Mapping Artificial Immune Systems into Learning Classifier Systems

Integrated care in the emergency department: A complex adaptive systems perspective

ABSTRACTSupply networks are composed of large numbers of firms from multiple interrelated industries. Such networks are subject to shifting strategies and objectives within a dynamic environment. In recent years, when faced with a dynamic environment, several disciplines have adopted the Complex Adaptive System (CAS) perspective to gain insights into important issues within their domains of study. Research investigations in the field of supply networks have also begun examining the merits of complexity theory and the CAS perspective. In this article, we bring the applicability of complexity theory and CAS into sharper focus, highlighting its potential for integrating existing supply chain management (SCM) research into a structured body of knowledge while also providing a framework for generating, validating, and refining new theories relevant to real‐world supply networks. We suggest several potential research questions to emphasize how a CAS perspective can help in enriching the SCM discipline. We propose that the SCM research community adopt such a dynamic and systems‐level orientation that brings to the fore the adaptivity of firms and the complexity of their interrelations that are often inherent in supply networks.

As organizations are becoming more diverse in terms of the sociological and psychological characteristics of their workforces, diversity emerges as an important issue in contemporary work settings. As a result, workforce diversity research has evolved significantly over the last decades. However, today there is still a consensus that the variegated contemporary organizational settings require scholars and practitioners alike to develop a more nuanced understanding of diverse employees. In this vein, this conceptual paper examines workplace diversity through a complex adaptive systems (CAS) perspective. We introduce the concept of protean diversity as an application of CAS to diversity research in order to explain how individuals act on their differences through the manifestation of personal and interpersonal dynamics. Our work contributes to organizational theory and practice by offering new ways to identify both research methods and managing techniques that scholars and practitioners may apply to study and manage diverse individuals as CAS.

A transition towards circular manufacturing systems (CMS) has brought awareness of untapped economic and environmental benefits for the manufacturing industry. Conventional manufacturing systems already present a high level of complexity in terms of physical flows of materials and products as well as information and financial flows linked to them. Closing the loop of materials and products through multiple lifecycles, as proposed in CMS, increases this complexity manifold. To support practitioners in implementing CMS through enhanced decision-making, this research studies CMS from a complex adaptive systems (CAS) perspective and proposes to exploit methods and tools used in the study of CAS to characterise, model and analyse CMS. By viewing CMS as CAS composed of autonomous, interacting agents, this research proposes a multi-method model architecture for modelling and simulating CMS. The different CMS stakeholders are modelled individually as autonomous agents by integrating agent-based, discrete-event, and/or system dynamics modules within each agent to capture their diverse and heterogeneous nature. The applicability of the proposed multi-method approach is illustrated through a case study of a white goods manufacturing company implementing CMS in practice. This case study shows the relevance and feasibility of the proposed multi-method approach as a decision support tool for the systemic exploration and quantification of CMS. It also shows how a transition towards CMS necessitates a lifecycle approach in terms of costs, revenues and environmental impacts to identify hotspots and, therefore, design circular systems that are viable in both economic and environmental terms. In fact, the analyses of the simulation results indicate how decisions in terms of business models, product design, and supply chain might affect the CMS performance of the case company. For instance, implementing a service-based model led to a high number of usecycles (on average six usecycles per washing machine), which, in turn, led to high lifecycle costs and emissions due to more frequent transportation and recovery operations. Similarly, the deployment of long-lasting washing machines, which is a core principle of CMS, led to high manufacturing costs. Due to the high initial costs and a time mismatch between revenues and costs in the service-based model, it required a longer time for the company to reach the break-even point (approximately 23 months). Overall, the case study shows that multi-method simulation modelling can provide decision-making support for a successful implementation of CMS.

Abstract: Evaluation designs that can capture the complexity of health promotion (HP) interventions are needed. Our objective was to assess if such evaluations use a Complex Adaptive Systems (CAS) perspective, by using a scoping review of evaluations of HP interventions concerning alcohol and tobacco use in the peer-reviewed (PR) and grey literature (GL). We developed indicator questions to assess CAS aspects. Our study revealed that none of the 45 PR and 9 GL evaluations that we reviewed explicitly used a CAS perspective; however, most indirectly assessed complexity aspects. Our indicator questions are a step toward addressing the challenges of the practical application of a CAS perspective.

