This book argues that complexity theory offers new departures for (spatial-) economic modelling. It offers a broad overview of recent advances in non-linear dynamics (catastrophe theory, chaos theory, evolutionary theory and so forth) and illustrates the relevance of this new paradigm on the basis of several illustrations in the area of space-economy. The empirical limitations - inherent in the use of non-linear dynamic systems approaches - are also addressed. Next, the application potential of biocomputing (in particular, neural networks and evolutionary algorithms) is stressed, while various empirical model results are presented. The book concludes with an agenda for further research.

A comprehensive core text from the expert in the field introducing students to the main issues of spatial systems modelling and analysis.

This book is open access under a CC BY-NC 4.0 license. This collected volume represents the final outcome of the COST Action IS1104 “The EU in the new complex geography of economic systems: models, tools and policy evaluation”. Visualizing the EU as a complex and multi-layered network, the book is organized in three parts, each of them dealing with a different level of analysis: At the macro-level, Part I considers the interactions within large economic systems (regions or countries) involving trade, workers migration, and other factor movements. At the meso-level, Part II discusses interactions within specific but wide-ranging markets, with a focus on financial markets and banking systems. Lastly, at the micro-level, Part III explores the decision-making of single firms, especially in the context of location decisions.

With the dawn of the twenty-first century comes the awareness that current rapid political-economic-social and technological transformations will affect our of living, by producing new forms of information, communications, common way market, work-style and leisure. In this context, human behaviour will certainly change its 'fixed' parameters. It is likely that the relationships between internal structures and external influences, between individual components and collective behaviour, as well as between multi-scale networks and interrelated dynamics, will show spatio-temporal patterns which will be difficult to predict by means of our usual tools. As a consequence, academic research is increasingly being required to play an active role in addressing new ways of understanding and forecasting the sets of interacting structures, ranging from the technical to the organizational, and from the social to the economic and political levels, while at the same time incorporating concerns about the 'new' economy, environment, society, information and technology. It is now evident that social science - especially spatial and economic scienc- needs innovative 'paths', together with continuous cross-fertilization among the many disciplines involved. In order to investigate these intriguing perspectives, we seem to have embarked on an era of methodological reflections - rather than developing strong theoretical foundations. This volume aims to provide an overview of these new insights and frontiers for theoretical/methodological studies and research applications in the space-economy.

A comprehensive core text from the expert in the field introducing students to the main issues of spatial systems modelling and analysis.

This book is open access under a CC BY-NC 4.0 license. This collected volume represents the final outcome of the COST Action IS1104 “The EU in the new complex geography of economic systems: models, tools and policy evaluation”. Visualizing the EU as a complex and multi-layered network, the book is organized in three parts, each of them dealing with a different level of analysis: At the macro-level, Part I considers the interactions within large economic systems (regions or countries) involving trade, workers migration, and other factor movements. At the meso-level, Part II discusses interactions within specific but wide-ranging markets, with a focus on financial markets and banking systems. Lastly, at the micro-level, Part III explores the decision-making of single firms, especially in the context of location decisions.

Complex systems analysis has become a fascinating topic in modern research on non-linear dynamics, not only in the physical sciences but also in the life sciences and the social sciences. After the era of bifurcation theory, chaos theory, syn- getics, resilience analysis, network dynamics and evolutionary thinking, currently we observe an increasing interest in critical transitions of dynamic real-world systems in many disciplines, such as demography, biology, psychology, economics, earth sciences, geology, seismology, medical sciences, and so on. The relevance of this approach is clearly re?ected in such phenomena as traf?c congestion, ?nancial crisis, ethnic con?icts, eco-system breakdown, health failures, etc. This has prompted a world-wide interest in complex systems. Geographical space is one of the playgrounds for complex dynamics, as is witnessed by population movements, transport ?ows, retail developments, urban expansion, lowland ?ooding and so forth. All such dynamic phenomena have one feature in common: the low predictability of uncertain interrelated events occurring at different interconnected spatio-temporal scale levels and often originating from different disciplinary backgrounds. The study of the associated non-linear (fast and slow) dynamic transition paths calls for a joint research effort of scientists from different disciplines in order to understand the nature, the roots and the con- quences of unexpected or unpredictable changes in complex spatial systems.