No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Abstract
So far, the world has been dealing with certainty, orderliness, and stability in the social and economic systems. The system in question—social or economic—was taken as a single homogeneous structure. These have defined the thoughts about the method of inquiry and policy and economic theories. In contrast, social and economic systems consisting of real-world problems are complex. A system is called complex when it comprises multiple interconnected elements, parts, or subsystems, and their interactions and feedback loops determine the behavior of the system or economy. It is the interaction between elements that matters. Studying the policy system or economy as a single structure may not provide a reasoned approach. Though challenging, understanding complexity can add an advantage by realizing the hidden potential of interacting elements. For over a century, scholarly research about complexity has brought to the fore concepts that were not realized before. The research in complexity economics at Santa Fe Institute has made a significant contribution since the 1980s. The deeper understanding has added characteristics, such as the interactive nature of elements, emergence, adaptation, evolution, and path dependency, to examine a complex system. Understanding them assumes importance in exploring new approaches and strategies for better policymaking, managing the economy, and meeting the challenges of the twenty-first century.
ResearchGate has not been able to resolve any citations for this publication.
The main statement of this book is that a mechanism which we define as co-evolution in economic systems plays a key role in the dynamics of contemporary societies. We state that co-evolution operates when, considering several evolving realms within a socio-economic system, these realms mutually shape their respective innovation, replication and/or selection processes. The processes which emerge from co-evolution should be analyzed as being globally co-determined in dynamic terms. We argue that co-evolution is a key concept which can expand the analytical and methodological scope of evolutionary economics, allowing for further unification and advance of evolutionary sub-fields.
In the first section of this work, we introduce some core concepts needed to build up this vision. Following that, in Section two, we begin to develop our co-evolution argument formally by putting all these concepts to work. We propose original co-evolutionary models to study supply-demand market interactions in innovative multisectoral settings. Then, in Section three, we maintain that the development of institutions and technology underlying growth can be formally studied from a co-evolution perspective. We propose a new model in which the co-evolution of institutions and technology plays a key driving role underlying growth. In Section four, we argue that certain issues of political economy in contemporary democracies are inherent to the processes of economic change explored in the preceding sections. We present a new co-evolution model of public opinion formation to analyze these problems. Finally, we bring our work to a close with theoretical, methodological and policy reflections inspired by the idea of co-evolution.
From a technical point of view, we start out by defining key conceptual issues which are gradually incorporated in formal models. Thus, in Section two, we present a co-evolutionary ABM (agent-based model) involving two-sector market relations with an innovative upstream sector co-evolving with a downstream user sector which, in turn, interacts with final consumers. We explore the model by combining closed-form results and computational outcomes. In this way, we obtain results for evolutionary price theory and the development of market orders and we extract technology policy implications from a co-evolution perspective.
Regarding economic growth studied in Section three, we state how technological progress emerges from the co-evolution between bodies of practice and bodies of understanding. We formally explore some consequences of the existence of mutually-dependent selection processes at work in both realms, and we extract implications regarding catalysts of co-evolution as well as blocking factors in economic growth. We put forward a replicator dynamics model with two sectors. These sectors grow at uneven rates and engender structural change, and they also co-evolve with different layers of supporting institutions. We obtain closed-form results and we show how the framework can be extended to the analysis of economic development.
The discussion in Section four proceeds from the results in Section three. We bring out the idea that in contemporary digitalized economies, in which democratic dynamics develop in continuous time, we cannot rule out the political implications of economic change. Therefore, we propose a co-evolutionary model in which economic agents (as citizens) show differential contributory levels of citizenship, and try to foster competing alternative ways of social organization in changing economies. We model the socio-economic order as a result of the co-evolution of competing worldviews (emphasizing either traditions, the market, alternative civic-settings, or centralized allocative mechanisms to solve the problems of property, trade and distribution). Citizens seek to affect the relative balance of opinions and institutions so as to progress toward their envisioned society, a vision which is not independent of economic change. By combining closed-form results with computational analysis, the model highlights the role of behavioral diversity, the permeability to peer opinion, and initial opinion configurations in the persistency and/or the predominance of specific worldviews in alternative scenarios. Finally, we synthesize our overall view in the final section.
