that organizations can contribute to both.

The purpose of this paper is to investigate different cybernetic structures of simple adaptive systems and their cognitive and behavioral options.

Using a functional approach, two basic forms of adaptive systems are constructed, which process data on one level respectively two hierarchical levels. Based on that complex combinations of such one‐level and hierarchical structures are investigated.

It is shown how different cybernetic structures enable simple forms of adaptive behavior. A basic blueprint for the controller structure of animal species is derived from them, with a simple “brain” and a unit for “motion control” as subsystems. Four paths of evolutionary growth are identified that allow a widely independent development of these subsystems.

The paper provides a typology of simple adaptive systems and discusses the forms of behavior they can develop with preprogrammed – i.e. evolutionary given or technically programmed – decision‐rules. It discusses the requirements that these decision‐rules can form models enabling adaptive behavior. It is suggested that these requirements hold for the models of more complex adaptive systems, too.

This paper is the first in a series of three on a cybernetic theory distinguishing systems able of preprogrammed adaptation, system‐specific adaptation, and learning.

The purpose of this paper is to build a bridge between climate change adaptation and spatial planning and design. It aims to develop a spatial planning framework in which the properties of climate adaptation and spatial planning are unified.

Adaptive and dynamical approaches in spatial planning literature are studied and climate adaptation properties are defined in a way they can be used in a spatial planning framework. The climate adaptation properties and spatial planning features are aggregated in coherent groups and used to construct the spatial planning framework, which subsequently has been tested to design a climate adaptive region.

The paper concludes that the majority of spatial planning methods do not include adaptive or dynamic strategies derived from complex adaptive systems theory, such as adaptive capacity or vulnerability. If these complex adaptive systems properties are spatially defined and aggregated in a coherent set of spatial groups, they can form a spatial planning framework for climate adaptation. Each of these groups has a specific time dimension and can be linked to a specific spatial planning “layer”. The set of (five) layers form the spatial planning framework, which can be used as a methodology to design a climate adaptive region.

Previous research did not connect the complex issue of climate change with spatial planning. Many frameworks are developed in climate change research but are generally not aiming to meet the needs of spatial planning. This article forms the first attempt to develop a spatial planning framework, in which non‐linear and dynamical processes, such as climate adaptation, is included.

This article proposes an adaptive strategy for managing knowledge in complex organizations. Specifically, this article aims to extend understanding in the field of knowledge management (KM) by examining how an adaptive strategy for managing knowledge can help organizations become innovative and build dynamic capabilities.

Literature on complexity theory and KM is reviewed to propose the development of an adaptive strategy that will assist organization in managing knowledge and becoming innovative. The paper is structured around the following constructs: complexity theory, complex adaptive systems, and KM.

A link between an adaptive strategy for managing knowledge, innovation and dynamic capability is established. The central proposition of the article is the organizations that follow adaptive complex processes for managing knowledge are better able to compete in the market today.

This article extends prior research on KM by proposing complexity theory as a framework for establishing adaptive strategies for managing knowledge and fostering innovation.

With the dramatic environmental changes and fierce competition that organizations are faced with today, managing knowledge becomes critical for driving creativity and adapting to changing markets. Organizations lack direction on how best to develop an adaptive strategy for managing knowledge. The revelation of adaptive processes for managing knowledge in complex systems can lead to more effective KM practices and a higher rate of creativity and flexibility.

The study answers recent calls for defining processes for the second generation of KM that shift focus from the codification and transfer of knowledge to the creation of new knowledge. Although previous studies have established a link between complex adaptive systems and KM, this study takes it one step further in defining an integrative strategy for the creation of knowledge based on the processes of complex adaptive systems. The paper provides a foundation for future studies to test the causal relationship between adaptive processes for knowledge creation and innovation.

The purpose of this paper is to review the use of adaptive systems in education. It is intended to be a useful introduction for the non-specialist reader.

A distinction is made between intelligent tutoring systems (ITSs) and adaptive hypermedia systems (AHSs). The two kinds of system are defined, compared and contrasted. Examples of the implementation of the two kinds of system are included.

Similarities and differences between the two kinds of system are highlighted. A conceptual unification is proposed based on the architecture of Course Assembly System and Tutorial Environment, a seminal prototype learning environment developed by Pask and Scott in the 1970s as an application of Pask’s conversation theory.

The architecture shows how the key aspects of ITSs and AHSs can be combined to complement each other. It is intended to be an original contribution that is of particular interest for the specialist reader.

The purpose of this paper is to present an adaptive neuro‐sliding mode control scheme for uncertain nonlinear systems with Lyapunov approach.

The paper focuses on neural network (NN) adaptive control for nonlinear systems in the presence of parametric uncertainties. The plant model structure is represented by a NNs system. The essential idea of the online parametric estimation of the plant model is based on a comparison of the measured state with the estimated one. The proposed adaptive neural controller takes advantages of both the sliding mode control and proportional integral (PI) control. The chattering phenomenon is attenuated and robust performances are ensured. Based on Lyapunov stability theorem, the proposed adaptive neural control system can guarantee the stability of the whole closed‐loop system and obtain good‐tracking performances. Adaptive laws are proposed to adjust the free parameters of the neural models.

Simulation results show that the adaptive neuro‐sliding mode control approach works satisfactorily for nonlinear systems in the presence of parametric uncertainties.

The proposed adaptive neuro‐sliding mode control approach is a mixture of classical neural controller with a supervisory controller. The PI controller is used to attenuate the chattering phenomena. Based on the Lyapunov stability theorem, it is rigorously proved that the stability of the whole closed‐loop system is ensured and the tracking performance is achieved.

The decline of the motoric and cognitive functions of the elderly and the high risk of changes in their vital signs lead to some disabilities that inconvenience them. This paper aims to assist the elderly in their daily lives through personalized and seamless technologies.

The authors developed a personalized adaptive system for elderly care in a smart home using a fuzzy inference system (FIS), which consists of a predictive positioning system, reflexive alert system and adaptive conditioning system. Reflexive sensing is obtained from a body sensor and environmental sensor networks. Three methods comprising the FIS generation algorithm – fuzzy subtractive clustering (FSC), grid partitioning and fuzzy c-means clustering (FCM) – were compared to obtain the best prediction accuracy.

The results of the experiment showed that FSC produced the best F₁-score (96 per cent positioning accuracy, 94 per cent reflexive alert accuracy, 96 per cent air conditioning accuracy and 95 per cent lighting conditioning accuracy), whereas others failed to predict some classes and had lower validation accuracy results. Therefore, it is concluded that FSC is the best FIS generation method for our proposed system.

Personalized and seamless technologies for elderly implies life-share awareness, stakeholder awareness and community awareness.

This paper presents a model of personalized adaptive system based on their preferences and medical reference, which consists of a predictive positioning system, reflexive alert system and adaptive conditioning system.