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Part 2: CI and Governance
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Part 2: CI and Governance
by Amos David
Competitive Intelligence and Decision Problems
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Part 1: Models and Tools
Chapter 1: Model Use: From a Decision-Making Problem to a Set of Research Problems
1.1. Introduction: why model?
1.2. General presentation of the Watcher Information Search Problem model
1.3. Dimensions and aspects of the model
1.4. Description of model elements
1.4.1. Elements describing the decision problem and its context
1.4.2. Chosen solutions and the final decision
1.4.3. Supporting elements of the information problem
1.4.4. Demand, stakes, and context
1.4.5. Information indicators
1.4.6. Elements of research problems
1.4.7. Analysis and presentation of results
1.4.8. Common parameters for all model elements
1.4.9. Knowledge building through annotation
1.5. Conclusion: toward flexibility in the model
1.6. Bibliography
Chapter 2: Analytical Tools for Competitive Intelligence: from Data Collection to Data Processing
2.1. Introduction
2.2. Overview of the multidimensional analysis model
2.2.1. Information process
2.2.2. Process architecture
2.3. Application of the multidimensional analysis model
2.3.1. Preliminary data
2.3.2. Data visualization
2.4. Conclusion
2.5. Bibliography
Chapter 3: The Synergy of Knowledge Management and Competitive Intelligence
3.1. Introduction
3.2. Theoretical context
3.2.1. Definitions of knowledge
3.2.1.1. Types of knowledge
3.2.2. Competitive intelligence
3.2.3. KM in CI
3.2.3.1. A generic model for CM: application to industrial systems
3.2.3.2. KC in an equipment repair and diagnostics system
3.2.3.3. Knowledge acquisition and modeling for CM: lessons learned
3.2.3.4. Software engineering for KC using CBR: case structure
3.2.3.5. Information security systems and KM
3.2.3.6. Business process modeling through KM
3.2.3.7. KM: planning for the future
3.2.3.8. KM in industry and government: security versus sharing
3.2.3.9. KC in research and design projects: an integrated and diversified approach
3.2.3.10. Overview: classification of works
3.2.3.11. Evaluation criteria for methodologies
3.2.3.12. Application evaluation criteria
3.2.3.13. Evaluation criteria based on principles
3.2.3.14. Summary of evaluation of KM methodologies, principles, and systems
3.3. Knowledge acquisition strategy
3.3.1. Action-based knowledge acquisition
3.4. Formalization of knowledge
3.4.1. KC structure for CI projects
3.4.2. Architecture for KM in CI projects
3.4.2.1. Case study of a DP: moral decadence among young people
3.4.2.1.1. Scenario
3.4.2.2. Action-based knowledge use
3.5. Conclusion
3.6. Appendices
3.6.1. Appendix A: knowledge acquisition based on actor activities
3.6.2. Appendix B: capitalization scenario in decision making
3.7. Bibliography
Chapter 4: Collaborative Information Seeking in the Competitive Intelligence Process
4.1. Introduction
4.2. The CI process
4.3. From information retrieval to CIR
4.3.1. Information retrieval
4.3.2. Collaborative information behavior
4.3.3. CIS and retrieval
4.3.3.1. Domain knowledge
4.3.3.2. Competence in search methodology
4.3.3.3. System knowledge
4.3.3.4. Knowledge of information sources
4.3.3.5. Knowledge of collaborators
4.4. Facilitation and management of CIS
4.4.1. The conceptual framework
4.4.1.1. Communication
4.4.1.2. Modes of collaboration
4.4.1.3. Coordination of user interactions
4.4.1.4. Managing knowledge in collaboration
4.4.2. Communication model for CIS
4.4.2.1. User
4.4.2.2. Object
4.4.2.3. Context
4.4.3. Application context
4.5. Collective information seeking scenario
4.6. Conclusion
4.7. Bibliography
Chapter 5: Study of Risk Factors in Competitive Intelligence Decision Making: A Cognitive Approach
5.1. Decision making and decision problems
5.1.1. Introduction
5.1.2. Fundamental aspects of the decision problem
5.1.3. Decision and cognitive capacity
5.1.4. Decisions in the context of CI
5.2. Risks and RFs in CI
5.2.1. Introduction
5.2.2. Actors and their interactions in CI
5.2.3. Risks and RFs
5.3. Cognitive capacity, a risk, and decision factor
5.3.1. Introduction
5.3.2. Cognitive capacity and its effects on decision making
5.3.3. Cognitive model of RFs
5.4. Conclusion
5.5. Bibliography
Chapter 6: Multimedia Information Seeking Through Competitive Intelligence Process
