Біоекономіка як комплексна система забезпечення сталого розвитку країни.

Complex adaptive systems (CAS) have been identified as being hard to comprehend, composed of multiple interacting components acting interdependently with overlapping functions aimed at adapting to external/environmental forces. The current theoretical model utilized the natural functions of teams, viewing teams as a complex adaptive system, to develop the structure of the theory of complex adaptive team systems (CATS). The CATS model was formulated around the components of complexity theory (interactions, nonlinearity, interdependency, heterogeneity, complex systems, emergence, self-organizing, and adaptability) to show its utility across multiple domains (the role of leadership, organizational learning, organizational change, collective cognitive structures, innovation, cross-business-unit collaborations). In theorizing the CATS model, a new level of analysis was implemented, the interactions between agents as a move toward emergence in complex systems. The CATS model ultimately provides a model for organizations/institutions to drive knowledge creation and innovation while operating in today's complexity.

Arecent Institute of Medicine (IOM) report describes a chasm in health care quality that we must cross for patients to receive better care in the 21st century. The report calls for a “systems approach,” drawing on the rapid evolution of knowledge about complex adaptive systems.1 Understanding how complex adaptive systems work can give physicians insights to develop and modify health care systems. By describing a practical application of the ideas about complex adaptive systems to newborn care, we aim to help pediatricians prepare to lead in this field. A complex adaptive system is a collection of individual agents who have the freedom to act, but because the agents are interconnected, action by any agent changes the context for other agents in the system. One familiar example is the buyers in a stock market. In the last century, it was usual to see organizations as mechanical systems: in mechanical systems, if we know what each part of a system does, we can predict perfectly how the whole will respond in a given situation. This is obviously not true of the stock market. A complex adaptive system may display sudden unpredictable shifts in behavior caused by interactions among agents. An essential first step in improving the US health care system is to recognize that its member organizations and individuals, with sublevels nested within and interconnected to each other, make up a complex adaptive system. One of the key attributes of a complex adaptive system is that orderly behavior can emerge among many agents who are acting independently but who share a common drive. For instance, ants, driven to survive, create intricate buildings and foraging systems without any planning by a chief executive ant. So do humans. The citizens of New York City share a drive to eat; with no single individual …

Complex adaptive systems are a special kind of self-organizing system with emergent properties and adaptive capacity in response to changing external conditions. In this article, we investigate the proposition that international environmental law, as a network of treaties and institutions, exhibits some key characteristics of a complex adaptive system. This proposition is premised on the scientific understanding that the Earth system displays properties of a complex adaptive system. If so, international environmental law, as a control system, may benefit from the insights gained and from being modelled in ways more appropriately aligned with the functioning of the Earth system itself. In this exploratory review, we found evidence suggesting that international environmental law is a complex system where treaties and institutions self-organize and exhibit emergent properties. Furthermore, we contend that international environmental law as a whole is adapting to exogenous changes through an institutional process akin to natural selection in biological evolution. However, the adequacy of the direction and rate of adaptation for the purpose of safeguarding the integrity of Earth’s life-support system is questioned. This paper concludes with an emphasis on the need for system-level interventions to steer the direction of self-organization while maintaining institutional diversity. This recommendation stands in contrast to the reductionist approach to institutional fragmentation and aims at embracing the existing complexity in international environmental law.

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.

This book provides an introduction to the role of diversity in complex adaptive systems. A complex system--such as an economy or a tropical ecosystem--consists of interacting adaptive entities that produce dynamic patterns and structures. Diversity plays a different role in a complex system than it does in an equilibrium system, where it often merely produces variation around the mean for performance measures. In complex adaptive systems, diversity makes fundamental contributions to system performance. Scott Page gives a concise primer on how diversity happens, how it is maintained, and how it affects complex systems. He explains how diversity underpins system level robustness, allowing for multiple responses to external shocks and internal adaptations; how it provides the seeds for large events by creating outliers that fuel tipping points; and how it drives novelty and innovation. Page looks at the different kinds of diversity--variations within and across types, and distinct community compositions and interaction structures--and covers the evolution of diversity within complex systems and the factors that determine the amount of maintained diversity within a system. Provides a concise and accessible introduction Shows how diversity underpins robustness and fuels tipping points Covers all types of diversity The essential primer on diversity in complex adaptive systems

