الصفحة 1
الصفحة 1
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Learning from clusters : A critical assessment from an economic-geographical perspective

Edited volumes run the danger of being a hotchpotch of contributions on a wide variety of topics. Here, we have explicitly focused on a central theme in contemporary economic geography and regional science, namely the relationship between learning, innovation and clustering. Internationally renowned scientists made both theoretical and empirical contributions to this volume. We think this book constitutes a broad palette of contemporary thinking and research on the relationship between spatial concentration and innovation and hope it will play a significant role in future debates on this issue.

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Browning Agents and Active Particles : Collective Dynamics in the Natural and Social Sciences

Lays out a vision for a coherent framework for understanding complex systems'' (from the foreword by J. Doyne Farmer). By developing the genuine idea of Brownian agents, the author combines concepts from informatics, such as multiagent systems, with approaches of statistical many-particle physics. This way, an efficient method for computer simulations of complex systems is developed which is also accessible to analytical investigations and quantitative predictions. The book demonstrates that Brownian agent models can be successfully applied in many different contexts, ranging from physicochemical pattern formation, to active motion and swarming in biological systems, to self-assembling of networks, evolutionary optimization, urban growth, economic agglomeration and even social systems.

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A life cycle for clusters? : The dynamics of agglomeration, change, and adaption

The phenomenon of non-random spatial concentrations of firms in one or few related sectors (clusters) is intensively debated in economic theory and policy. The euphoria about successful clusters however neglects that historically, many thriving clusters did deteriorate into old industrial areas. This book studies the determinants of cluster survival by analyzing their adaptability to change in the economic environment. Linking theoretic knowledge with empirical observations, a simulation model (based in the N/K method) is developed, which explains when and why the cluster's architecture assists or hampers adaptability. It is found that architectures with intermediate degrees of division of labour and more collective governance forms foster adaptability. Cluster development is thus path dependent as architectures having evolved over time impact on the likelihood of future survival.

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