Innovation Networks: New Approaches in Modelling and Analyzing

ISBN-13: 9783642100772 / Angielski / Miękka / 2010 / 330 str.

Springer

Opis

social network analysis has been an established eld since the 1950s; in computer and information sciences, in biology, and of course in mathematics (graph theory) networks are central representations of objects and methods (De Nooy, forthc- ing). More detailed bibliometric studies have examined the individual, cognitive, and institutional composition of complex network theory (Morris and Yen 2004), and social network theory (Otte and Rousseau 2002). Among the more impor- ] tant pieces of literature are Borner et al. (2007), Bornholdt and Schuster (2003), Buchanan (2002), Dorogovtsev and Mendes (2003), Otte and Rousseau (2002), Newman (2003), and Watts (1999, 2004). Of these, Borner ] et al. (2007) stand out because they have most recently re-examined network science, considering it as a possible innovation in information science. All the reviews mentioned include efforts to build bridges between different scienti c disciplines and specialties. In this book we draw particular attention to the link between evolutionary economics and statistical physics. Despite this impressive development, claims that an entirely new science has been created (Barabasi 2002) have nevertheless been the subject of criticism. - depth analyses of a subset of complex networks contributions (1991 2003) have shown that the notion of complex networks was already prevalent in a number of different elds before it became practically a brand name or the popular label for a new specialty area in physics, or a new cross-disciplinary paradigm."

Recenzje

From the reviews:

"This book is a worthwhile contribution aimed at narrowing down the divergence between the socioeconomic research and the physicists' research on networks. ... provides a valuable resource for those interested in how network structures affect innovation and their outcome ... . the book presents a rich set of models and empirical evidence of networks that mainly represent the share of knowledge between nodes (firms). Readers looking for methods and modelling techniques across innovation studies and statistical physics will find this book of valuable use." (Tommaso Ciarli, Journal of Artificial Societies and Social Simulation, Vol. 13 (1), 2010)

"This book is an edited collection of ten articles that address aspects of the relationship between innovation and networks. ... will be of much value not only to those interested in complex economic or social behaviour, but also to those interested in graph-theoretic, statistical, probabilistic, and algebraic structure of networks." (Charles J. Colbourn, Zentralblatt MATH, Vol. 1174, 2009)

Spis treści

Innovation networks in economics.- Knowledge Networks: Structure and Dynamics.- Death of Distance in Science? A Gravity Approach to Research Collaboration.- Evolution and Dynamics of Networks in #x2018;Regional Innovation Systems#x2019; (RIS).- Agent-Based Modelling of Innovation Networks #x2013; The Fairytale of Spillover.- Structural Holes, Innovation and the Distribution of Ideas.- Introduction: Network Perspectives on Innovations: Innovative Networks #x2013; Network Innovation.- Innovation networks in complex theories.- Tools from Statistical Physics for the Analysis of Social Networks.- Modeling Evolving Innovation Networks.- Propagation of Innovations in Complex Patterns of Interaction.- Sensitive Networks #x2013; Modelling Self-Organization and Innovation Processes in Networks.

Blurb

The science of graphs and networks has become by now a well-established tool for modelling and analyzing a variety of systems with a large number of interacting components. Starting from the physical sciences, applications have spread rapidly to the natural and social sciences, as well as to economics, and are now further extended, in this volume, to the concept of innovations, viewed broadly.

In an abstract, systems-theoretical approach, innovation can be understood as a critical event which destabilizes the current state of the system, and results in a new process of self-organization leading to a new stable state.

The contributions to this anthology address different aspects of the relationship between innovation and networks. The various chapters incorporate approaches in evolutionary economics, agent-based modeling, social network analysis and econophysics and explore the epistemic tension between insights into economics and society-related processes, and the insights into new forms of complex dynamics.