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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

A dynamical model of a central place system is described which, derived from the concepts underlying dissipative structures, takes into account the self-organizing aspects of urban evolution, and shows the importance both of chance and of determinism in such systems. A theoretical evolution is discussed together with the modified dynamics of different possible decisions showing the long-term consequences of these. A recent application of this new theory to the evolution of the Bastogne region of Belgium is briefly described, and conclusions are drawn as to the real difficulties involved in decisionmaking on the part of national, regional, and municipal authorities.

This paper is part II of "Towards a model of urban evolution." This paper defines a formal model of the Signature of an urban space, comprised of: an urban genome which captures the expected groups (i.e., users) and activities (i.e., uses) of physical forms; a description of the actual activities and groups of the physical forms; and the signals that are communicated within and among urban spaces. Central to the model is a formeme, which provides the building blocks for a Signature. A formeme captures the interactions among physical forms, groups and activities. We then show how various metrics can define an urban area based on its Signature, and that these metrics can be used to measure similarity of urban spaces. The Signature and its underlying formemes capture the sources of variations in urban evolution.

This paper seeks to develop the core concepts of a model of urban evolution. It proceeds in four major sections. First we review prior adumbrations of an evolutionary model in urban theory, not-ing their potential and their limitations. Second, we turn to the general sociocultural evolution litera-ture to draw inspiration for a fresh and more complete application of evolutionary theory to the study of urban life. Third, building upon this background, we outline the main elements of our proposed model, with special attention to elaborating the value of its key conceptual innovation, the "formeme." Last, we conclude with a discussion of what types of research commitments the overall approach does or does not imply, and point toward the more formal elaboration of the model that we undertake in "Towards a Model of Urban Evolution II" and "Towards a Model of Urban Evo-lution III."

Here Sir Terry Farrell, who has built an international career as an architect-planner, encourages other planners and architects to follow the biologists-look at, learn from, and, indeed, admire the nature of the forces that drive the change, and then with humility and respect work with them to nudge, anticipate and prepare for where it takes us. Searching for patterns within the apparent turbulence and complexity, he analyses the notions of urban design and urban evolution and examines whether or not they need necessarily be seen as opposing one another. The first two chapters discuss emerg.

Cover; Title Page; Copyright Page; Acknowledgements; Contents; Preface; Introduction; Chapter 1: The Emergence of Emergence; Chapter 2: The Urbicultural Revolution; Chapter 3: Connectedness and the Nurturing of Invention; Chapter 4: The DNA of Habitat; Chapter 5: Time, Layers and City Identity; Chapter 6: Architecture Out of Urbanism; Chapter 7: The High Art of Adaptation; Chapter 8: Urban Activism; Chapter 9: The Era of the Digital City; Conclusion; Bibliography; Picture Credits.

Urban construction activities are subject to periods of fast expansion followed by periods of slow growth. Some of these expansions are limited in size, while others are huge. Therefore, it is not surprising that equilibrium-oriented classical models of urban spatial structure are hard pressed to explain the formation of modern cities with polycentric structure and births of subcenters in particular. To understand the development of cities' spatial patterns we present a model of urban spatial dynamics that is driven by two types of real-estate entrepreneurs that differ in their degree of risk aversion. The developers act in the shadow of the city planning board that formulates urban development policy and defines the boundaries of future residential expansions. The model's salient feature is the time lag between the time of purchase of property rights by land developers and the time of the realization of revenues. We assume that this lag varies in space, being much larger in locations that are not zoned for building. It can be reduced by the planning board in cases of high demand for dwellings. We use the model to demonstrate how the interaction between demand for dwellings, the choices taken by each type of developer, and planning policies leads to the creation of new urban subcenters. The model dynamics are characterized by long out-of-equilibrium periods followed by sudden bursts of construction activity that resembles self-organized criticality.

With the use of French and US data, new and systematic evidence is provided about the rapid location changes of industries across cities (the fast). Cities are also slowly moving up and down the urban hierarchy (the slow), while the size distribution of cities is skewed to the right and very stable (the still). The model proposed here reproduces these three features. Small, innovation-driven shocks lead to the churning of industries across cities. Then, cities slowly grow or decline following net gains or losses of industries. These changes occur within a stable distribution. The quantitative implications of the model are also explored. (JEL R12, R32)

AbstractIn this paper we empirically investigate the dynamics of employment and industrial location across municipalities in the state of Sao Paulo, Brazil. Making use of a number of indicators we have illustrated that the state's urban system is becoming more complex and facing a number of considerable changes. In the main part of the paper spatial econometric models are estimated and our results provide preliminary evidence of the role played by geographical and economic factors on employment growth and industrial spatial reallocation. The analysis suggests that diversified economies within metropolitan areas and close to the state's capital are subject to relatively more intense dynamics. However, controlling for a range of variables, smaller towns have been growing and churning more rapidly than the large cities. We have also evidenced that the presence of universities and the participation of the private sector are important for this dynamism. We also find that employment growth is subject to local spatial externalities but industrial churning is not.Resumen. En este artículo se investigan empíricamente las dinámicas de empleo y localización industrial en municipios del estado de São Paulo, Brasil. Mediante el empleo de una serie de indicadores, hemos mostrado que el sistema urbano estatal está haciéndose cada vez más complejo y afronta una variedad de cambios considerables. En la parte principal del artículo se estiman modelos econométricos espaciales, cuyos resultados proporcionan pruebas preliminares del papel que juegan los factores geográficos y económicos en el crecimiento del empleo y la redistribución espacial de la industria. El análisis sugiere que las economías diversificadas dentro de las áreas metropolitanas cercanas a la capital estatal están sujetas a dinámicas más intensas en términos relativos. Sin embargo, al controlar una serie de variables, se observa que las ciudades más pequeñas han estado creciendo y mostrando una mayor fluctuación de industrias que las grandes ciudades. También hemos aportado pruebas de que la presencia de universidades y la participación del sector privado son importantes en este dinamismo. También hemos hallado que el crecimiento del empleo está sujeto a externalidades espaciales locales, pero que la fluctuación industrial no lo está.graphic

This paper develops a formal model of urban evolution in terms of 1) sources of variations; 2) principles of selection; and 3) mechanisms of retention. More specifically, regarding (1) it defines local and environmental sources of variation and identifies some of their generative processes, such as recombination, migration, mutation, extinction, and transcription errors. Regarding (2), it outlines a series of selection processes as part of an evolutionary ecology of urban forms, including density dependence, scope dependence, distance dependence, content dependence, and frequency dependence. Regarding (3), it characterizes retention as a combination of absorption and restriction of novel variants, defines mechanisms by which these can occur, including longevity, fidelity, and fecundity, and specifies how these processes issue in trajectories define by properties such as stability, pace, convergence, and divergence. A conclusion reviews the effort and looks forward to computer simulation and data-driven applications, as well as focused theoretical extensions of parts of the model.