The causes of wellbeing and illbeing interact with feedback dynamics resulting in the same set of traits giving rise to a variety of health outcomes (multi-finality) and different traits giving rise to the same health outcome (equi-finality). As a result, a full understanding of health and its disorders must be in terms of a complex adaptive system of causes, rather than in terms of categorical diagnoses or sets of symptoms. The three domains of person-centered integrative diagnosis (PID) are considered here as interacting components of a complex adaptive system comprised of health status (functioning/wellness versus disability/disorder), experience of health (self-awareness/fulfillment versus misunderstanding/suffering) and contributors to health (protective versus risk factors). The PID domains thereby allow healthcare and health promotion to be understood in terms of measurable components of a complex adaptive system. Three major concepts of health are examined in detail to identify their dynamic origins: Psychological Maturity, Flourishing and Resilience. In humanistic psychology, psychological maturity (i.e. healthy personality, mental wellbeing) involves the development of high self-directedness, high co-operativeness and high self-transcendence, but self-transcendence is nevertheless devalued in individualistic and materialistic cultures except when people must face adversity and ultimate situations like suffering or the threat of death. Psychological Maturity develops through two complementary processes often labeled as Flourishing and Resilience. Flourishing is the development of one's potential to live optimally, especially as the result of favorable circumstances, whereas Resilience is positive adaptation to life despite adverse circumstances. As a result of the complex feedback dynamics between the processes of flourishing and resilience, each person is a unique individual who has a variety of paths for achieving positive health and wellbeing open to him or her. Person-centered health promotion and care can thereby be approached as a creative life project that can be conducted with the assistance of healthcare workers who are both therapeutic allies and well-informed experts.

This introductory chapter provides an overview and a brief history of complexity science, which is the study of complex systems. All living systems and all intelligent systems are complex systems. Complexity science is relatively new but already indispensable. Many of the most important problems in engineering, medicine, and public policy are now addressed with the ideas and methods of complexity science. However, there is no agreement about the definition of 'complexity' or 'complex system', nor even about whether a definition is possible or needed. The conceptual foundations of complexity science are disputed, and there are many and diverging views among scientists about what complexity and complex systems are. Even the status of complexity as a discipline can be questioned given that it potentially covers almost everything. The origins of complexity science lie in cybernetics and systems theory, both of which began in the 1950s. Complexity science is related to dynamical systems theory, which matured in the 1970s, and to the study of cellular automata, which were invented at the end of the 1940s. By then computer science had become established as a new scientific discipline.

BackgroundGoverning immunization services in a way that achieves and maintains desired population coverage levels is complex as it involves interactions of multiple actors and contexts. In one of the Indian states, Kerala, after routine immunization had reached high coverage in the late 1990s, it started to decline in some of the districts. This paper describes an application of complex adaptive systems theory and methods to understand and explain the phenomena underlying unexpected changes in vaccination coverage.MethodsWe used qualitative methods to explore the factors underlying changes in vaccination coverage in two districts in Kerala, one with high and one with low coverage. Content analysis was guided by features inherent to complex adaptive systems such as phase transitions, feedback, path dependence, and self-organization. Causal loop diagrams were developed to depict the interactions among actors and critical events that influenced the changes in vaccination coverage.ResultsWe identified various complex adaptive system phenomena that influenced the change in vaccination coverage levels in the two districts. Phase transition describes how initial acceptability to vaccination is replaced by a resistance in northern Kerala, which involved new actors; actors attempting to regain acceptability and others who countered it created several feedback loops. We also describe how the authorities have responded to declining immunization coverage and its impact on vaccine acceptability in the context of certain highly connected actors playing disproportionate influence over household vaccination decisions.Theoretical exposition of our findings reveals the important role of trust in health workers and institutions that shape the interactions of actors leading to complex adaptive system phenomena.ConclusionsAs illustrated in this study, a complex adaptive system lens helps to uncover the ‘real’ drivers for change. This approach assists researchers and decision makers to systematically explore the driving forces and factors in each setting and develop appropriate and timely strategies to address them. The study calls for greater consideration of dynamics of vaccine acceptability while formulating immunization policies and program strategies. The analytical approaches adopted in this study are not only applicable to immunization or Kerala but to all complex interventions, health systems problems, and contexts.

