Note to all Contributors xv
Note to the Reader xvii
List of Acronyms xxi
Introduction xxvii
Part 1 Sustainability: Toward the Unification of Some Underlying Principles and Mechanisms 1
Chapter 1 Toward a Sustainability Science 3
1.1 Introduction 3
1.2 What does unification mean? 4
1.3 Coming back to sustainability: how many âsustainabilitiesâ? 7
1.4 Sustainability: what kind of unification? An integration issue? 10
1.5 What kind of paradigm do we have to integrate? 12
1.6 The issue and the implementation of a new dimension 14
1.6.1 Preamble: code of matter, power of laws and balance of powers 14
1.6.2 The addition of a new dimension: gimmick or necessity? 16
1.6.3 Integration of time and dynamics 17
1.6.4 Application 19
1.7 Extensions of the concept 20
1.7.1 Comments 20
1.7.2 Life sciences: power laws, evolution, life and death phenomena 21
1.7.3 The power laws 24
Chapter 2 Sustainability in Complex Systems 29
2.1 Preamble: theories of interconnected systems 29
2.2 Analysis of feedback phenomena in an assembly manufacturing cell 30
2.2.1 Preliminary considerations 30
2.2.2 Case study 1: modeling the limitation of work in progress (WIP) by a threshold called âMAQâ 32
2.2.3 Case study 2: modeling the WIP through assignment rules 33
2.2.4 Case study 3: model building based on dynamic management of bottlenecks 34
2.2.5 Main comments 36
2.3 Application to complex systems: quantitative characteristics of a deterministic chaos 37
2.3.1 Introduction 37
2.3.2 Quantification of state variables in a production system 39
2.4 General considerations about interactions in networked organizations 39
2.5 Role of feedback in mimicry and ascendancy over others 41
2.6 Network theory: additional characteristics due to their new structure 43
2.6.1 Mycorrhization networks 46
2.7 Simplexification 47
2.8 Convergences in network theory 51
Chapter 3 Extension: From Complexity to the Code of Thought 53
3.1 The code of thought: effects of cognition and psyche in global sustainability 53
3.2 Is sustainability the only technological and technocratic approach? 56
3.3 The three laws of sustainability: prediction and anticipation in complex systems 57
3.3.1 Is sustainability a consistent property of any complex system? 58
3.3.2 Sustainability is also the art of combining paradoxes 59
3.3.3 Adaptation of a manufacturing process: what is so important in planning and scheduling? 59
3.3.4 Predicting the future? Is it a necessity? 60
3.4 Consequence: toward a new dimension 63
3.5 Conclusion 64
3.6 Indicators for monitoring the EU sustainable development strategy 65
Part 2 Operationalization: Methods, Techniques and Tools â" the Need to Manage the Impact 69
Chapter 4 From Context to Knowledge: Building Decision-making Systems 71
4.1 Introduction 71
4.1.1 In the back part of the brain, there is the cerebellum 72
4.1.2 In the temporal lobe of the cerebrum and limbic system 73
4.1.3 The frontal lobe of the cerebrum (frontal neocortex) 73
4.2 How about obtaining a sustainable knowledge? 74
4.2.1 The first question: how do we learn from experience? 74
4.2.2 The second question: how do we learn from experiences and develop a conceptual understanding? 75
4.2.3 The third question: how do we model a sustainable information and knowledge processing system? 76
4.3 Preliminary consideration: the nature of the problems encountered in test and diagnosis 77
4.3.1 The world of industry 78
4.3.2 Health and medical care 78
4.3.3 Consequences 80
4.4 Preamble: basic concepts for creating knowledge 80
4.4.1 Description of the basic reasoning techniques 80
4.4.2 Conventional collaborative techniques for creating knowledge 81
4.5 Retroduction and abduction 83
4.5.1 The retroduction technique 84
4.5.2 The abduction technique 86
4.6 Deduction and induction 87
4.6.1 The inductive reasoning technique 88
4.6.2 Linear characteristics and limitations of induction and deduction 89
4.7 The development of a relational reasoning graph 90
4.8 A complete integrated reasoning process 92
4.9 How can a computer analyze different types of reasoning? 94
4.9.1 Theorem proving by semantic techniques 95
4.9.2 Theorem proving by syntactical techniques 95
4.9.3 Theorem proving by grammatical techniques 96
4.10 Applications 96
4.10.1 Building the planning and scheduling involved in an industrial production system 97
4.10.2 Diagnosis or classification in qualitative processes (medical, system testing, etc.) 97
4.10.3 Comments 98
Chapter 5 From Context to Knowledge: Basic Methodology Review 101