Economic complexity offers a potentially powerful paradigm to understand key societal issues and challenges of our time. The underlying idea is that growth, development, technological change, income inequality, spatial disparities, and resilience are the visible outcomes of hidden systemic interactions. The study of economic complexity seeks to understand the structure of these interactions and how they shape various socioeconomic processes. This emerging field relies heavily on big data and machine learning techniques. This brief introduction to economic complexity has three aims. The first is to summarize key theoretical foundations and principles of economic complexity. The second is to briefly review the tools and metrics developed in the economic complexity literature that exploit information encoded in the structure of the economy to find new empirical patterns. The final aim is to highlight the insights from economic complexity to improve prediction and political decision-making. Institutions including the World Bank, the European Commission, the World Economic Forum, the OECD, and a range of national and regional organizations have begun to embrace the principles of economic complexity and its analytical framework. We discuss policy implications of this field, in particular the usefulness of building recommendation systems for major public investment decisions in a complex world.
In this article, we present a critical discussion of complexity theory. We ask: what does it really offer policy studies? We suggest that its stated advantages-- interdisciplinarity, theoretical novelty, and empirical advance--are generally exaggerated and based more on hope than experience. In that context, we identify a cautiously positive role for complexity theory, primarily as a way to bridge academic and policymaker discussions by identifying the role of pragmatic responses to complexity in policymaking.
The failure of public policies is ubiquitous. This paper ascribes this failure to the complex system nature of public policies. A key characteristic of complex systems is that they cannot be closely controlled or predicted. Yet the traditional approach to public policy is fundamentally based on both control and prediction, as it proceeds by comparing the expected costs and benefits of a postulated set of alternatives. In this paper I provide five pathologies of complex systems and show how they cause the failure of the traditional approach. If a public policy is recognized as taking place within a complex system, it is necessary to use instruments that can work within those informational and epistemological constraints. I provide several examples of the types of policies that meet these demands. But when dealing with complex systems, even with appropriate instruments it is nevertheless necessary to adjust the expectations of what can realistically be achieved.
Theoretically and conceptually, evolutionary economic geography has paid little attention to technological characteristics when explaining the emergence of new industries. Building on the literature on technological innovation systems, the article develops a framework for investigating interconnections between territorial dynamics and technological characteristics in path creation processes. The theoretical argument is operationalized in an analytical framework that is applied in empirical investigation of two green technologies and their linkages to the region of southwestern Norway, namely, carbon capture and storage and maritime battery technology. As illustrated by the empirical investigation, territorial dynamics or technological characteristics alone do not explain path creation. Rather, interconnections between the two and how interconnections play out in time and space are considered focal.
Complex Adaptive Systems (CAS) is a framework for studying, explaining, and understanding systems of agents that collectively combine to form emergent, global level properties. These agents can be nearly anything, from ants or bees, to brain cells, to water particles in a weather pattern, to groups of cars or people in a city or town. These agents produce emergent patterns via correlated feedbacks throughout the system, feedbacks that create and fortify a basin of attraction: a persistent pattern of behavior that itself is outside of equilibrium. There is also an ever-growing understanding that similar features in complex systems across a diversity of domains may indicate similar fundamental principles at work, and as such there is often utility in using the key features of one system to gain insight into the workings of seemingly distinct fields. Here we also include a brief review of multiple models that attempt to do exactly this, including some of our previous work. Though there is not complete agreement on all aspects and definitions in this field, this introduction also summarizes our understanding of what defines a CAS, including the concepts of complexity, agents, adaptation, feedbacks, emergence, and self-organization; and places this definition and its key features in a historical context. Finally we briefly discuss two of the common biases often found that the tools of CAS can help counteract: the hierarchical bias, assuming a strong top-down organization; and the complexity bias, the tendency to assign complicated features to agents that turn out to be quite simple.
Systems theory has been challenged in the recent literature due to its perceived
disconnection from today’s research and practice demands. Moving away from the reductionist
frameworks and the complicated domain predominated by known unknowns and order, a call is
being made to the social sciences to begin adopting complexity theory and newer connectionist
methods that better address complexity and open social systems. Scholars and scholar-practitioners
will continue to find the need to apply complexity theory as wicked problems become more
prevalent in the social sciences. This paper differentiates between general systems theory (GST) and
complexity theory, as well as identifies advantages for the social sciences in incorporating
complexity theory as a formal theory. Complexity theory is expanded upon and identified as
providing a new perspective and a new method of theorizing that can be practiced by disciplines
within the social sciences. These additions could better position the social sciences to address the
complexity associated with advancing technology, globalization, intricate markets, cultural change,
and the myriad of challenges and opportunities to come.