Spatial planning and climate change science are part of a complex and uncertain context. The general response to this, and this can be seen throughout both the spatial planning and the climate change community, is to try to reduce uncertainty by introducing more procedures, developing more detailed models and increasing control of processes. However, gaining more detailed knowledge does not always increase certainty, or as Kevin Trenberth (2010) puts it: ‘More knowledge less certainty’. Both spatial planning and climate change, even more so if the two are linked, could gain from introducing self-organising principles. In order to be able to do so, the spatial system needs to be understood as a complex adaptive system, in which processes of self-organisation and emergence create ever changing spatial patterns, which, when used purposefully, will increase the system’s capability to respond effectively to unexpected change and uncertainty, for instance as a result of climate change. Providing the individual spatial elements in the landscape with a surplus of ‘technical skills’ will enable these spatial entities to self-organise and adapt more easily, thereby collaboratively increasing the adaptive capacity of the system. In order to create the conditions, which allow these self-organising processes to take place, current spatial planning practice needs to let go of its preference to regard spatial systems as being simple and problems as being tame. Complex Adaptive problems, such as climate change, cannot be dealt with within the current spatial planning framework. They require fundamental rethinking of the models underpinning spatial planning and introducing a new planning methodology. Swarm Planning claims to offer this methodology, using the dynamics of swarms as a metaphor. The behavioural patterns of swarms in nature are governed by the principles of self-organisation and emergence, rather than being planned and controlled by an outside authority. When these principles are built into a complex spatial system, the system can start displaying the properties of a swarm: responding to interventions and impulses it will change its shape, but not its content. The elements that make up the system will still be the same, yet they will interact in way that is more responsive to changing and uncertain circumstances, thereby increasing its adaptive capacity. The purpose of this chapter is to develop Swarm Planning as a planning methodology, which is better equipped to deal with uncertainties and to effectively plan for the complex problem of climate change. This new methodology looks at spatial systems as complex adaptive systems and uses the properties of these systems spatially to increase the resilience and adaptive capacity of the system. The chapter will first examine different views on dealing with uncertainty, it will then describe the properties of swarms and complex adaptive systems and their applicability to a Swarm Planning method and the chapter will conclude with describing a Swarm Planning design, illuminating the potential benefits.KeywordsUncertaintySelf-organisationSwarm planningComplex adaptive systemsSpatial planning

A transport system can be defined as a complex system characterized by a random value of transport demand, variable weather and climatic factors, a set of characteristics of transport infrastructure, and a complex system of interconnections. One of the key modes of transport providing freight transport both in domestic and international traffic is road. Its mobility and the ability to deliver cargo from door to door is a unique competitive advantage over other modes of transport. To create an effective logistics infrastructure that meets the demand for domestic freight transport, first of all, information is needed on the needs for transport between regions of the country. Thus, it is necessary to look for mathematical approaches to modeling freight flows, combining their practical implementation using widely used software products (for example, MS Excel). The purpose of the paper is to build effective multifactor regression models of demand for input and output transportation of goods by road for each region of Ukraine according to publicly available statistical data of the State Statistics Service of Ukraine. The modern approach to modeling cargo flows requires fast processing of a large amount of statistical data. In addition, the method should be as universal as possible and capable of quick and simple changes under conditions of a change in statistical data. From this point of view, the most acceptable option can be considered to be the modeling of freight traffic using regression models based on correlation and regression analysis. In general, the task is to find the dependence of the demand for transportation on the factors that influence it. Such factors in the existing models are connected with various macroeconomic indicators, as well as the distance of delivery. The data of regional statistics of the State Statistics Service of Ukraine and data of the “Lardi-Trans” website as the most widely used by freight carriers and shippers were taken as the initial data for modeling. A list of factors has been found that significantly influence the demand for freight transport by road between regions of Ukraine. A rating of influencing factors has been compiled, among which are the gross regional product, regional volumes of foreign trade in goods (imports) and gross regional product per one inhabitant of the region. The absolute values of the correlation coefficients are in the range 0.351-0.974. The lowest correlation coefficient is between the transportation distance and the demand for delivery, which proves a negligible relationship between the volume of regional transportation and the distance of delivery. Multivariate regression models with thirteen, five and two factors of influence on demand are built. Accuracy parameter values are acceptable for all model variants. The normalized R-squared of the obtained models does not fall below 84%, and the average approximation error does not rise above 1.6%, which is an excellent performance of the models.