5.1 Application of abduction and retroduction to create knowledge 101
5.2 Analysis and synthesis as modeling process 102
5.2.1 Fundamental analytic process 102
5.2.2 Modeling process 103
5.2.3 Abnormal or paranormal analysis and synthesis 106
5.2.4 Application: the main influences due to basic emotions 107
5.2.5 Comment 108
5.3 Background on empirical results: integration principles 109
5.3.1 Cyclical and hierarchical theories about theorizing; Heron and Kolb 109
5.3.2 Complementary advice: how to get good knowledge? 111
5.4 A review and comparison of some common approaches: TRIZ and C-K theory 112
5.4.1 TRIZ is about design problem solving 112
5.4.2 C-K is dealing with design innovation 113
5.4.3 C-K INVENT: toward a methodology for transformational K 114
Chapter 6 From Knowledge to Context and Back: The C-K Theory and Methodology 117
6.1 Introduction 117
6.2 A primer on C-K theory 118
6.3 On the nature of the knowledge space 120
6.4 On the nature of the concept space 120
6.5 Discussing the theory 122
6.6 Some differentiating points and benefits of C-K theory 123
6.7 On fielding C-K theory in organizations 124
6.8 A summary on C-K theory 124
6.9 A short glossary on C-K theory 126
6.10 Links with knowledge management 128
6.11 Example on a specific futuristic conceptual case: âa man who can travel through timeâ 130
6.12 Methodological findings 130
Part 3 Reformulating the Above Into Business Models and Solutions for New Growth and Applications 135
Chapter 7 Principles and Methods for the Design and Development of Sustainable Systems 137
7.1 Introduction 137
7.2 How to go further? 139
7.3 Examples of methods and learning related to complex adaptive systems 140
7.3.1 Why and how to mix different theories? 141
7.3.2 Errors and mistakes not to make 142
7.4 First example: crisis management 143
7.5 Second example: urban organizations 144
7.5.1 A village infrastructure 144
7.5.2 Urban networks 146
7.6 Third example: education and career evolution 148
7.7 A review of survival, resilience and sustainability concepts 149
7.7.1 Definition of resilience 150
7.7.2 Definition of sustainability 151
7.7.3 Definition of reliability 153
7.7.4 Structure and organization of the concepts 154
7.8 Methodologies in sustainability 155
7.8.1 Modeling a sustainable system 156
7.8.2 Evaluation of the sustainability 157
7.8.3 Causes of non-achieving sustainability 158
7.9 Resilience: methodology 162
7.9.1 Problem of attitude change 162
7.9.2 Solving approaches 164
7.9.3 Methods associated with structured scenarios 165
7.9.4 Adaptive management in the Everglades and the Grand Canyon 166
7.9.5 Living together and empathy 167
7.10 Information system sustainability 171
7.10.1 General approach to assess reliability and sustainability in a complex system 171
7.10.2 Favoring a step-by-step approach 172
7.10.3 Comments about sustainability assessment 173
7.11 Application: managing the âskill mismatchâ in a company 177
7.11.1 Assumptions 177
7.11.2 Methodological approach 178
7.11.3 Model development and results 180
7.12 Sustainability of the organizations in a company 181
7.13 Conclusions 183
Chapter 8 Toward the Mass Co-design: Why is Social Innovation so Attractive? 189
8.1 Introduction 189
8.2 How can we define innovation and social innovation? 190
8.2.1 Innovation: main principles 190
8.2.2 Social innovation: an evolution 191
8.3 Sustainability: how can we position social innovation? 193
8.4 Social innovation examples 195
8.4.1 Application 1: research and development of future technologies 195
8.4.2 Application 2: marketing and sales: âI think to youâ 197
8.4.3 Application 3: inclusivity and cognition 200
8.4.4 Consequences 201
8.5 A contextual change in society 203
8.5.1 Networks are everywhere 203
8.5.2 Advantages of the Web approach 203
8.6 Basic concepts and mechanisms 205
8.6.1 The social concept of a process: principle of emergence 206
8.6.2 The social innovation process mechanism 207
8.6.3 Social innovation: conditions for sustainable implementation 209
8.7 The principle of circularity: a paradigm shift 211
8.8 Generalization: how to turn back time 212
8.9 Problems of technological evolution 214
8.9.1 In nature, evolution is consistent with Mooreâs law 214
8.9.2 The limits of new technologies and sciences 215
8.9.3 Application in industry: where are we going? 216
8.10 Evolution: application to cellular networks 218
8.10.1 Extended environments 218
8.10.2 Social networking 219