The Public Policy Process is essential reading for anyone trying to understand the process by which public policy is made. Explaining clearly the importance of the relationship between theoretical and practical aspects of policy-making, the book gives a thorough overview of the people and organisations involved in the process. Fully revised and updated for a 7th edition, The Public Policy Process provides: Clear exploration, using many illustrations, of how policy is made and implemented. A new chapter on comparative theory and methods. New material on studying advocacy coalitions, policy changes, governance, and evaluation. More European and international examples. This edition appears at a time when its concern to emphasise the complex implications of modern ‘governance’, and the way in which the ultimate outcome of a new policy initiative will depend on policy formulation and implementation processes, is particularly relevant to the UK government’s efforts to leave the European Union.
This special issue looks at the current debates on the coevolution of policy and innovation. We discuss the theoretical and empirical roots of this debate and provide an outlook to the papers within the special issue.
This study aims at exposing the potential of futures images in anticipating and informing transitions of complex adaptive systems toward sustainability. Our case concerns the food system. The inherent properties of complex adaptive systems make the exact trajectories of these systems unforeseeable. However, since the systems unfold into a common direction, we can say something about the qualities of the milestones toward which these systems navigate. Attractors configure the evolution of complex adaptive systems. Since attractors are the most stable and robust elements in these systems, they are more feasible targets for foresight than the several variants that they configure and effectuate. We have depicted attractors of sustainable local food systems by futures images: through working with an appropriate level of abstraction, by leaning on a multi-perspective approach and by breaking the linear relationship between the present and the future. In this context they were sustainability-oriented trading and delivery systems, food cultures, product development projects, food brands and transparent food systems. We also located hot spots of structural change and agency within the food system. These insights may inform transition management efforts, but they must be updated frequently, since sustainable development is a journey.
The city’s twentieth century institutional design implicitly embraced a linear perspective on the city’s development path. The Western world exemplified this linear development route throughout the twentieth century. Since the industrial revolution, the population of this part of the world has steadily retreated from the countryside into cities. It is a development which has now affected Asia, though much more quickly and in a shorter period. This is the traditional context we call Plan A: the assumption of linear growth. This Plan A no longer works well, underpinned as it is by arguments deduced from the ‘normal’ sciences and their linear understanding of the world we are part of. Functionality, certainty and predictability have proven to be no longer trustworthy, with serious consequences for city planning. It is not easy to venture out beyond current paradigms, as these are entrenched deeply within us, framing our ideas, attitudes, behaviours and actions. Nevertheless, with this contribution we propose a Plan B and what some would call a ‘post normal’ science perspective, focusing on a non-linear understanding of our world. A non-linear understanding means we consider the world to be undergoing discontinuous change, which is and becomes manifest largely beyond our control. It will have far-reaching consequences for the institutional design used by planners, interacting with and influencing a city’s development. Despite this we believe there are strong arguments in support of a Plan B.
The Indian software industry is growing rapidly. Whether firms can actually sustain this high rate of growth remains an empirical question. The ability to maintain the momentum of software export growth will ostensibly be determined by innovative capability. Notwithstanding the immense benefits accruing from the external orientation of the Indian software industry, there are good theoretical reasons why innovation may not be a pervasive feature of Indian software firms. I use a structural argument to suggest that the sector’s overt export-dependence on one single (US) market contributes to a lower innovative trajectory (also Parthasarathi and Joseph, Chapter 4). The lock-in effects associated with serving a spatially distant market, albeit vibrant and profitable, detracts the Indian sector from undertaking a more long-term innovative strategy (D’Costa, Chapter 1). Interrelatedly, the sector’s weak domestic orientation truncates the immense technological spin-offs possible with finding software (IT) solutions to local problems (D’Costa, 2002a). An inescapable outcome is uneven development in its most pronounced form: a highly dynamic software sector in the midst of various lagging sectors and a few innovative software firms coexisting with numerous low end software service providers (D’Costa, 2003a, 2003b).
This chapter has two objectives: first an analysis of the evolution of Israel’s high-tech sector and cluster over the past thirty years to identify aspects of Israel’s IT high-tech experience of the 1990s which may be useful in assessing the prospects of India’s IT high-tech sector during this decade; the second to suggest policy directions or policy issues that, if put into effect, might contribute to accelerating the evolution, alongside India’s existing software/IT industry, of a more R&D-intensive, ‘Silicon Valley’-type segment of high-tech.
