Complex Decision-Making in Economy and Finance

Pierre Massotte is the I2D (Institut de l�Innovation et du Développement) Chairman. He was Deputy Director at École des Mines d�Alès within the Nîmes EMA Laboratory, France. He has previously worked for IBM in Quality, Advanced Technologies and Machine Learning. Formerly, he was also the AI Scientific Director at IBM EMEA Manufacturing and Development. Patrick Corsi is a Senior Consultant, an Associate Practitioner with Mines Paris Tech, France, and a member of the Club of Rome EU Chapter. He was for a long time with IBM, THOMSON-CSF, a start-up in AI, and the European Commission in Brussels.

Introduction xiii

Part 1. Dealing with Complexity 1

Chapter 1. Engineering Complexity within Present-Day Industrial Systems 3

1.1. Introduction 3

1.1.1. Reference definitions 3

1.1.2. What are the problems to be solved? 5

1.1.3. What is the “engineering” approach developed here? 7

1.2. Basic properties of complex industrial systems 7

1.2.1. Structure and organization of system functions 8

1.3. The complexity of systems 9

1.3.1. The basic principles of complexification 9

1.3.2. The complexification process 10

1.3.3. The smoothing property of chaotic characteristics 11

1.4. Analysis of some industrial dynamic systems 13

1.4.1. Introduction 13

1.4.2. Interactions in industrial workshops 14

1.4.3. Product flow in a flexible production system 16

1.4.4. Message flows in complex information systems 18

1.5. Applications of new concepts in industrial systems 20

1.5.1. New features and functionalities to consider 20

1.5.2. Design of complex industrial systems management tools 21

1.5.3. The contribution of chaos and self-organization 22

1.5.4. Consequences 24

Chapter 2. Designing Complex Products and Services 27

2.1. Complex systems engineering: the basics 27

2.1.1. Relationship between organization and product: basic principles 27

2.1.2. Reminder of the operating rules of an organization 28

2.1.3. The challenges of such organizations 30

2.1.4. Concepts of sociability and emergence of order 32

2.1.5. The genesis and evolution of complex systems 34

2.1.6. How and where do structures emerge? 36

2.2. The implementation conditions for self-organization 38

2.2.1. Emergence of self-organized patterns 39

2.2.2. Best stability conditions: homeostasis 40

2.3. Advantages and benefits of a complexity approach 41

Chapter 3. Engineering and Complexity Theory: A Field Design Approach 43

3.1. Design approach for a complex system 43

3.1.1. Methodological elements for the design of a complex system 43

3.1.2. Example: how can we propose a “customized product”? 45

3.2. Applications and solutions 46

3.2.1. Case 1: current approaches based on “design on demand” 46

3.2.2. Case 2: “design by assembly according to demand” approach 47

3.2.3. Case 3: product reconfiguration and on-demand adaptation 50

3.2.4. Case 4: product auto-configuration and adaptation for use 53

3.2.5. Case 5: designing self-propagating computers 55

3.3. Application: organization and management in companies 56

3.4. Main conclusions related to the first three chapters 57

Chapter 4. Organizational Constraints and Complexity Theory: Modeling with Agents 61

4.1. A preamble to modeling 61

4.2. Introducing collective intelligence 62

4.3. Studying the agent concept 63

4.3.1. Some definitions of an agent 64

4.3.2. The different categories and models of agents available 65

4.4. Applications using agents 69

4.4.1. Modeling the behavior of a living organism 69

4.4.2. Modeling of an industrial management and control system 71

4.5. Conclusion: information related to the use and usage of modeling 71

4.5.1. Free Trade considerations 71

4.5.2. Harmonization of situations and objectives 72

4.5.3. Emergence of the ecology and “patriotism” 72

4.5.4. Comments and expectations on modeling expectations 73

Chapter 5. Complexity and the Theory of Organizations: Implementation of Collective Intelligence 75

5.1. Introducing the notion of collective intelligence 75

5.2. Definition of a multi-agent system 76

5.2.1. Introduction 76

5.2.2. What’s in a multi-agent system? 77

5.2.3. MAS areas of application 78

5.2.4. Negotiation protocols between agents 79

5.3. Behavioral and interaction strategies between agents 86

5.3.1. Applying the above principles 86

5.3.2. Application example: workshop reconfiguration 89

5.3.3. Influence of the individual characteristics of agents on the decision process 89

5.4. Concluding comments 95

Chapter 6. Complexity and the Theory of Organizations: The Notion of Collective Patterns 97

