Knowledge, Complexity and Innovation SystemsManfred M. Fischer, Josef Fröhlich Springer Science & Business Media, 20/06/2001 - 477 من الصفحات 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. |
المحتوى
Knowledge Complexity and Innovation Systems Prologue | 1 |
Innovation Systems | 19 |
Network National Innovation Systems and SelfOrganisation | 21 |
22 Complexity and Evolutionary Theories | 23 |
23 Implications of Evolutionary Theories for the NSI | 31 |
24 Conclusions | 43 |
Innovation Policy in the Systems of Innovation Approach Some Basic Principles | 46 |
33 Objectives of Innovation Policy | 47 |
115 Conclusions | 223 |
Endogenous Technological Change Entrepreneurship and Regional Growth | 228 |
122 Endogenous Technical Change | 230 |
123 Entrepreneurial Discovery | 233 |
124 Regional Growth | 236 |
125 Theory and Empirical Results | 242 |
126 Policy Implications | 244 |
Modelling Complexities | 249 |
35 The Role of Different Kinds of Innovation | 48 |
36 Systems of Innovation | 50 |
38 The SI Approach as a Framework for Designing Specific Innovation Policy | 55 |
The Globalisation of Technology and the European Innovation System | 58 |
42 The Globalisation of Technology | 59 |
43 The Quantitative Significance of the Globalisation of Technology and the Position of Europe | 61 |
44 Policy Analysis | 68 |
45 Conclusions | 74 |
Knowledge Creation and Spillovers | 77 |
Scaling Knowledge Production How Significant is the Region? | 79 |
52 The Region as a Natural and Unique Site of Knowledge Production | 80 |
53 The Region as a System of Innovation | 84 |
54 The Region as a Political Site of Knowledge Production | 87 |
The Region as a Spatially Reified Site of Knowledge Production | 91 |
56 The Region as a Socially Constructed Site of Knowledge Production | 96 |
The Region as a Site of Policy Innovation | 100 |
Knowledge Spillovers in a Spatial Context A Critical Review and Assessment | 101 |
62 Knowledge in Economic Theory | 103 |
63 Knowledge Spillovers A General Introduction | 105 |
64 Knowledge Spillovers over the Industry LifeCycle | 109 |
65 Knowledge Spillovers The Empirical Evidence | 110 |
66 Knowledge Spillovers Towards a Formalisation | 114 |
67 Knowledge Spillovers and Spatial Interaction | 118 |
68 Modelling the Influence of Knowledge Spillovers | 119 |
69 Technology Policy in a World with Knowledge Spillovers | 121 |
The Role of Space in the Creation of Knowledge in Austria An Exploratory Spatial Data Analysis | 124 |
72 Methodology and Data | 125 |
73 TimeSpace Patterns of Knowledge Production in Austria | 130 |
74 Local Inputs to Innovation An Assessment of Their Relative Significance in Knowledge Production | 136 |
75 Conclusions | 141 |
Knowledge Spillovers in High Technology Agglomerations Measurement and Modelling | 146 |
82 CorePeriphery Spatial Models | 148 |
83 Data and the Definition of High Technology | 154 |
84 Statistical Results | 155 |
85 Conclusions | 158 |
Innovation Knowledge and Regional Development | 163 |
Inventive Knowledge and the Sources of New Technology Regional Changes in Innovative Capacity in the United States | 165 |
92 The Emergence of the Sunbelt | 166 |
93 The Factors of Inversion | 172 |
94 Conclusions | 179 |
Urban Innovation and Collective Learning Theory and Evidence from Five Metropolitan Cities in Europe | 181 |
102 Learning in Cities | 182 |
103 Data Sample Characteristics and Methodology | 188 |
104 Innovative Behaviour of Firms in Metropolitan Cities | 191 |
105 The Determinants of Innovation in Cities | 197 |
The Role of Firms Size and Sectoral Specialisation | 199 |
107 Conclusions | 203 |
Distributed Knowledge in Complex Engineering Project Networks Implications for Regional Innovation Systems | 209 |
112 Complex Engineering Project Networks | 211 |
113 Regional Innovation Systems and Project Value Systems | 212 |
114 Case Studies | 217 |
Modelling of Knowledge Capital Formation and Innovation Behaviour within MicroBased Profit Oriented and Correlated Decision Processes | 251 |
132 Modelling Nested Innovation Processes | 254 |
133 Simulations for Selected Examples and Scenarios | 264 |
134 Conclusions | 273 |
Communication and SelfOrganisation in Complex Systems A Basic Approach | 275 |
142 Complex Systems and SelfOrganisation | 276 |
143 Complex Versus Minimalistic Agents | 278 |
144 An InformationTheoretic Approach | 281 |
145 Basic Model of Communicating Agents | 283 |
146 The MeanField Approach | 286 |
147 Spatial Information Distribution | 289 |
148 Conclusions | 295 |
Agents Interactions and CoEvolutionary Learning | 297 |
152 Schellings SelfOrganising Neighbourhoods | 298 |
153 Simulation via Cellular Automata | 302 |
154 Growing an Innovative Silicon Society | 306 |
155 CoEvolutionary Learning | 309 |
156 Discovering Artificial Economics | 311 |
157 Some Final Thoughts | 314 |
Major Actors in the Innovation Diffusion Process | 317 |
162 Major Actors in the Innovation Diffusion Process | 318 |
163 The First Principle of Individual Choice within the Collective | 328 |
164 Innovators and Innovating Elites | 332 |
165 Active Environment and SocioEcological Niches | 335 |
166 Conclusions | 340 |
Policy Issues | 343 |
Options Innovation and Metropolitan Development Novel Insights from NonLinear Dynamics | 345 |
172 Options and Metropolitan Development | 347 |
173 Options and Their Prices | 350 |
174 Derivatives Speculation and Development | 356 |
175 Derivatives Market Failures and Regulation | 361 |
176 Conclusions | 367 |
Spatial Dynamics and Government Policy An Artificial Intelligence Approach to Comparing Complex Systems | 369 |
182 Research Synthesis and MetaAnalysis | 372 |
183 Rough Set Analysis as an Artificial Intelligence Tool for Research Synthesis | 374 |
184 A Sample of Studies on Government and Growth | 377 |
A Multilevel Strategy Learning Approach | 379 |
186 Conclusions | 390 |
Does RD Infrastructure Attract HighTech StartUps? | 402 |
193 Definitions and Data | 405 |
194 HighTech StartUps in Eastern Germany | 406 |
195 Determinants for Regional Differences in the Number of HighTech StartUps | 410 |
196 Conclusions and Policy Implications | 419 |
423 | |
List of Figures | 455 |
List of Tables | 457 |
459 | |
467 | |
List of Contributors | 475 |
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عبارات ومصطلحات مألوفة
agents agglomeration approach areas Audretsch behaviour cluster competition complex components concept context countries derivatives markets distribution dynamic urbanisation economies economic development economic growth emergence empirical endogenous Equation equilibrium European evolutionary example existence externalities factors function geographical global globalisation Herfindahl Index high technology high-tech start-ups human capital impact important increase individual industry infrastructure innovation diffusion Innovation Policy innovation processes innovative activity institutions interaction investment Journal knowledge production knowledge spillovers learning-by-doing manufacturing markets metropolitan development milieu economies national innovation systems neoclassical economics observation OECD Oinas options organisations parameters patent pecuniary externalities percent political districts proximity R&D intensity regional development regional innovation system role rough set rule scatterplot scientific sectors simulation social spatial specialised specific structure studies Sunbelt suppliers systems of innovation Table tacit knowledge theory U.S.-Mexico border University urban variables