IntroductionDespite over two decades of international experience and research on health systems integration, integrated care has not developed widely. We hypothesized that part of the problem may lie in how we conceptualize the integration process and the complex systems within which integrated care is enacted. This study aims to contribute to discourse regarding the relevance and utility of a complex-adaptive systems (CAS) perspective on integrated care.MethodsIn the Canadian province of Ontario, government mandated the development of fourteen Local Health Integration Networks in 2006. Against the backdrop of these efforts to integrate care, we collected focus group data from a diverse sample of healthcare professionals in the Greater Toronto Area using convenience and snowball sampling. A semi-structured interview guide was used to elicit participant views and experiences of health systems integration. We use a CAS framework to describe and analyze the data, and to assess the theoretical fit of a CAS perspective with the dominant themes in participant responses.ResultsOur findings indicate that integration is challenged by system complexity, weak ties and poor alignment among professionals and organizations, a lack of funding incentives to support collaborative work, and a bureaucratic environment based on a command and control approach to management. Using a CAS framework, we identified several characteristics of CAS in our data, including diverse, interdependent and semi-autonomous actors; embedded co-evolutionary systems; emergent behaviours and non-linearity; and self-organizing capacity.Discussion and conclusionOne possible explanation for the lack of systems change towards integration is that we have failed to treat the healthcare system as complex-adaptive. The data suggest that future integration initiatives must be anchored in a CAS perspective, and focus on building the system’s capacity to self-organize. We conclude that integrating care requires policies and management practices that promote system awareness, relationship-building and information-sharing, and that recognize change as an evolving learning process rather than a series of programmatic steps.

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.

In this paper natural immune system and artificial immune system are described. Natural immune system is an example of evolutionary learning mechanism which possesses a content addressable memory and the ability to forget little-used information, it is highly complicated and appears to be precisely turned to the problem of detecting and eliminating infection. A novel information processing system inspired by immune system of human and other animals, the artificial immune system is introduced in this paper, AIS is a computational system designed on the principles of natural immune system, which is highly distributed, adaptive and diverse system. AIS research, being interdisciplinary, demands significant knowledge of immunology and computational science. Due to the different in the nature of two fields, researchers in either field face difficulties in having mutual understanding and effectively contributing for AIS research. The paper reviews the mechanism of immune system, the basis of artificial immune system, its development history, content of research and Immune Engineering which is applied in processing control. And a major method of AIS is described, so that it explains to how to set up artificial immune network and system models. The AIS is an example of a system developed around the current understanding of the immune system. It has proved artificial immune system can capture the basic elements of the immune system and exhibit some of its chief characteristics. Through this paper, we know it is more suitable than simulated annealing and genetic algorithms for solving problem. At last, the disadvantage of AIS and the development tendency are discussed.

Despite efforts to control fraud in public assistance programs, the perception and realities of the problem persist. Serious barriers related to data collection and research methods impede the understanding of how and why fraud occurs, thereby limiting options for improving program integrity. This article argues that based on a complex adaptive systems (CAS) perspective, social welfare fraud can be understood as a collective outcome emerging from repeated interactions among stakeholders during the routinized business processes of public assistance programs. While dealing with fraud, great attention must be paid to how it occurs and persists, not just how serious the problem is or who commits these crimes.

