Knowledge, Complexity and Innovation Systems

1. Front Matter

   Pages i-xii

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2. Knowledge, Complexity and Innovation Systems: Prologue

   1. Knowledge, Complexity and Innovation Systems: Prologue

      • Manfred M. Fischer, Josef Fröhlich

      Pages 1-17

3. Innovation Systems

   1. Front Matter

      Pages 19-19

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   2. Networks, National Innovation Systems and Self-Organisation

      • Pier Paolo Saviotti

      Pages 21-45

   3. Innovation Policy in the Systems of Innovation Approach: Some Basic Principles

      • Charles Edquist

      Pages 46-57

   4. The Globalisation of Technology and the European Innovation System

      • Daniele Archibugi

      Pages 58-75

4. Knowledge Creation and Spillovers

   1. Front Matter

      Pages 77-77

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   2. Scaling Knowledge Production: How Significant is the Region?

      • Arnoud Lagendijk

      Pages 79-100

   3. Knowledge Spillovers in a Spatial Context — A Critical Review and Assessment

      • Charlie Karlsson, Agostino Manduchi

      Pages 101-123

   4. The Role of Space in the Creation of Knowledge in Austria. An Exploratory Spatial Data Analysis

      • Manfred M. Fischer, Josef Fröhlich, Helmut Gassler, Attila Varga

      Pages 124-145

   5. Knowledge Spillovers in High Technology Agglomerations: Measurement and Modelling

      • Elsie Echeverri-Carroll

      Pages 146-161

5. Innovation, Knowledge and Regional Development

   1. Front Matter

      Pages 163-163

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   2. Inventive Knowledge and the Sources of New Technology: Regional Changes in Innovative Capacity in the United States

      • Luis Suarez-Villa

      Pages 165-180

   3. Urban Innovation and Collective Learning: Theory and Evidence from Five Metropolitan Cities in Europe

      • Roberta Capello

      Pages 181-208

   4. Distributed Knowledge in Complex Engineering Project Networks: Implications for Regional Innovation Systems

      • Neil Alderman

      Pages 209-227

   5. Endogenous Technological Change, Entrepreneurship and Regional Growth

      • Zoltán J. Ács

      Pages 228-247

6. Modelling Complexities

   1. Front Matter

      Pages 249-249

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   2. Modelling of Knowledge, Capital Formation, and Innovation Behaviour within Micro-Based Profit Oriented and Correlated Decision Processes

      • Günter Haag, Philipp Liedl

      Pages 251-274

   3. Communication and Self-Organisation in Complex Systems: A Basic Approach

      • Frank Schweitzer, Jörg Zimmermann

      Pages 275-296

   4. Agents, Interactions, and Co-Evolutionary Learning

      • David F. Batten

      Pages 297-316

In recent years there has been growing scientific interest in the triangular relationship between knowledge. complexity and innovation systems. The concept of'innovation systems' carries the idea that innovations do not originate as isolated discrete phenomena, but are generated through the interaction of a number of actors or agents. This set of actors and interactions possess certain specific characteristics that tend to remain over time. Such characteristics are also shared by national, regional, sectoral and technological interaction systems. They can all be represented as sets of [institutional] actors and interactions, whose ultimate goal is the production and diffusion of knowledge. The major theoretical and policy problem posed by these systems is that knowledge is generated not only by individuals and organisations, but also by the often complex pattern of interaction between them. To understand how organisations create new products, new production techniques and new organisational forms is important. An even more fundamental need is to understand how organisations create new knowledge if this knowledge creation lies in the mobilisation and conversion of tacit knowledge. Although much has been written about the importance of knowledge in management, little attention has been paid to how knowledge is created and how the knowledge­ creation process is managed. The third component of the research triangle concerns complexity.

• Complexity
• Evolution
• Innovation
• Innovation Policy
• Innovation Systems
• Knowledge
• Learning
• Regional Growth
• artificial intelligence
• calculus
• communication
• mathematics
• modeling
• technological change
• technology

• Department of Economic Geography & Geoinformatics, Vienna University of Economics and Business Administration, Vienna, Austria

  Manfred M. Fischer

• Business Division Systems Research, Technology-Economy-Environment, Austria Research Centre Seibersdorf, Seibersdorf, Austria

  Josef Fröhlich

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