Based on concepts of the complex adaptive system (CAS) from system theory and complexity studies, the authors characterize the CAS and investigate whether the CAS construct is transferrable to business organizations. A scale is developed to rate a business organization's similarity to a CAS. The call a business enterprise matching the criteria of a CAS an "evolutionary organization". Short case studies of three high-technology companies (Microsoft, Intel, and Netscape) lead to an evaluation of these companies as evolutionary organizations. Limits of the transferability of this method are noted.

School‐improvement initiatives are implemented with admirable goals, often requiring substantial human and material resources. However, many fail to be sustainable beyond short‐term funding cycles or the enthusiasm of local initiators. Typically, implementation and improvement are viewed linearly and as static end‐products that fail to consider that schools are complex adaptive systems (CAS) that are continuously and recursively challenged with change. To investigate sustainable school‐improvement within CAS, we used PRISMA‐SR guidelines to conduct a scoping review of peer‐reviewed journal articles extracted from six databases using keywords synonymous with ‘ complex or adaptive system ’ , ‘ sustain ’ , ‘ school ’ and ‘ initiative ’ . The search process yielded 1146 articles but only 16 of those articles met our inclusion/exclusion criteria that specified that authors present an integrated view of sustainable implementation in schools conceptualised as CAS. Within the selected 16 articles, key components for sustainability in schools described as CAS included access to adequate funding and resources, engagement and involvement of stakeholders, the ability of stakeholders to adapt to change, formation of collaborative partnerships, and the development of supportive policies and procedures. Some important issues arose, such as the tendency of the ‘whole school approach’ to be reduced to information dissemination activities that do not adequately deal with components of complex systems, and the increasing recognition that older implementation models that seek ‘institutionalisation’ fail to appreciate that sustainability is a process, not an end goal. This scoping review highlights the need to recognise the complexity and adaptivity of school systems for successful and sustained implementation of school‐improvement initiatives.

Many important challenges facing society today involve the management of interlinked complex adaptive systems (CAS): coupled socio-economic and ecological systems composed of many interacting elements which have been created or partially created by human actions. As we explicitly wish to manage and transform these systems, engineering and design approaches have much to offer us, however they must be fundamentally modified to deal with CAS. These systems are not static artifacts, but dynamic, evolving and reflexive processes the behaviour of which is not straightforwardly predicable and which may respond in unexpected ways in response to our interventions. Additionally many of the complex systems which we would most like to influence have significant social components. Objective choices about design goals cannot be made and the integration of participatory or political processes may be required. In order to manage complex adaptive systems, we suggest a “steering” approach; an action or series of actions applied to a complex system and/or its environment for achieving a specific purpose. Steering combines tools from complexity science with whole systems design philosophy and is a continuous process which involves interacting with, monitoring and learning from the system in question. The techniques required for effective steering fall into two categories. Firstly we wish to understand, and indeed exploit, the systems’ structure and dynamics in order to intervene efficaciously with them. Hence we need techniques to uncover this structure and to choose points of intervention: system “levers” through which the system as a whole could be manipulated with system interventions designed accordingly. Secondly we frame those techniques within a participatory “adaptive management” structure (Waltner-Toews and Kay, 2005), which explicitly takes into account the adaptive nature of these systems and our limited capacity to fully model real world complex systems, by building in monitoring and feedback processes with which to modify our interventions as systems respond. We are currently applying this process to a case study aiming to facilitate regional decision making in an industrial ecosystem in the Humber region, UK. The region represents a significant proportion of UK infrastructure, energy generation capacity and CO2 production. However, there is a strong desire to develop the “Humber Gateway” as a renewable energy hub using the extensive agricultural hinterland and offshore and port facilities to support bio-based energy production and offshore wind and tidal generation. We have undertaken participatory modelling exercises in which stakeholders collaboratively constructed simple systems models of the development of their regional bio-based economy, the key factors of influence, drivers and their perceived interdependencies (Penn et al., 2013). Building on this approach we used a “control nodes” methodology from network theory (Liu et al., 2011) to determine the specific subsets of these factors which could theoretically be used to drive the system into any given state. This technique is combined with an evaluation of the practical controllability of each factor from the perspectives of the actors present to allow its use in real world contexts in which policy makers and industrial stakeholders must make decisions (Penn et al., In press.). Applying this hybrid approach in the real world context of the Humber allowed stakeholders to uncover and discuss possible novel points of intervention in their regional system, based both on its structure and their own differing abilities to influence different factors within it. This proved to be a useful starting point for debate on policy ideas and the importance of considering not just where to intervene, but who is able to intervene with a given factor. However this approach, like all network-based methods, is limited by its sensitivity to the network structure described. Additionally by the fact that once suitable control configurations are discovered, the method as yet gives us no indication of how to construct the time variable control inputs required to steer the system to a given state. Instead we must use such modelling as a “thinking tool” to provide principled starting points, to be combined with stakeholder expertise, for the participatory design of complex social systems.

