Complexity In Economic And Social Systems
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Complexity in Economic and Social Systems
There is no term that better describes the essential features of human society than complexity. On various levels, from the decision-making processes of individuals, through to the interactions between individuals leading to the spontaneous formation of groups and social hierarchies, up to the collective, herding processes that reshape whole societies, all these features share the property of irreducibility, i.e., they require a holistic, multi-level approach formed by researchers from different disciplines. This Special Issue aims to collect research studies that, by exploiting the latest advances in physics, economics, complex networks, and data science, make a step towards understanding these economic and social systems. The majority of submissions are devoted to financial market analysis and modeling, including the stock and cryptocurrency markets in the COVID-19 pandemic, systemic risk quantification and control, wealth condensation, the innovation-related performance of companies, and more. Looking more at societies, there are papers that deal with regional development, land speculation, and the-fake news-fighting strategies, the issues which are of central interest in contemporary society. On top of this, one of the contributions proposes a new, improved complexity measure.
Complexity and Co-evolution
Author: Elizabeth Garnsey
language: en
Publisher: Edward Elgar Publishing
Release Date: 2006-01-01
. . . in my opinion. . . readers. . . should find in this book both several remarkable insights concerning basic statements of evolutionary theorising and concrete results that can be acquired by applying such basic statements in computer simulation models and in various fields of analysis. Mauro Lombardi, The Journal of Artificial Societies and Social Simulation Complexity theory first emerged three decades or so ago, but only recently has its potential relevance for the study of social and economic phenomena really begun to be recognised. This timely collection of essays clearly demonstrates, both conceptually and empirically, how complexity theory ideas can provide considerable insight into how socio-economic systems cities, societies, industries, technologies and economies evolve and adapt over time. It is essential reading for anyone interested in how order and evolution emerge out of the seemingly chaotic socio-economic world around us. Ron Martin, University of Cambridge, UK I read Complexity and Co-Evolution with real pleasure. These authors have done the near impossible they have made the concepts of a new and evolving science accessible to people who can apply it in practical ways. The clarity of writing reflects the sort of confidence only the truly informed can muster, for they need no jargon to cover confusions. Their mastery allows them to present the essentials in simple, unadorned forms and through genuinely illustrative examples. Any manager or director trying to navigate dynamic markets can use this book to learn new ways of thinking, explore new possibilities, and study historical experiences. Robert Artigiani, United States Naval Academy Current thinking about evolutionary dynamics increasingly relies on co-evolution, and co-evolution increasingly implies complex dynamics of one sort or another. This volume brings together a capable and well-balanced group of thinkers on these topics who explore these deeply related concepts with up-to-date and advanced tools and concepts. For anyone wishing to learn about the latest developments in these rapidly developing areas, this book is highly recommended. J. Barkley Rosser Jr., James Madison University, US This book applies ideas and methods from the complexity perspective to key concerns in the social sciences, exploring co-evolutionary processes that have not yet been addressed in the technical or popular literature on complexity. Authorities in a variety of fields including evolutionary economics, innovation and regeneration studies, urban modelling and history re-evaluate their disciplines within this framework. The book explores the complex dynamic processes that give rise to socio-economic change over space and time, with reference to empirical cases including the emergence of knowledge-intensive industries and decline of mature regions, the operation of innovative networks and the evolution of localities and cities. Sustainability is a persistent theme and the practicability of intervention is examined in the light of these perspectives. Specialists in disciplines that include economics, evolutionary theory, innovation, industrial manufacturing, technology change, and archaeology will find much to interest them in this book. In addition, the strong interdisciplinary emphasis of the book will attract a non-specialist audience interested in keeping abreast of current theoretical and methodological approaches through evidence-based and practical examples.
Simulating Social Complexity
Social systems are among the most complex known. This poses particular problems for those who wish to understand them. The complexity often makes analytic approaches infeasible and natural language approaches inadequate for relating intricate cause and effect. However, individual- and agent-based computational approaches hold out the possibility of new and deeper understanding of such systems. Simulating Social Complexity examines all aspects of using agent- or individual-based simulation. This approach represents systems as individual elements having each their own set of differing states and internal processes. The interactions between elements in the simulation represent interactions in the target systems. What makes these elements "social" is that they are usefully interpretable as interacting elements of an observed society. In this, the focus is on human society, but can be extended to include social animals or artificial agents where such work enhances our understanding of human society. The phenomena of interest then result (emerge) from the dynamics of the interaction of social actors in an essential way and are usually not easily simplifiable by, for example, considering only representative actors. The introduction of accessible agent-based modelling allows the representation of social complexity in a more natural and direct manner than previous techniques. In particular, it is no longer necessary to distort a model with the introduction of overly strong assumptions simply in order to obtain analytic tractability. This makes agent-based modelling relatively accessible to a range of scientists. The outcomes of such models can be displayed and animated in ways that also make them more interpretable by experts and stakeholders. This handbook is intended to help in the process of maturation of this new field. It brings together, through the collaborative effort of many leading researchers, summaries of the best thinking and practice in this area and constitutes a reference point for standards against which future methodological advances are judged. This book will help those entering into the field to avoid "reinventing the wheel" each time, but it will also help those already in the field by providing accessible overviews of current thought. The material is divided into four sections: Introductory, Methodology, Mechanisms, and Applications. Each chapter starts with a very brief section called ‘Why read this chapter?’ followed by an abstract, which summarizes the content of the chapter. Each chapter also ends with a section of ‘Further Reading’ briefly describing three to eight items that a newcomer might read next.