6.1. The emergence of collective patterns 98

6.1.1. Conditions and method of emergence of patterns 98

6.2. System complexity factors and their measurement 102

6.3. Conclusion: towards the notion of “complex adaptive systems” (CAS) 104

Chapter 7. Complexity and Theory of Organizations: Structure and Architecture of an Enterprise 107

7.1. Notions of structure in organizations 107

7.1.1. The “enabling” environment for Information and Decision Systems 107

7.1.2. The structural environment 108

7.1.3. The company and the global context 109

7.2. Structure of distributed complex systems 111

7.2.1. Introduction 111

7.2.2. The centralized structure 113

7.2.3. The non-centralized structure; the hierarchical structure 114

7.2.4. The heterarchical non-centralized structure 116

7.2.5. The n-cube structure 117

7.3. Conclusion 118

Chapter 8. Complexity and the Theory of Organizations: Applications 119

8.1. Applications: trends and models 119

8.1.1. Application of the principles to steering systems 119

8.2. Application and implementation of concepts in the “Fractal Factory” 125

8.2.1. The case of the Fractal Factory – organization 125

8.2.2. Consequences for production management 126

Chapter 9. Complexity and the Theory of Organizations: Complex Systems Reengineering 129

9.1. The reengineering of complex systems 129

9.1.1. Introduction 129

9.1.2. The approach and the initial conditions 131

9.1.3. The RECOS reengineering methodology 134

9.2. Comments on the technologies used 136

9.2.1. Modeling techniques and tools 136

9.2.2. Role and contribution of IT in BPR 138

9.3. Theory of constraints and complexity management 140

9.4. Measurement of the complexity of a new organization. 141

9.5. Concluding remark 143

Chapter 10. Evaluating and Measuring Complexity: The CINSYS Methodology 145

10.1. A brief overview of the CINSYS system 145

10.2. What can be found in a CINSYS model? 147

10.3. Functional analysis of the method: interpretation by the CINSYS symbolic and structural diagram 148

10.3.1. The vertical axis is the axis of the “structure” 149

10.3.2. The horizontal axis is the axis of “explanations” 152

10.3.3. The ascending bisector axis 153

10.3.4. The “descriptive inversion” axis 155

10.4. Illustration of the method 156

10.4.1. Evaluating project proposals 156

10.4.2. The RAGTIME proposal 157

10.4.3. The BOLERO proposal 158

10.5. What are the advantages of using the method? 158

10.6. “The network metaphor” as the general application context of the method 159

