On Complex Adaptive Systems and Electronic Government: A Proposed Theoretical Approach for Electronic Government Studies

This paper will explore the concept of resilience from its roots in ecology to the application of this ecological concept of resilience to social and community resilience in the context of climate change. In this context, resilience is seen as a property of complex adaptive communities rather than of individuals. This paper will explore how this ecological concept of resilience has been taken up both by climate adaptation research and by the Transition Town movement. This ecological concept of resilience is at odds with the individualism of both psychological and economic approaches to resilience in relation to climate change.

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

PurposeThe aim is to investigate the state of complex adaptive system (CAS) theory in the organizational theory literature and to provide a map for future studies of CAS theory.Design/methodology/approachAbstracts were searched via electronic database and a range of recently published (1996‐2004) books and articles were identified that contained a relatively concise description of CAS. Content analysis is used to deconstruct the CAS descriptions into “component concepts.” Those concepts are analyzed from multiple viewpoints.FindingsThere is no single, shared, sense of CAS theory. Differing understandings of CAS theory are identified based on “expert version” and “most popularly identified concepts.” Also, differences and similarities are identified between an “academic” version of CAS and a version developed by those who are influenced by both academic learning and practical experience.Research limitations/implicationsStudy is limited to concise definitions of CAS, so could be improved by including more lengthy conversations. Additionally, study is limited to organizational theory, so may be less applicable in other disciplines.Practical implicationsWhen working within a CAS framework, academics should specify their CAS perspective to improve clarity of their work. When using a CAS framework to study organizations, researchers should include a comprehensive suite of concepts. Though not described in depth, no effective application of CAS for organizational change were found.Originality/valueFor those who study CAS theory and theory of theory, this paper provides an important benchmark by identifying a bifurcation in the evolution of CAS theory.

This research paper starts from the belief that digital government is a systemic process and that by studying the technical architecture it is possible to gain a better understanding of its behavior. Drawing on insights from system dynamics, systems theory, and complex adaptive systems, the paper hypothesizes that by including and reinforcing feedback loops in the architecture, it is possible to obtain significant performance gains. For the sake of testing the hypothesis, and to answer the research question: How can Systems Theory be used to understand the digital government infrastructure of a country? the case of Estonia is presented. As a result of the research, it is found that the presence of reinforcement loops in the technical architecture leads to performance gains, that it is possible to observe complex behavior in digital government infrastructure, and demonstrates that systems thinking may be used to analyze digital government systems.

Classical forest management has worked out a series of forest regulation methods with the aim of obtaining the “fully regulated” forest. Considering the forest as a complex biological adaptive system means overcoming the reductionist and mechanist paradigm, and entails a shift towards a systemic approach in silviculture and forest management. The aim of this work is to discuss the objectives and theoretical assumptions of classical forest management methods in the light of the new systemic paradigm. I conclude that managing forests as complex adaptive systems and sustaining their ability to adapt to future changes is possible only if there is also a change in forest management methods so that they are consistent with the new theoretical approach.

