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Leveraging Knowledge Communication for Innovation

Framework, Methods and Applications of Social Network Analysis in Research and Development

Series:

Tobias Müller-Prothmann

The paradigm of social network analysis (SNA) is widely recognized as a potential approach to analyze, evaluate, and influence communication processes. The author argues that SNA proves useful as a theoretical concept and as a practical tool for knowledge communication in research and development (R&D). The context of innovative knowledge generation in organizational R&D environments is introduced very broadly with reference to the existing literature. The pragmatic approach of networks is outlined as a powerful concept to grasp the social relationships between individuals as well as between social aggregates for conceptual and analytical purposes. Based on three case studies, methods of SNA are simplified and illustrated according to their basic steps to meet practical needs and show their usefulness for business practice. Moreover, the book provides examples for interventions and follow-up activities to improve processes of organizational knowledge communication based on SNA.

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List of Tables xi

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List of Tables 2.1 Four Aspects of Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2 Knowledge Management Matrix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 2.3 Knowledge Networks Reference Model . . . . . . . . . . . . . . . . . . . . . . . . . 62 3.1 Types of Network-Like Structures: A Snapshot . . . . . . . . . . . . . . . . . . . . . 88 3.2 Basic Network Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 4.1 Basic Characteristics of R&D Management Generations . . . . . . . . . . . . . . . . 119 4.2 Innovation Phases and Key Communication Domains . . . . . . . . . . . . . . . . . . 122 4.3 Network Levels and Knowledge Management Processes . . . . . . . . . . . . . . . . 126 5.1 Adjacency Matrix of Social Relationships . . . . . . . . . . . . . . . . . . . . . . . . 149 5.2 Case Study 2: Descriptive Statistics of Subjective Relevance of Knowledge Exchange and Networking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 5.3 Case Study 2: Descriptive Statistics of Subjective Relevance of Domain-related Knowl- edge Exchange and Networking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 5.4 Case Study 2: Correlations of Domain-related Relevance of Knowledge Exchange . . . 194 5.5 Case Study 2: Correlations of Dimension-related Relevance of Knowledge Exchange . 195 5.6 Case Study 2: Entrepreneurial Activity and Relevance of Networking . . . . . . . . . 196 5.7 Case Study 2: Reciprocity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198 5.8 Case Study 2: Actor Degree Centrality . . . . . . . . . . . . . . . . . . . . . . . . . . 198 5.9 Case Study 2: Domain-related Networks: Density and Centralization . . . . . . . . . . 200 5.10 Case Study 2: Blocks of the Knowledge Exchange Network for Project and Customer Acquisition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201 5.11 Case Study 2: Domain-related Actor Centralities . . . . . . . . . . . . . . . . . . . . 201 5.12 Case Study 2: Domain-related Central Actors . . . . . . . . . . . . . . . . . . . . . . 202 5.13 Case Study 2: Comparison between All Actors and Central Actors 1 . . . . . . . . . . 204 5.14 Case Study 2: Comparison between All Actors and Central Actors 2 . . . . . . . . . . 204 5.15 Case Study 2: Descriptive Statistics All vs. Central Actors . . . . . . . . . . . . . . . 205 5.16 Case Study 2: Central Actors in t2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208 5.17 Case Study 2: Central Actors in t1&t2 and All Actors . . . . . . . . . . . . . . . . . . 208 5.18 Case Study...

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