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In the global information society, innovation is a highly pervasive process that influences all facets of human life: cultural, economic, political, and institutional. A desire to comprehend the impacts of innovative change on so many areas of urban life prompted the research project that has resulted in the publication of this volume. Our research confirms that we are presently in the midst of an era of rapid and explosive change. The primary engine driving this latest transformation of the post-industrial society is generally thought to be technological. But such an explanation is too narrow. Broadly speaking, the age in which we find ourselves could be more aptly described as a global, knowledge-intensive age. Many of today's knowledge-intensive activities, like research and development (R&D) programs, are being conducted with relative ease on a multinational scale. As well as science having an increasing impact on processes of innovation, R&D activities also have become more complex. We can observe a growing sophistication of learning-by-doing among creative economic agents. This more sophisticated era of global knowledge exchange is facilitated by major advances in our infrastructure networks. In this highly interactive world, many innovations are by-products of collective exchanges between cities far apart, simplified by the ease of transport and communication. Thus, there is a need for us to look more closely at various collective sequences of learning, knowledge exchange and innovation in a spatial setting. This is the primary purpose of this book.
Covering a broad range of topics, this text provides a comprehensive survey of the modeling of chaotic dynamics and complexity in the natural and social sciences. Its attention to models in both the physical and social sciences and the detailed philosophical approach make this a unique text in the midst of many current books on chaos and complexity. Including an extensive index and bibliography along with numerous examples and simplified models, this is an ideal course text.
In the global information society, innovation is a highly pervasive process that influences all facets of human life: cultural, economic, political, and institutional. A desire to comprehend the impacts of innovative change on so many areas of urban life prompted the research project that has resulted in the publication of this volume. Our research confirms that we are presently in the midst of an era of rapid and explosive change. The primary engine driving this latest transformation of the post-industrial society is generally thought to be technological. But such an explanation is too narrow. Broadly speaking, the age in which we find ourselves could be more aptly described as a global, knowledge-intensive age. Many of today's knowledge-intensive activities, like research and development (R&D) programs, are being conducted with relative ease on a multinational scale. As well as science having an increasing impact on processes of innovation, R&D activities also have become more complex. We can observe a growing sophistication of learning-by-doing among creative economic agents. This more sophisticated era of global knowledge exchange is facilitated by major advances in our infrastructure networks. In this highly interactive world, many innovations are by-products of collective exchanges between cities far apart, simplified by the ease of transport and communication. Thus, there is a need for us to look more closely at various collective sequences of learning, knowledge exchange and innovation in a spatial setting. This is the primary purpose of this book.
Covering a broad range of topics, this text provides a comprehensive survey of the modelling of chaotic dynamics and complexity in the natural and social sciences. Its attention to models in both the physical and social sciences and the detailed philosophical approach make this an unique text in the midst of many current books on chaos and complexity. Part 1 deals with the mathematical model as an instrument of investigation. The general meaning of modelling and, more specifically, questions concerning linear modelling are discussed. Part 2 deals with the theme of chaos and the origin of chaotic dynamics. Part 3 deals with the theme of complexity: a property of the systems and of their models which is intermediate between stability and chaos. Including an extensive index and bibliography along with numerous examples and simplified models, this is an ideal course text.
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