8.11 Conclusions: the new sustainable environment 220
8.11.1 Generalities 220
8.11.2 Global process engineering 221
8.11.3 Intelligence economy 222
Chapter 9 On Integrating Innovation and CSR when Developing Sustainable Systems 225
9.1 The new Smartphones: a tool for an inclusive society 225
9.2 Innovation and corporate social responsibility (CSR) behaviors 228
9.3 Integrating business objectives (CBO) and corporate social responsibility (SCR) 230
9.3.1 Implementation comments 230
9.4 Lessons gained from this study case: toward a citizen democracy 234
9.5 Conclusion on crowd and social approaches 238
Part 4 Reformulating Future Thinking: Processes and Applications 239
Chapter 10 Sustainability Engineering and Holism: Thinking Conditions are a Must 241
10.1 Introduction to holism 241
10.1.1 What do we mean by holism? 242
10.1.2 Application to decision and management systems 243
10.2 Toward a holistic company 244
10.3 Culture: on what positive factors can we rely? 246
10.4 Sustainability: a framework 249
10.5 Application: holonic industrial systems 250
10.5.1 Definitions 250
10.5.2 The design of a holonic manufacturing system (HMS) 251
10.5.3 Holism: a contribution to a better sustainability 253
10.6 Consequences 254
Chapter 11 Sustainable Cognitive Engineering: Brain Modeling; Evolution of a Knowledge Base 257
11.1 Introduction 257
11.2 Sustainable cognition: definition and concepts 258
11.3 Concepts and âslippageâ needs: effects related to new generations 260
11.4 Basic structure of our brain: a probabilistic approach 261
11.4.1 Application to a human population: macro behavior and conditional probabilities 262
11.4.2 Bayes theorem: a universal statistical concept 264
2.4.3 Impact of the Bayes theorem on information system sustainability and decision theory 265
11.5 Application and probabilistic reasoning in updating a knowledge base: a more sustainable model 266
11.5.1 Two applications 266
11.5.2 Complex reasoning: a question of plausibility and probabilistic estimates 269
11.6 Sustainable cognition: brain structure, understanding micro-to-macro links 271
11.7 More recent developments 271
11.8 Detection of novelties through adaptive learning and fractal chaos approaches 274
11.9 Neuro computing: new opportunities provided by quantum physics 277
11.10 Applications 279
11.11 Quantum physics: impact on future organizations 280
Chapter 12 Brain and Cognitive Computing: Where Are We Headed? 283
12.1 State of the art 283
12.2 Achievements: is neuroscience able to explain how to perform sustained assumptions and studies? 284
12.3 Artificial brain: evolution of the simulation models 289
12.4 Examples of challenges to be well controlled 290
Part 5 Towards an Approach to the Measurement of Sustainability and Competitivity 293
Chapter 13 On Measuring Sustainability 295
13.1 Introduction 295
13.2 Some basic criteria specific to the new âSustainableâ era 296
13.3 What are the nature and limits of the new paradigm, in terms of sustainability evolution? 297
13.4 A reminder about competitivity and sustainability properties 299
13.5 Synthesis: the present dimensions of a production system 302
13.6 An under-assessed value: time 305
13.7 Application and results 307
13.7.1 Time is the source of streams and flows 307
13.7.2 Time and power: some considerations about streams and throughputs 308
13.7.3 Measurement of sustainability in a chaotic system: Lyapunov experiments 310
13.7.4 Consequences at governance level to get a sustainable system 312
13.8 Two new dimensions: thought and information within network theory 313
13.8.1 From storytelling⦠314
13.8.2 ⦠to âtalking bullshitâ 315
13.8.3 An improved understanding of a âNew Worldâ complexity 315
13.9 Synthesis: cognitive advances provided by the new exchange and communication tools 316
13.9.1 The cognitive behaviors associated with this classification 317
13.9.2 Synthesizing the cognitive advances 319
13.10 Consequences and characteristics linked to a global network notion 321
13.10.1 Generalizing the knowledge at organization level 321
13.10.2 The behaviors associated with human beingsâ psychological features 322
13.11 Back to the code of matter: contributions to âSimultaneous Timeâ and âNetwork Theoryâ 323
13.12 Application of quantum interactions 326
13.13 Sustainability: how to widen the scope of competitiveness indicators? 328
13.14 Conclusion 330
13.15 Social interactions and massively multiplayer online role playing games 330
General Conclusion 333
Bibliography 355
Index 375