This paper explores the origin of costly complexity/complicatedness from a stance in evolutionary complexity. It argues that the tendency to the former is a property of the evolution in the latter. The creation of space, physical and virtual for adaptation may be a managerial solution - one amenable to various interventions which draw upon complexity as a metaphor.
This volume offers a new and very different approach to exploring leadership, one based on the new sciences of complexity. What we are calling “Complex Systems Leadership Theory” posits that leadership can be enacted through any interaction in an organization. Far from being the sole province of managers and executives, we contend leadership is an emergent phenomenon within complex systems. As such, exploring the meaning and implications of “emergent” is one of the major issues taken up by the chapters in this book. Through advances in computational modeling and non-linear dynamics, the interactions which generate leadership can be “tracked” in a much more rigorous way, enabling managers to better understand and encourage those dynamics of interaction which prove to have beneficial effects on the organization. Overall, we see a Complex Systems Leadership Theory as the core of a new era in leadership studies; introducing and furthering this new era are the primary goals of the present volume.
This
Scholars taking the evolutionary perspective argue that technologies, competence and institutions on successful paths may spill over to related industry initiatives and subsequent industry paths. The notion of co-evolution has been introduced as an analytical category for such interconnectivity. In this article, we investigate the development of salmon farming in Norway as a successful industry path and its linkages with cod farming, a subsequent emerging industry path. In the public debate, there has been an expectation that knowledge and solutions from salmon farming will diffuse to aquaculture for other species. However, this diffusion appears to be missing. Cod farming is an area that should capitalize on the success of salmon aquaculture, and we investigate why cod farmers appear to be unable to utilize the experience and knowledge of salmon farmers and copy their solutions. We found that the development of a specialized institutional arrangement for salmon farming makes these models incompatible with the needs of farming of other species, resulting in limited co-evolution between subsequent aquaculture industry paths. Thus, a situation characterized by strong co-evolution within an industry path, facilitating the development of an institutional arrangement tailor-made for the firms of the industry, reduce the possibilities for co-evolution between related industry paths.
The rise of the Indian information technology industry is a remarkable economic success story. Software and services exports from India amounted to less than 100 billion. But, as Dinesh Sharma explains in The Outsourcer, Indian IT’s success has a long prehistory; it did not begin with software support, or with American firms’ eager recruitment of cheap and plentiful programming labor, or with India’s economic liberalization of the 1990s. The foundations of India’s IT revolution were laid long ago, even before the country’s independence from British rule in 1947, as leading Indian scientists established research institutes that became centers for the development of computer science and technology. The “miracle” of Indian IT is actually a story about the long work of converting skills and knowledge into capital and wealth. With The Outsourcer, Sharma offers the first comprehensive history of the forces that drove India’s IT success.
Sharma describes India’s early development of computer technology, part of the country’s efforts to achieve national self-sufficiency, and shows that excessive state control stifled IT industry growth before economic policy changed in 1991. He traces the rise and fall (and return) of IBM in India and the emergence of pioneering indigenous hardware and software firms. He describes the satellite communication links and state-sponsored, tax-free technology parks that made software-related outsourcing by foreign firms viable, and the tsunami of outsourcing operations at the beginning of the new millennium. It is the convergence of many factors, from the tradition of technical education to the rise of entrepreneurship to advances in communication technology, that have made the spectacular growth of India’s IT industry possible.
This article is an introduction to
complexity theory, which will be discussed using the example of economic
science. In this context, a short historical overview is intended to
demonstrate why the traditional mechanistic worldview persistently remains a
part of economic science and how it led to the development of the theory of
complex systems, which, for example, can be subsumed under chaos theory.
Furthermore, a simple supply and demand model is employed as an example to
discuss this new theory and to describe the characteristics of complexity in
comparison with the general mechanistic principle. For this purpose, specially
designed software is used for the simulation and analysis of selected complex
systems.
