Innovation in Clusters

This book aims to bind together latest theories on creation of innovative clusters and operating modalities, empirical analysis, and several new formal models describing cluster formation and dynamics. Another objective of the book is the analysis of the role of the innovative activities on the economic performances of the firm during the crisis, focusing the attention on the complementarities existing among the innovative dimensions, hypothesizing a positive role of integrated innovative strategies in increasing the firm resilience to the challenges brought by the economic crisis. The part of empirical analysis contains a comprehensive survey of different international legislation sources useful for deep studies of influential factors and peculiarities. In this book international statistical reports on economic activity and business cases of successful application of clusters model are described for Western Europe and BRIC. This book also presents authors findings in the domain of mathematical and simulation modeling of the major elements of cluster and innovation management.

Offers insight into development of innovative clusters and their analysis elements Presents latest insights on University-industry relations in the innovative clusters Guides the reader into formal models to analyze clusters and innovation

Autorentext
Nataliya Klimova, PhD is the Deputy Director of National Research University Higher School of Economics, Nizhny Novgorod, Russia Professor Oleg Kozyrev is the Director of National Research University Higher School of Economics, Nizhny Novgorod, Russia Professor Eduard BABKIN is the Deputy Director of National Research University Higher School of Economics, Nizhny Novgorod, Russia.

Inhalt
Introduction.- The main characteristics of the cluster model on the modern srage.- Problems of modern Russian Industry and the development of clusters.- A methodology for evaluating the efficiency of University clusters.- Formal approaches to cluster modeling.- A new approach to designing and modeling the evolution of clusters.- Conclusion.