6.1. Introduction
6.2. The two dimensions of CI: decisions and information
6.3. Multimedia information: between complexity and accessibility
6.4. The information seeking process: an overview of paradigmatic evolution
6.5. Actors involved in information seeking processes and problem solving
6.5.1. Terminology: the notion of the user
6.5.2. Terminology: the notion of use
6.6. Applying a user-centered approach to facilitate multimedia information seeking
6.6.1. Multimedia information granulation to support multimedia information seeking processes
6.6.2. Integration of the representation of the user into the multimedia information retrieval process
6.6.2.1. Representation of user characteristics
6.6.2.2. Representation of user knowledge
6.6.2.2.1. Representation of user knowledge of the system used
6.6.2.2.2. Representation of user knowledge in the research domain
6.6.2.3. Representation of user competences
6.6.2.4. Representation of user preferences
6.6.2.5. Representation of information needs
6.6.2.5.1. Awareness of the information need
6.6.2.5.2. Information needs and knowledge: paradoxal or complementary?
6.6.2.5.3. Transformation of the information need in the context of information use
6.7. Conclusion
6.8. Bibliography
Chapter 7: Strategies for Analyzing Chinese Information Sources from a Competitive Intelligence Perspective
7.1. Introduction
7.2. Chinese scientific information as an essential source of information
7.3. A global vision of the sector through patent analysis
7.4. Chinese sources of scientific information
7.5. Automatic processing of information by bibliometrical analysis of metadata
7.5.1. Specificities of a Chinese-language corpus
7.5.2. Analysis and results
7.5.3. Validation and comparison
7.6. Conclusion
7.7. Bibliography
Chapter 8: Generic Tagging Strategy Using a Semio-Contextual Approach to the Corpus for the Creation of Controlled Databases
8.1. Introduction
8.2. The adaptive journal concept
8.2.1. The notion of semantic tagging: selection of relevant information
8.2.2. Modeling knowledge: organizing relevant information
8.2.3. Recomposed documents: sorting and presenting relevant information
8.2.3.1. The extraction—recomposition principle
8.2.3.2. The decontextualization—recontextualization principle
8.3. A generic tagging strategy: models using the ASCC
8.3.1. Categorizing meaning
8.3.2. The ASCC at the nano-level of information in an adaptive journal
8.3.3. ASCC at micro-level in an adaptive journal
8.3.4. ASCC for authors in an adaptive journal
8.3.5. ASCC at meso-level in an adaptive journal
8.3.6. ASCC at macro-level in an adaptive journal
8.4. Conclusion
8.5. Bibliography
Chapter 9: Design and Development of a Model for Generating and Exploiting Annotation in the Context of Economic Intelligence
9.1. Introduction
9.2. Annotation as a concept
9.3. Annotation in EI
9.3.1. Annotation for knowledge elicitation
9.3.2. Annotation in information retrieval
9.3.3. Annotation as value-added information
9.3.4. Requirements for annotation model
9.4. Proposition
9.4.1. Annotation creation
9.4.2. Annotation exploitation
9.5. Annotation model and architectural components
9.5.1. Annotation schema
9.5.2. AMTEA architecture
9.6. Bibliography
Chapter 10: Contribution of Cognitive Sciences to Document Indexing in Scientific, Technical, and Economic Watch for Competitive Intelligence
10.1. Introduction
10.2. Functionality of the PIETRA platform: general presentation
10.3. Global usage strategy
10.4. Operation of the platform
10.4.1. Watch profiles
10.4.2. The pivot language
10.4.2.1. Functions
10.4.3. Memory indexing
10.4.4. Validation
10.4.4.1. Phase 3: statistical analysis
10.4.4.2. Examples of application: example 1
10.4.4.2.1. Creation of initial corpus
10.4.4.2.2. Memory indexing (corpus 2)
10.4.4.2.3. Statistical processing
10.4.4.3. Example 2
10.4.4.3.1. Translation into the pivot language
10.4.4.3.2. Presentation of an extract from the translation of the pivot language
10.4.4.3.3. Results
10.5. Elaborated databases
10.6. Conclusion
10.7. Bibliography
Part 2: CI and Governance
Chapter 11: Integration of Competitive Intelligence and Watch in an Academic Scientific Research Laboratory
11.1. Introduction
11.2. Existing structures in universities and research organizations
11.3. Research structures, research actors and evaluation in the context of CI integration