An important perspective use of Agent-based models (ABMs) is that of being employed as tools to support decision systems in policy-making, in the complex systems framework. Such models can be usefully employed at two different levels: to help in deciding (policy-maker level) and to empower the capabilities of people in evaluating the effectiveness of policies (citizen level). Consequently, the class of ABMs for policymaking needs to be both quite simple in its structure and highly sophisticated in its outcomes. The pursuing of simplicity and sophistication can be made more effective by applying network analysis to the emergent results. Actually, in today’s world the consequences of choices and decisions and their effects on society, and on its organization, are equally relevant. Considering the agent-based and network techniques together, we have a further important possibility. Since it is easier to have network data (i.e. social network data) than detailed behavioral individual information, we can try to understand the relationships between the dynamic changes of the networks emerging from agent-based models and the behavior of the agents. As we understand these connections, we can apply them to actual networks, to try to understand what the behavioral black boxes of real-world agents contain. We propose a simple basic structure where events, scheduled upon time, call upon agents to behave, to modify their context, and to create new structures of links among them. Events are organized as collections of small acts and steps. The metaphor is that of a recipe, i.e. a set of directions with a list of ingredients for making or preparing something, especially food (as defined in the American Heritage dictionary). Technically, recipes are sequences of numerical or alphanumerical codes, reported in vectors, and move from an agent to another determining the events and generating the edges of the emerging networks. A basic code will be shown, useful to manage possible applications in different fields: production, health-care scenarios, paper co-authorship, opinion spreading, etc.
Complexity theory provides an understanding of how systems, such as the economy and global corporations, grow, adapt, and evolve. It explains how the relationships between members of these systems give rise to the collective behavior and sheds light on how a system interacts with its environment. It does not need to have a complex explanation. The principle of Occam's razor encourages us to simplify complexity, where possible, for the study of organizational change. The discussion can be simplified by delineating the difference between complicated and complex systems. Complicated requires attention to detail whereas complexity calls for attention to the behavior of the whole system. Organization move from a complicated mode of handling day-to-day matters to a more complex mode of operation that evolves and adapts with its internal divisions and its environment. Complexity theory recognizes that economic and organizational phenomena are similar to those observed in science and in nature. The best way to understand the similarity is to look at the key components of complex systems: increasing returns, self-organizing systems, continuous adaptation, sensitivity to initial conditions, and nonlinearity.
Organizational emergence from chaotic events has often been described as unpredictable and random, at least when observed over the long term. Through a literature review this paper paves the path for the possible development of a forecasting model for making short term predictions during chaotic events so as to assist business practitioners in navigating their way out of chaos, thereby facilitating organizational emergence. As such, the paper builds on chaos and complexity theory, as its foundational theory, and identifies the most important factors and mechanisms cited in current literature that influence organizational emergence so as to potentially incorporate the factors in the future development of a short term forecasting model.
There is a revolution in the physical sciences with applying new theories that emphasize holism, uncertainty, and nonlinearity and that de-emphasize reductionism, predictability and linearity. The interest is growing in applying these theories to the study of organizations, including public organizations. The classic model of the organization as a machine has long since been discredited, but the models that have replaced this metaphor have been less than satisfactory. The basic principles of complexity theory are explained using organizations as examples. Complexity theory suggests that organizational managers promote bringing their organizations to the “edge of chaos” rather than troubleshooting, to trust workers to self-organize to solve problems, to encourage rather than banish informal communications networks, to “go with the flow” rather than script procedures, to build in some redundancy and slack resources, and to induce a healthy level of tension and anxiety in the organization to promote creativity and maximize organizational effectiveness.
The book describes what it means to say the world is complex and explores what that means for managers, policy makers and individuals. The first part of the book is about the theory and ideas and science of complexity. This is explained in a way that is thorough but not mathematical. It compares differing approaches, and also provides a historical perspective, showing how such thinking has been around since the beginning of civilisation. It emphasises the difference between a complexity worldview and the dominant mechanical worldview that underpins much of current management practice. It defines the complexity worldview as recognising the world is interconnected, shaped by history and the particularities of context. The comparison of the differing approaches to modelling complexity is unique in its depth and accessibility. The second part of the book uses this lens of complexity to explore issues in the fields of management, strategy, economics and international development. It also explores how to facilitate others to recognise the implications of adopting a complex rather than a mechanical worldview and suggests methods of research to explore systemic, path-dependent emergent aspects of situations.