Complex Adaptive Systems (CAS) are ubiquitous and composed of many interacting “agents” that exhibit independent properties and behaviors that function together with their environment to produce emergent properties. Emergence and emergent properties cannot be predicted by isolated understanding of these interacting agents/components; but can be demonstrated by observing the outcomes associated with dynamically changing interacting components of a CAS. Obviously, evolution also plays a key role in driving emergence as a defining feature of biological CAS. Biological CAS are highly heterogeneous and complex, both within and across broad scales of time and space. Biological CAS are also non-linear which means that predicting outcomes is difficult. Moreover, it is impossible to “fix” a CAS, rather the identification of leverage points that can alter the trajectory of the system to achieve desired outcomes is a more logical approach. Until recently, systems of such high dimensionality were not sufficiently tractable to understand and apply CAS principles to a disease as complex as cancer. However, recent progress in the development of advanced technologies such as computation, machine learning, artificial intelligence, and modeling portend a day when cancer will be viewed and managed as a CAS. These “big data” tools offer new and innovative opportunities to mine, manage, manipulate, model and simulate cancer to derive the information needed to manage it as a CAS. In terms of applying these principles at least one approach to treating cancer, immunotherapy, suggests that achieving a future state where cancer is viewed through the lens of CAS is well underway. Immunotherapy represents a paradigm shift in cancer therapy in that it targets the immune system, which is a quintessential CAS. When immunotherapy is successful the outcome is a “homeostatic reset” of what is an extraordinarily complex interaction between cancer and the immune system. Together these two complex systems comprise a CAS that promises to re-define how we treat and prevent cancer. A variety of immunotherapeutics (dominated by checkpoint inhibitors) have produced durable responses (possible cures) in a few patients against some cancers. These agents essentially block signals that the tumor employs to keep the immune system from recognizing and killing the cancer. However, the interaction of cancer and the immune system is a dynamic CAS that will ultimately require a detailed understanding of the cellular and microenvironmental changes that occur in patients in response to specific immunotherapeutic interventions. The challenges we face are significant including: identifying responders/non-responders; determining doses; predicting and controlling toxicities; developing rational combinations; and creating new targeted systems-based therapies. Fortunately, many of these challenges can be met by defining the “states” produced by some of the defining alterations observed in responsive and non-responsive patients including “omics” alterations, types of immune cells, temporal relationships, immune activation, humoral factors, etc. Although early, models and platforms to describe, annotate, model and simulate these systems alterations are emerging. In the past several years, we have developed a modeling platform that permits the study of the immune system and its interaction with cancer. “Cell Studio” is an immune-modeling engine that seeks to examine cancer and the immune response as a dynamic CAS by using real world data on the immune system and cancer to develop and inform computational models. Cell Studio permits the user to conduct in silico experiments of defined time and complexity. It combines agent-based and mathematical modeling approaches to capture multiscale dynamics within the immune system. The engine permits user creation of multiple different types of immune cells each with different classes of properties including different collections of cell surface receptors at different concentrations and affinities as well as the capacity to release and respond to cytokines. Multiple compartments corresponding to different body niches (e.g. lymph node, tumor environment) can be created. Mathematical models govern phenomena such as diffusion and cell tracking of cytokine gradients. As a CAS, based on a finite number of “rules” the system is self-organizing and can display emergent properties. User defined therapeutic interventions such as drug administration can be incorporated to assess the system’s response. Cell Studio is implemented using a gaming platform so that the in silico experiments can be visualized in 3D - in real time if desired. This permits researchers to perform experiments similar to those done using biologic model systems and visualizing the results. Like most video gaming platforms, different user views, overviews, individual cell movement, etc. are available and real-time as well as cumulative statistical outputs are captured and displayed. Unlike biologic model systems the simulations can be time reversed to identify, visualize, and manipulate key events. Experimentation using the Cell Studio modeling engine shows that it can recapitulate the longitudinal events in biologic model systems. Additionally, it can recover “immunophenotypes” observed in human studies of immunotherapy in cancer. It is anticipated that the in silico modeling can augment current biologic modeling strategies - especially since it can be run with numbers of replicates of virtual experiments that are not practical with biologic model systems. Additionally, it promises to assist in the rationale to develop combinatorial interventions hitting multiple immune targets and in understanding factors that modulate successful outcomes. In summary, the implications of viewing, studying and developing strategic approaches to fundamentally understand the cancer - immune system CAS are profound. Cell Studio is a next generation novel and powerful approach to analyze and model specific components of this dynamic and integrated CAS for the benefit of patients. Citation Format: Anna D. Barker, Kenneth Buetow. Viewing cancer as a complex adaptive system and managing immunotherapy as “homeostatic reset” [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr SY36-03.

New product development (NPD) is challenging, as it involves mastering new technologies by coordinating appropriate resources efficiently and effectively. Established models of NPD focus on structuring, planning and ordering the innovation process but do not account for complexity and organizational responses and strategies in handling day-to-day resource allocation and decision-making. Our work is theoretically based on ideas from complexity science and NPD procedures. We build on and extend the work on Complex Adaptive System (CAS) and combine it with Socio-Technical System in an innovative approach to analyze, understand and manage NPD complexity by means of network analysis and performance metrics.This paper contributes to existing literature by introducing a framework of complex adaptive socio-technical systems (CASS). It is intended to (1) consider dependencies between product and individuals, (2) provide indicators to measure complexity, efficiency and effectiveness, (3) explain complex phenomena by identifying patterns, and (4) enable NPD governance.We demonstrate the applicability of our framework and metrics using comparative longitudinal case studies using novel and unique data from 4 years of meeting minutes and document exchange in the design phase of the NPD process of a large German automobile OEM. Results reveal new measures for addressing operational, social and technical complexity, providing new insights into complex dynamic behavior. From a managerial point of view, contributions of CASS are twofold: First, new possibilities for NPD governance emerge from performance indicators. Second, the extraction of dynamic socio-technical networks supports project-to-project learning.

Complexity science suggests that our current health care delivery system acts as a complex adaptive system (CAS). Such systems represent a dynamic and flexible network of individuals who can coevolve with their ever changing environment. The CAS performance fluctuates and its members' interactions continuously change over time in response to the stress generated by its surrounding environment. This paper will review the challenges of intervening and introducing a planned change into a complex adaptive health care delivery system. We explore the role of the "reflective adaptive process" in developing delivery interventions and suggest different evaluation methodologies to study the impact of such interventions on the performance of the entire system. We finally describe the implementation of a new program, the Aging Brain Care Medical Home as a case study of our proposed evaluation process.

