Eva Panetti 
The Dynamics of Local Innovation Systems [EPUB ebook] 
Structures, Networks and Processes

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This book offers a comprehensive overview of the dynamics underpinning the successful performance of local innovation systems (LIS), that is, spatial concentration of innovation activities in specific geographical areas, characterized by the synergetic co-localization of research centers, innovation-driven enterprises, large corporations and capital providers.

The reader will gain a deeper knowledge of LIS theory and learn about the theoretical and empirical challenges of studying the LIS from a relational perspective. The book also provides an analytical framework to explore the level of connectivity among LIS actors through the use of social network analysis (network architecture) and second, to assess the variety of different types of relationships that local actors put in place to produce innovation within the LIS (network portfolio). More specifically, this book explores which network configuration is associated with a successful LIS by deriving evidence from the empirical study of the biopharma LIS in the Greater Boston Area (GBA), which has been exemplified as a benchmark case in terms of successful LIS performance.

This book also contributes to the theoretical debate about the optimal configuration of network structure (e.g. network closure vs. network openness). In capturing the heterogeneous nature of the LIS demography, it addresses the challenges brought about by the adoption of a holistic approach. Finally, the study provides insights into the network portfolio composition, which has been underexplored by extant literature. Besides addressing the scientific community in the field, this book will also be a valuable resource with practical implications for policymakers and those actors willing to undertake an active role in the development of an LIS in their own regions.

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Format EPUB ● Pages 120 ● ISBN 9780429514449 ● Publisher Taylor and Francis ● Published 2019 ● Downloadable 3 times ● Currency EUR ● ID 6984987 ● Copy protection Adobe DRM
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