In this book, Haridimos Tsoukas, one of the most imaginative organization theorists of our time, examines the nature of knowledge in organizations, and how individuals and scholars approach the concept of knowledge. Tsoukas firstly looks at organizational knowledge and its embessedness in social contexts and forms of life. He shows that knowledge is not just a collection of free floating representations of the world to be used at will, but an activity constitute of the world. On the one hand, the organization as an institutionalized system does produce regularities that can be captured via propositional forms of knowledge. On the other, the organization as practice as a lifeworld, or as an open-ended system produce stories, values, and shared traditions which can only be captured by narrative forms of knowledge. Secondly, Tsoukas looks at the issue of how individuals deal with the notion of complexity in organizations: Our inability to reduce the behavior of complex organizations to their constituent parts. Drawing on concepts such as discourse, narrativity, and reflexivity, he adopts a hermeneutical approach to the issue. Finally, Tsoukas examines the concept of meta-knowledge, and how we know what we know. Arguing that the underlying representationalist epistemology of much of mainstream management causes many problems, he advocates adopting a more discursive approach. He describes what such an epistemology might be, and illustrates it with examples from organization studies and strategic management. An ideal introduction to the thinking of a leading organizational theorist, this book will be essential reading for academics, researchers, and students of Knowledge Management, Organization Studies, Management Studies, Business Strategy and Applied Epistemology.
Since its publication in 2000, Public Management Reform has established itself as the standard text in the field, presenting a comparative analysis of recent changes in Public Management and Public Administration in a range of countries in Europe, North America and Australasia. This completely rewritten second edition radically expands, develops and updates the original. Two countries have been added to the comparison (making twelve countries in all) and a much fuller treatment has been provided of the European Commission (including a commentary on the recent reforms led by Vice-President Kinnock). Empirical data has been brought up to date, so as to cover many key developments of the last few years. The theoretical framework of the book has been further developed, including a challenging new interpretation of the trends in continental Europe, which are seen here as markedly different from the Anglo-American style ‘New Public Management”. This second edition provides an unparalleled synthesis of developments in Australia, Belgium, Canada, Finland, France, Germany, Italy, the Netherlands, New Zealand, Sweden, the UK, the USA and the European Commission. It is organized in an integrated format, within an overall theoretical framework that identifies the main pressures for and trajectories of, change. It includes a multi-dimensional analysis of the results of reform, and a chapter reflecting on the dynamic relationship between management reform and politics. Extensive appendices provide an in valuable information resource for students.
Complexity science—made possible by modern analytical and computational advances—is changing the way we think about social systems and social theory. Unfortunately, economists’ policy models have not kept up and are stuck in either a market fundamentalist or government control narrative. While these standard narratives are useful in some cases, they are damaging in others, directing thinking away from creative, innovative policy solutions. This book outlines a new, more flexible policy narrative, which envisions society as a complex evolving system that is uncontrollable but can be influenced. The book describes how economists and society became locked into the current policy framework, and lay out fresh alternatives for framing policy questions. Offering original solutions to stubborn problems, the complexity narrative builds on broader philosophical traditions, such as those in the work of John Stuart Mill, to suggest initiatives that the authors call “activist laissez-faire” policies. The book develops innovative bottom-up solutions that, through new institutional structures such as for-benefit corporations, channel individuals’ social instincts into solving societal problems, making profits a tool for change rather than a goal. It argues that a central role for government in this complexity framework is to foster an ecostructure within which diverse forms of social entrepreneurship can emerge and blossom.
In a famous passage drawing implications from determinism, Laplace introduced the image an intelligence who knew the positions and momenta of all of the particles of which the universe is composed, and asserted that in a deterministic universe such an intelligence would be able to predict everything that happens over its entire history. It is not, however, difficult to establish the physical possibility of a counterpredictive device, i.e., a device designed to act counter to any revealed prediction of its behavior. What would happen if a Laplacean intelligence were put into communication with such a device and forced to reveal its prediction of what the device would do on some occasion? On the one hand, it seems that the Laplacean Intelligence should be able to predict the device's behavior. On the other hand, it seems like that device should be able to act counter to the prediction. An examination of the puzzle leads to clarification of what determinism does (and does not) entail, with some insights about various other things along the way.
Adaptation is inherent in all biological organisms and societal systems, and provides the means for assuring the fitness and survival of any biological species or society in a given environment. It was of primary concern by biologists and scientists over time and produced strong debates about its nature and impact on life evolution. Complexity is also an inherent property of life, human society, and technology. It is due to the interrelationship, interdependence, and connectivity of elements and entities in the interior and the environment of an organism or system. Complex Adaptive Systems (CAS) have the general properties of complex systems, but they also exhibit several higher level features. In this chapter, an overview of this field is provided including biological, hard science, soft science, and computer science issues. This chapter starts by introducing the concept of adaptation, its manifestations, and its basic properties and mechanisms. The adaptation measurement aspect is also examined. Then, the concept of “emergence”, which again is one of the most difficult philosophical concepts strongly connected with delicate questions of life existence and evolution on Earth, is examined. This chapter includes a short historical note highlighting the results and opinions of workers that have initiated and expanded the adaptation, and emergence scientific field.