PurposeBlockchain is a distributed ledger technology that uses cryptography to ensure transmission and access security, which provides solutions to numerous challenges to complex supply networks. The purpose of this paper is to empirically test the impact of blockchain implementation on shareholder value varying from internal and external complexity from the complex adaptive systems (CASs) perspective. It further explores how business diversification, supply chain (SC) concentration and environmental complexity affect the relationship between blockchain implementation and shareholder value.Design/methodology/approachBased on 138 blockchain implementation announcements of listed companies on the Chinese A-share stock market, the authors use event study methodology to evaluate the impact of blockchain implementation on shareholder value.FindingsThe results show that blockchain implementation has a positive impact on shareholder value, and this impact will be moderated by business diversification, SC concentration and environmental complexity. In addition, environmental complexity exerts a moderating effect on SC concentration. In the post hoc analysis, the authors further explore the impact of blockchain implementation on long-term operational performance.Originality/valueThis is the first research empirically examining the effect of blockchain implementation on shareholder value varying from internal and external complexity from the CASs perspective. This paper provides evidence of the different effects of blockchain implementation on short- and long-term performance. It adds to the interdisciplinary research of information systems (IS) and operations management (OM).

Supporting interoperability in complex adaptive enterprise systems: A domain specific language approach

This study adopts a systemic view to investigate societal resilience within the whole-of-society framework for crisis preparedness, focusing on best practices, challenges, and solutions. Finland serves as the case study due to its pioneering position in crisis preparedness and its adoption of a comprehensive preparedness model that encompasses relationships and interactions among diverse stakeholders. In this study, the Finnish preparedness system is illustrated and analysed through the lens of complex adaptive systems (CAS). Data are collected through interviews with security actors representing different stakeholder groups, including civil society, businesses, and the public sector. An interpretative approach synthesises insights from literature, reports, and stakeholder interactions to co-create knowledge. The analysis covers the CAS tenets of context, relational constitution, adaptive capacity, emergence, and openness. The study presents an exploratory model anchored in CAS theory, incorporating key practices, processes, and adaptation loops integral to societal resilience from a systemic perspective in the Finnish context. From a theoretical point of view, this study contributes to CAS theory by exploring the role of context as a slow-changing variable, which is often considered a constant in CAS. Furthermore, while emergent behaviour is a critical component of CAS, most studies explore the emergent behaviour of a system within a short time span. However, the findings of this study highlight the importance of long-term emergent behaviour in addition to short-term behaviour. From a practical standpoint, this study not only explores best practices but also identifies the challenges of the Finnish system and provides a benchmark for other countries to develop their own crisis preparedness. However, replicating the system elsewhere may be challenging due to certain unique contextual factors.

A new method to medical diagnosis: Artificial immune recognition system (AIRS) with fuzzy weighted pre-processing and application to ECG arrhythmia

Tourism area development is affected by the competitive global tourism industry and the complex, multilevel dynamics of the contemporary network society. The strategic planning and governance challenge is stimulating tourism areas to become adaptive areas, being capable of responding to changing contexts in order to maintain or improve the performance of these areas as competitive tourism destinations. This article examines conditions for “adaptive tourism areas”. It does so on the basis of a complex adaptive system (CAS) perspective on tourism area development. The perspective is used to conceptualise tourism areas as complex and potentially adaptive systems, and to discuss how tourism area development can be understood as a multilevel, co-evolutionary and path dependent process. Furthermore, the CAS perspective is used to draw attention to the importance of a degree of diversity in terms of tourism products, experiences and firms. Encouraging a degree of diversity requires among other things interconnectivity among actors to ease communication and coordination, (policy) experimentation for niche-innovations, learning and reflexivity. The article ends with a discussion on the potential of, and constraints on, pursuing adaptive tourism areas from a strategic planning and governance point of view.

The effects of organizational social capital on organizational innovation have attracted the bulk of attention in recent innovation literature. However, few studies have investigated the effects of organizational social capital on innovation performance from the complex adaptive system (CAS) perspective. Based on the CAS perspective, this paper simulates how organizations in manufacturing and service industries seek higher innovation performance on the rugged fitness landscape, which is determined by the complexity of the six components of organizational social capital. Data are collected from 271 firms including 129 manufacturing and 142 service firms. Empirical results indicate that except for inter-organizational coordination, the other five components of organizational social capital significantly affect innovation performance; and their effects vary between manufacturing and service organizations. Further, simulation results demonstrate that after adaptive evolution, the average innovation performance in manufacturing organizations is higher than that in service organizations.