11.4. Clusters and their power of attraction
11.5. Strategic analysis units, a support for the development of laboratories and of CI
11.5.1. GICC UMR
11.5.2. The LSCC: strategic intelligence survey unit
11.5.2.1. Available facilities
11.5.2.2. Potential results and user references
11.5.2.3. Industrial applications in France (extract)
11.5.2.4. Platform finance
11.5.2.5. Example: Thailand
11.6. Conclusion
11.7. Bibliography
Chapter 12: E-Health and Societal and Territorial Intelligence in France: Collective Knowledge Production Issues and New Network Interface Organizations
12.1. Introduction
12.2. E-health, the convergence of health issues, and ICT
12.2.1. Compartmentalization and crisis in health systems
12.2.2. The development of e-health
12.2.3. Evolution of medical practice, computerization, and ICT use
12.3. Toward a new territorialization of healthcare management
12.3.1. Reorganization of the health system by regionalization
12.3.2. Affirmation of new organizations of innovative interfaces as sociotechnical forms, projects, and apparatus
12.4. E-health and CI: societal dimensions and territorial intelligence
12.4.1. E-health and CI
12.4.2. The convergence of societal and territorial intelligence: a global intelligence approach to complexity
12.5. Issues in the production of collective knowledge
12.5.1. Coordination: the complementarity of information and communication
12.5.2. Information needs for decision assistance and new tools
12.5.3. Evolution of professions and new professions
12.6. Shared information systems at regional level: a step toward societal and territorial information systems with a health component?
12.6.1. Issues in the construction of regionalized information systems
12.6.2. Societal and territorial intelligence and building trust between actors around sociotechnical systems
12.6.3. Collective knowledge production: the core of new governance in the health system
12.7. Conclusion
12.8. Bibliography
Chapter 13: Governance and Short-Term Product Development in Clusters — An Example: The FIRE Application
13.1. Introduction
13.2. Considerations on the development of clusters
13.3. Grievances of small businesses and industries
13.4. The context of the SCS cluster, PACA, France
13.5. Origins of the FIRE project
13.5.1. From idea to creation
13.5.2. Industrial aims of the project
13.6. From design to creation and commercialization
13.6.1. General event sequence from an idea to a commercial product
13.7. Conclusion
13.8. Bibliography
Chapter 14: Competitive Intelligence and the Development of Corporate Universities
14.1. Introduction
14.2. Competitive intelligence
14.3. Corporate universities
14.4. The role of CI in the creation of corporate universities
14.5. Corporate universities and potential domains of action
14.6. Integrated CI services in corporate universities
14.7. Conclusion
14.8. Bibliography
Chapter 15: Emerging Functions for Driving Competitive Intelligence at Regional Level
15.1. Regional systems for CI
15.1.1. History
15.1.2. Definition of regional systems for CI
15.1.3. System actors
15.2. Competitiveness clusters
15.2.1. What is a cluster?
15.2.2. The contribution of CI to clusters
15.2.3. Evaluation of centers
15.2.4. Review of the first phase of cluster support: 2006–2008
15.2.5. Launch of the second phase of cluster support: 2009–2011
15.3. Survey of CI systems
15.3.1. Results of the survey
15.3.2. Comments
15.4. The role of coordinator
15.4.1. Roles and activities of the coordinator
15.4.1.1. Ten strategic roles of the coordinator
15.4.2. Competences of the coordinator
15.5. Conclusion
15.6. Bibliography
Chapter 16: Attractiveness of Territories and Territorial Intelligence: Indicators
16.1. Introduction
16.2. Attractiveness and value of a territory: elements of analysis
16.2.1. Attractiveness of territories: creating and harnessing value
16.2.1.1. Using attractiveness to create value
16.2.1.2. Using attractiveness to harness value
16.2.2. TI and attractiveness: measuring the value of a territory
16.3. Attractiveness and implementation of a TI approach
16.3.1. Territorial attractiveness: comparison of studies on the IDF region
16.3.2. The participatory method
16.3.3. Information and attractiveness
16.4. Conclusion
16.5. Bibliography
16.6. Appendix A: grid for territorial analysis by aspect
List of Authors
Index
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