Stuart Kauffman here presents a brilliant new paradigm for evolutionary biology, one that extends the basic concepts of Darwinian evolution to accommodate recent findings and perspectives from the fields of biology, physics, chemistry and mathematics. The book drives to the heart of the exciting debate on the origins of life and maintenance of order in complex biological systems. It focuses on the concept of self-organization: the spontaneous emergence of order widely observed throughout nature. Kauffman here argues that self-organization plays an important role in the emergence of life itself and may play as fundamental a role in shaping life's subsequent evolution as does the Darwinian process of natural selection. Yet until now no systematic effort has been made to incorporate the concept of self-organization into evolutionary theory. The construction requirements which permit complex systems to adapt remain poorly understood, as is the extent to which selection itself can yield systems able to adapt more successfully. This book explores these themes. It shows how complex systems, contrary to expectations, can spontaneously exhibit stunning degrees of order, and how this order, in turn, is essential for understanding the emergence and development of life on Earth. Topics include the new biotechnology of applied molecular evolution, with its important implications for developing new drugs and vaccines; the balance between order and chaos observed in many naturally occurring systems; new insights concerning the predictive power of statistical mechanics in biology; and other major issues. Indeed, the approaches investigated here may prove to be the new center around which biological science itself will evolve. The work is written for all those interested in the cutting edge of research in the life sciences.
Transnational entrepreneurs — US-educated immigrant engineers whose activities span national borders — are creating new economic opportunities for formerly peripheral economies around the world. Talented immigrants who have studied and worked in the US are increasingly reversing the ‘brain drain’ by returning to their home countries to take advantage of promising opportunities there. In so doing they are building technical communities that link their home countries to the world centre of technology, Silicon Valley. As the ‘brain drain’ increasingly gives way to a process of ‘brain circulation’, networks of scientists and engineers are transferring technology, skill and know-how between distant regional economies faster and more flexibly than most corporations.
Business architecture is a general description of a system. It identifies its purpose, vital functions, active elements, and critical processes and defines the nature of the interaction among them. Business architecture consists of a set of distinct but interrelated platforms creating a multidimensional modular system. Each platform represents a dimension of the system signifying a unique mode of behavior with a predefined set of performance criteria and measures. Designing business architecture follows the general rules of interactive design; therefore starts by assuming that the system to be redesigned has been destroyed overnight but that everything else in the environment remains unchanged. The designers are given the opportunity to design the system from scratch. The systems boundary and business environment is briefly discussed; the first step in designing system architecture is to define the system's boundary and appreciate the environment in which it intends to operate. To define a system's boundary one needs to understand the behavior of its stakeholders. A stakeholder of an organization is any individual or group who is directly affected by what the organization does and therefore has a stake in its performance. This chapter briefly explains the purposes, functions, and structure for business architecture.
The disciplines of American public administration and economics are not dynamic, but are instead locked into their foundational principles and practices. Both fields are path-dependent which has made them change-resistant. This paper examines the nature of change in American culture and the influence of path-dependency on public administration and economics through a theoretical analysis. In the field of public administration, path dependency is used as the framework for analyzing recent public administration reform movements, and it explains how these movements are bound by the traditional public administration doctrine crafted in 1887. In the field of economics, the limitations of both orthodox and heterodox economics are analyzed. This paper will argue that orthodox economics, grounded in the ideas of the past-The Enlightenment, natural law, and Newtonian mechanics-is insufficient for dealing with the current political, social, and economic realities. Furthermore, heterodox economics, although in opposition to mainstream theory, only challenges the neoclassical model at the edges. Because of the constrained path of American public administration and adherence to the neoclassical model of economics, both disciplines are not prepared to respond to the complexities of the 21st Century. A new framework is needed in both disciplines that can accommodate the complexities, uncertainty, and nonlinearity of the future. © Common Ground, Rebekkah Stuteville, John Jumara, All Rights Reserved
Scitation is the online home of leading journals and conference proceedings from AIP Publishing and AIP Member Societies