Theoretical background: The FinTechs phenomenon is worth discussing as its multidimensional character causes difficulties not only with defining it but also with assessing the impact of its development on the economy and society. The impact of FinTechs on sustainable development is a relatively new field of research. Thus, the paper presents exploratory research aiming to analyse the current areas of FinTechs activity, the state of their development in Europe, and the state of the art in European research on their impact on sustainable development goals (SDGs) achievement. The study applied both inductive and deductive research methods, together with comparative analysis. Purpose of the article: The paper aims to analyse the European FinTechs landscape in the context of their impact on sustainability reflected by SDGs and prepare the framework for further research in this field. Research methods: The theoretical analysis conducted in the paper for defining FinTechs was based on an in-depth literature review, including scientific papers, documents and reports. In this section, the inductive method and comparative analysis were mostly applied. The empirical part of the paper includes the analysis of quantitative data published by the European Commission and Eurostat. This analysis is primarily based on comparative analysis. The framework for further research in this field is based on a systemic literature review (SLR). In this section, the PRISMA methodology was applied. Main findings: There is no doubt that FinTechs have already influenced the financial systems worldwide. In Europe, their disruptive development motivated the traditional market players to adapt their offerings, strategies and business models. They were perceived as market disruptors at the beginning of their operational activity. Today, the vast majority of authors notice their huge potential as sustainability enablers. The systemic literature review proved the worldwide systematically increasing scientific interest in surveying the FinTechs and their contribution to SDGs achievement. This trend has not yet been observed in Europe. Only a few papers directly refer to the relationship between FinTechs and SDGs achievement in European countries. The results have shed light on existing academic literature embracing both FinTech and SDGs issues in Europe, explored emerging trends in current research, and identified the main areas for further investigation.

Traditional whole systems of medicine, such as naturopathy, are founded upon holism; a philosophical paradigm consistent with contemporary complexity science. Naturopathic case management is predicated upon the understanding of an intimately interconnected internal physiological and external context of the human organism-potentially indicating a worldview aligned with a complexity perspective. In this study we investigate naturopathic clinical reasoning using a complexity lens with the aim of ascertaining the extent of correspondence between the two. Mind maps depicting case presentations were sought from Australian degree qualified naturopaths. A network mapping was undertaken, which was then analysed in accordance with a complexity science framework using exploratory data analysis and network analysis processes and tools. Naturopathic case schematics, in the form of mind maps (n = 70), were collected, network mapped, and analysed. A total of 739 unique elements and 2724 links were identified across the network. Integral elements across the network were: stress, fatigue, general anxiety, systemic inflammation, gut dysbiosis, and diet. A modularity algorithm detected 11 communities, the primary ones of these representing the nervous system and mood; the gastrointestinal tract, liver, and nutrition; immune function and the immune system; and diet and nutrients. Naturopathic case management is holistic and based on a perspective of an integrated physiology and external context of the human organism. The traditional concept of holism, when subjected to a complexity lens, leads to the emergence of a contemporary holistic paradigm cognisant of the human organism being a complex system. The application of complexity science to investigate naturopathic case management as employed in this study, demonstrates that it is possible to investigate traditional philosophies and principles in a scientific and critical manner. A complexity science research approach may offer a suitable scientific paradigm to develop our understanding of traditional whole systems of medicine.