Complex Adaptive Systems, for our purposes, are social systems that that evolve and display new, emergent properties, and self-organizing behavior of their components; they are based on a reasonably stable infrastructure, on the satisfaction of the most basic needs, and flexible, frequent, and open communication and interaction. Complex Adaptive Systems may be based on a few, simple rules, but can yield complex and unpredictable outcomes. The ‘Hole in the Wall’ project is an interesting case in point in the design of spaces for complex adaptive systems, or complex adaptive networks. In this project, touch screen computers were literally put in ‘holes in walls’ in places where unschooled children congregated. The children were given no instructions on how to use the computers, or what to do with them, but with startling results: the children soon taught themselves how to use the computers and the Internet, and much more (Mitra, 2003).

Complex Adaptive Systems, for our purposes, are social systems that that evolve and display new, emergent properties, and self-organizing behavior of their components; they are based on a reasonably stable infrastructure, on the satisfaction of the most basic needs, and flexible, frequent, and open communication and interaction. Complex Adaptive Systems may be based on a few, simple rules, but can yield complex and unpredictable outcomes. The ‘Hole in the Wall’ project is an interesting case in point in the design of spaces for complex adaptive systems, or complex adaptive networks. In this project, touch screen computers were literally put in ‘holes in walls’ in places where unschooled children congregated. The children were given no instructions on how to use the computers, or what to do with them, but with startling results: the children soon taught themselves how to use the computers and the Internet, and much more (Mitra, 2003).

On the emergent “Quantum” theory in complex adaptive systems

This chapter introduces Complex Adaptive Systems Thinking (CAST) into the domain of Intellectual Capital (IC). CAST is based on the theories of Complex Adaptive System (CAS) and Systems Thinking (ST). It argues that the CAST, combined with Intelligence Base offers a potentially more holistic approach to managing the Intellectual Capital of an organization. Furthermore, the authors extend this IC management with additional dimensions proper to a social entity such as an organization. New organizational design methods are needed and the capability approach is such a method that supports IC in virtual and real organizations. The characteristics of Intellectual Capital are discussed in the iterative process of inquiry and the Cynefin Framework, guaranteeing a holistic view on the organization and its environment.

Although many books and conference reports have considered the changeability of a complex adaptive system (CAS), no in-depth study has assessed how changes impact a CAS or the relationships among the CAS changeability parameters of agility, flexibility, robustness, and adaptability. This study analyzes the impact of CAS changeability when an external agent requires a change and analyzes how such a change affects the evolution of the CAS. We start by reviewing the general concepts of changeability and CAS, followed by an analysis of their relationship. A model using an extension of learning classifier system (XCSF) is presented and evaluated to meet the objectives of this research to: 1) accurately assess the impact of changeability on telecommunication-based CAS components and their evolution; and 2) gain insight into the impact of changes on CAS for the purpose of improving the engineering of such systems in the future. The relationship between changeability and fitness, which is an important CAS performance measure, is included. CAS simulations using the XCSF model are compared with data from a telecommunication company over the past few years; the comparison suggests that the XCSF approach may be useful for improving CAS engineering.

Purpose– The purpose of this study is to evaluate whether the global policy on sustainability, United Nations Global Compact (UNGC), is in alignment with the complexity of the sustainability landscape utilizing complex adaptive system (CAS) theory and theory of change.Design/methodology/approach– An original Complex Adaptive Policy System (CAPS) framework is used as a qualitative instrument with a constant comparison of 11 CAS themes in analyzing 117 UNGC speeches listed on the Global Compact Web site.Findings– Although this study is intended as a preliminary study, the findings raise important questions regarding the long-term impact of the Global Compact as a global policy on sustainability.Research limitations/implications– The limitations of the study include the preliminary study design and limited source of information. Future research should include a comprehensive evaluation of the UNGC to yield specific recommendations for aligning policy with the landscape.Originality/value– The study offers an original systems framework to evaluate public and private organizational polices on sustainability.

The benefits of horticulture to our society have long been known. Just recently, we are beginning to see the valuable role that horticulture can have on impacting youth. However, research into this area has been limited. As this avenue of horticulture is growing, so is the need to continue and establish substantial research into this area. One important obstacle to overcome is funding. While a desire to pursue the effects of horticulture on youth exists, too often a lack of financial support has limited the depth and scope of research. Finding and establishing funding allows the researcher to explore and allocate the resources necessary to continue reputable research. This workshop will explore various funding opportunities for research in the area of children and gardening. Areas of discussion will include sources for funding as well as generating a proposed idea, refining your idea, documenting the need, and establishing uniqueness of your study. This talk will focus on finding and establishing funding for children's gardening research—a much needed necessity to help document and establish the benefits and importance of youth gardening programs.