Hardback
Knowledge Diffusion and Innovation
Modelling Complex Entrepreneurial Behaviours
9781847209160 Edward Elgar Publishing
Modern economies are described as ‘knowledge based’. This book investigates the meaning of such a statement, assessing the relevance of knowledge and the channels through which knowledge is exchanged, both from a theoretical and an empirical perspective.
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Critical Acclaim
Contents
More Information
Modern economies are described as ‘knowledge based’. This book investigates the meaning of such a statement, assessing the relevance of knowledge and the channels through which knowledge is exchanged, both from a theoretical and an empirical perspective.
Moving within the realm of complexity theory, the authors provide a methodological assessment of the knowledge diffusion debate as well as presenting theoretical and applied models of knowledge diffusion and innovation. They illustrate how geography plays a role in shaping innovative patterns and how dense networks generally result in more innovative environments. The book concludes that establishing the right connections within such dense networks appears to be more crucial than any other factor, thus highlighting the importance of linkages (or the effects of their absence) within innovation systems.
Proposing a taxonomy of knowledge-sharing patterns, this book will be warmly welcomed by academics, researchers and postgraduate students in the areas of the economics of innovation, evolutionary economics and knowledge economics.
Moving within the realm of complexity theory, the authors provide a methodological assessment of the knowledge diffusion debate as well as presenting theoretical and applied models of knowledge diffusion and innovation. They illustrate how geography plays a role in shaping innovative patterns and how dense networks generally result in more innovative environments. The book concludes that establishing the right connections within such dense networks appears to be more crucial than any other factor, thus highlighting the importance of linkages (or the effects of their absence) within innovation systems.
Proposing a taxonomy of knowledge-sharing patterns, this book will be warmly welcomed by academics, researchers and postgraduate students in the areas of the economics of innovation, evolutionary economics and knowledge economics.
Critical Acclaim
‘. . . this book constitutes an important contribution to the literature on knowledge diffusion and networks. It provides novel results, raises new questions and hopefully will spur new work in this area.’
– Lorenzo Zirulia, Journal of Evolutionary Economics
‘The book uses state-of-the-art theorizing about a topic that has attracted a lot of attention in the past five years or so. It provides a very useful review of the literature, and is very well written and on a novel topic. I especially liked the methodological rigour in the exposition of the model, yet at the same time the text remains accessible to a wide readership. I highly recommend the book.’
– Koen Frenken, Utrecht University, The Netherlands
– Lorenzo Zirulia, Journal of Evolutionary Economics
‘The book uses state-of-the-art theorizing about a topic that has attracted a lot of attention in the past five years or so. It provides a very useful review of the literature, and is very well written and on a novel topic. I especially liked the methodological rigour in the exposition of the model, yet at the same time the text remains accessible to a wide readership. I highly recommend the book.’
– Koen Frenken, Utrecht University, The Netherlands
Contents
Contents: Part I: Theory 1. Introduction 2. Knowledge Economy: Old and New Issues 3. Modelling Knowledge and its Diffusion Patterns: A Pathway Towards Complexity 4. Knowledge Diffusion and Innovation: An Agent-based Approach Part II: Empirical Studies and Model Validations 5. Empirical Studies on Knowledge Flows 6. Theoretical and Applied Methodologies of Agent-based Models 7. Validating the Model of Knowledge Diffusion and Innovation 8. Final Remarks and Future Research References Index