Table of Contents -- Title -- Copyright -- Note to all Contributors -- Note to the Reader -- List of Acronyms -- Introduction -- PART 1: Sustainability: Toward the Unification of Some Underlying Principles and Mechanisms -- 1: Toward a Sustainability Science -- 1.1. Introduction -- 1.2. What does unification mean? -- 1.3. Coming back to sustainability: how many "sustainabilities"? -- 1.4. Sustainability: what kind of unification? An integration issue? -- 1.5. What kind of paradigm do we have to integrate? -- 1.6. The issue and the implementation of a new dimension -- 1.7. Extensions of the concept -- 2: Sustainability in Complex Systems -- 2.1. Preamble: theories of interconnected systems -- 2.2. Analysis of feedback phenomena in an assembly manufacturing cell -- 2.3. Application to complex systems: quantitative characteristics of a deterministic chaos -- 2.4. General considerations about interactions in networked organizations -- 2.5. Role of feedback in mimicry and ascendancy over others -- 2.6. Network theory: additional characteristics due to their new structure -- 2.7. Simplexification -- 2.8. Convergences in network theory -- 3: Extension: From Complexity to the Code of Thought -- 3.1. The code of thought: effects of cognition and psyche in global sustainability -- 3.2. Is sustainability the only technological and technocratic approach? -- 3.3. The three laws of sustainability: prediction and anticipation in complex systems -- 3.4. Consequence: toward a new dimension -- 3.5. Conclusion -- 3.6. Indicators for monitoring the EU sustainable development strategy -- PART 2: Operationalization: Methods, Techniques and Tools - the Need to Manage the Impact -- 4: From Context to Knowledge: Building Decision-making Systems -- 4.1. Introduction -- 4.2. How about obtaining a sustainable knowledge?.

4.3. Preliminary consideration: the nature of the problems encountered in test and diagnosis -- 4.4. Preamble: basic concepts for creating knowledge -- 4.5. Retroduction and abduction -- 4.6. Deduction and induction -- 4.7. The development of a relational reasoning graph -- 4.8. A complete integrated reasoning process -- 4.9. How can a computer analyze different types of reasoning? -- 4.10. Applications -- 5: From Context to Knowledge: Basic Methodology Review -- 5.1. Application of abduction and retroduction to create knowledge -- 5.2. Analysis and synthesis as modeling process -- 5.3. Background on empirical results: integration principles -- 5.4. A review and comparison of some common approaches: TRIZ and C-K theory -- 6: From Knowledge to Context and Back: The C-K Theory and Methodology -- 6.1. Introduction -- 6.2. A primer on C-K theory -- 6.3. On the nature of the knowledge space -- 6.4. On the nature of the concept space -- 6.5. Discussing the theory -- 6.6. Some differentiating points and benefits of C-K theory -- 6.7. On fielding C-K theory in organizations -- 6.8. A summary on C-K theory -- 6.9. A short glossary on C-K theory -- 6.10. Links with knowledge management -- 6.11. Example on a specific futuristic conceptual case: "a man who can travel through time" -- 6.12. Methodological findings -- PART 3: Reformulating the Above Into Business Models and Solutions for New Growth and Applications -- 7: Principles and Methods for the Design and Development of Sustainable Systems -- 7.1. Introduction -- 7.2. How to go further? -- 7.3. Examples of methods and learning related to complex adaptive systems -- 7.4. First example: crisis management -- 7.5. Second example: urban organizations -- 7.6. Third example: education and career evolution -- 7.7. A review of survival, resilience and sustainability concepts -- 7.8. Methodologies in sustainability.

7.9. Resilience: methodology -- 7.10. Information system sustainability -- 7.11. Application: managing the "skill mismatch" in a company -- 7.12. Sustainability of the organizations in a company -- 7.13. Conclusions -- 8: Toward the Mass Co-design: Why is Social Innovation so Attractive? -- 8.1. Introduction -- 8.2. How can we define innovation and social innovation? -- 8.3. Sustainability: how can we position social innovation? -- 8.4. Social innovation examples -- 8.5. A contextual change in society -- 8.6. Basic concepts and mechanisms -- 8.7. The principle of circularity: a paradigm shift -- 8.8. Generalization: how to turn back time -- 8.9. Problems of technological evolution -- 8.10. Evolution: application to cellular networks -- 8.11. Conclusions: the new sustainable environment -- 9: On Integrating Innovation and CSR when Developing Sustainable Systems -- 9.1. The new Smartphones: a tool for an inclusive society -- 9.2. Innovation and corporate social responsibility (CSR) behaviors -- 9.3. Integrating business objectives (CBO) and corporate social responsibility (SCR) -- 9.4. Lessons gained from this study case: toward a citizen democracy -- 9.5. Conclusion on crowd and social approaches -- PART 4: Reformulating Future Thinking: Processes and Applications -- 10: Sustainability Engineering and Holism: Thinking Conditions are a Must -- 10.1. Introduction to holism -- 10.2. Toward a holistic company -- 10.3. Culture: on what positive factors can we rely? -- 10.4. Sustainability: a framework -- 10.5. Application: holonic industrial systems -- 10.6. Consequences -- 11: Sustainable Cognitive Engineering: Brain Modeling -- Evolution of a Knowledge Base -- 11.1. Introduction -- 11.2. Sustainable cognition: definition and concepts -- 11.3. Concepts and "slippage" needs: effects related to new generations.

11.4. Basic structure of our brain: a probabilistic approach -- 11.5. Application and probabilistic reasoning in updating a knowledge base: a more sustainable model -- 11.6. Sustainable cognition: brain structure, understanding micro-to-macro links -- 11.7. More recent developments -- 11.8. Detection of novelties through adaptive learning and fractal chaos approaches -- 11.9. Neuro computing: new opportunities provided by quantum physics -- 11.10. Applications -- 11.11. Quantum physics: impact on future organizations -- 12: Brain and Cognitive Computing: Where Are We Headed? -- 12.1. State of the art -- 12.2. Achievements: is neuroscience able to explain how to perform sustained assumptions and studies? -- 12.3. Artificial brain: evolution of the simulation models -- 12.4. Examples of challenges to be well controlled -- PART 5: Towards an Approach to the Measurement of Sustainability and Competitivity -- 13: On Measuring Sustainability -- 13.1. Introduction -- 13.2. Some basic criteria specific to the new "Sustainable" era -- 13.3. What are the nature and limits of the new paradigm, in terms of sustainability evolution? -- 13.4. A reminder about competitivity and sustainability properties -- 13.5. Synthesis: the present dimensions of a production system -- 13.6. An under-assessed value: time -- 13.7. Application and results -- 13.8. Two new dimensions: thought and information within network theory -- 13.9. Synthesis: cognitive advances provided by the new exchange and communication tools -- 13.10. Consequences and characteristics linked to a global network notion -- 13.11. Back to the code of matter: contributions to "Simultaneous Time" and "Network Theory" -- 13.12. Application of quantum interactions -- 13.13. Sustainability: how to widen the scope of competitiveness indicators? -- 13.14. Conclusion.

13.15. Social interactions and massively multiplayer online role playing games -- General Conclusion - Where Are We Now? -- Bibliography -- Index -- End User License Agreement.