10.7. Perspectives beyond the CINSYS method 160

10.7.1. A generic methodology for dealing with complex problems 161

10.7.2. Analysis of how, or design of new systems 162

10.7.3. Systems development: organization 163

10.8. Conclusion 163

Part 2. Dealing with Risk in Complex Environments 165

Chapter 11. Underlying Mechanisms in Finance 167

11.1. Introduction to finance theory and its evolution 167

11.2. What are the best candidates for the so-called econophysics? 168

11.3. Action plans in financial regulation and bank regulation: are they ok? 169

11.4. Back to physics and matter: their contribution 170

11.5. From matter up to living beings: how can big events be generated? 172

11.6. The evolution of an economic system – the problem of CRISIS 176

11.6.1. Pre-industrial crises 177

11.6.2. Industrial crises 177

11.7. Role of complexity and diversity in Nature 178

11.8. Application: how should we proceed when faced with crises and financial crashes/crises? 180

11.8.1. Definition of a crisis and frequencies of occurrence 180

11.8.2. Future possible crisis 182

11.9. Crisis as the end of an evolution 182

11.10. Collapse theory and modeling – a theory of the “end” 186

11.10.1. Modeling the collapse 187

11.10.2. Application 188

11.10.3. Comments 190

11.11. Design of financial products: the example of world interconnections 190

11.12. Conclusion 192

Chapter 12. Physics and Social Networks: Domain Similarities 195

12.1. Introducing a similarity of domains 195

12.1.1. Problems of complexity and connectivity 196

12.2. On the principle of emergence 198

12.3. Finance, economics and physics: the quantification of emergence 200

12.3.1. Emergence and complexity 200

12.3.2. Complexity as a quality – self-organization and emergence 201

12.3.3. Emergence and thermodynamics: a general view 201

12.3.4. A few applications 202

12.4. About Gödel theorems 204

12.5. Conclusion 205

Chapter 13. Managing Behavioral Risks: Uncertainty and Catastrophes 209

13.1. Introduction 209

13.1.1. Uncertainty is not disorder 210

13.1.2. The different realities 211

13.1.3. World time 213

13.2. Implications for intellectual approaches 216

13.3. The uncertainties 217

13.3.1. Social acceptability 218

13.3.2. From ordinary risk… 220

13.3.3. …To major risk 221

13.3.4. Risk management 223

Chapter 14. On Managing Risk in the Energy Domain: Conventional Problems Encountered 225

14.1. From a new oil crisis (peak oil) and the resulting energy crisis 225

14.1.1. At present, what do we mean by energy crisis? 226

14.1.2. Energy crisis: impacts on prices and the economy 228

14.1.3. Biofuels: how can we prepare for and manage the shortage? 229

14.1.4. What about raw materials and resulting products? 230

14.2. The future: limit of price increases? Implications of the shortage 232

14.3. Modeling the problem correctly 234

14.4. Crisis or heuristic tactics? Large-scale oil shock? 238

14.5. A few conclusive remarks 239

Chapter 15. On Managing Risk in the Financial Domain 241

15.1. Taking about disasters – from risks to catastrophes in finance 241

15.2. An interesting approach: financial analysis of losses 242

15.3. When the drama occurs 243

15.4. How to conduct a risk consequence analysis process? 244

15.5. Conservatory measures: risk and diversification 247

15.6. An additional risk: the decline and inversion rate at the stock exchange 248

15.7. Concluding with additional risks of the shared economy 249

Chapter 16. Why Current Tools are Inadequate 251

16.1. On the shortcomings of current tools: risk and probability 251

16.2. A thematic illustration 252

16.3. What regularities? 254

16.4. Characteristics of rational expectations in economics 255

16.5. Risk characteristics in the industry 256

16.6. A philosophical summary: chance and necessity 258

16.7. The environment’s new challenge 262

Chapter 17. How to Manage Crises? 265

17.1. The fundamental principles of crisis management 265

17.2. Early warning risk signals and the basics of risk management 267

17.2.1. Several families of crises 268

17.2.2. Mechanisms and crisis preparation 269

17.2.3. Detecting early warning signals and containing damage 271

17.3. Five fundamental elements that describe a company 272

17.4. About stakeholders 273

Chapter 18. Managing Crises in Finance and Other Domains 275

18.1. Reorienting company aims 275

18.1.1. The growing importance of the shareholder 276

18.1.2. The specialization of companies in the new economy 276

18.1.3. The advantages and consequences of this evolution 277

18.1.4. Cultivating diversity 279

18.2. Interactions: towards a crisis model? 279

18.2.1. Effects of the crisis of confidence 280

18.2.2. Banks’ subprime exposure 280

18.2.3. Subprime effects within banks and the stock exchange 281

18.2.4. Subprime effects, at the level of individuals 281

18.2.5. Subprime effects, at bank level 281

18.2.6. Effects of changes in securities 282

Chapter 19. Technological, Monetary and Financial Crashes 283

19.1. Yet another view to complexity 283

19.1.1. Global complexity of economy 285

19.2. The reference financial systems are continuously changing 289

19.2.1. The US Dollar and Chinese Yuan 289

19.2.2. Lifetime of a currency. Importance of gold? 291

19.2.3. Distribution of GDP around the world 292

19.2.4. In terms of economical and overtime evolution 292

19.3. Conclusive discussion 294

19.3.1. Problem of gold and rare earth materials 294

19.3.2. Summary and main conclusions 295

19.3.3. T-bonds versus Eurobonds and Chinese bonds, etc. 297

19.3.4. Application and comments 297

Conclusion 299

List of Abbreviations 305

References 313

Index 327