With topics ranging from improving productivity and coaxing economic growth after periods of market inactivity, Complex Decision-Making in Economy and Finance offers pragmatic solutions for dealing with the critical levels of disorder and chaos that have developed throughout the modern age.
This book examines how to design complex products and systems, the benefits of collective intelligence and self-organization, and the best methods for handling risks in problematic environments. It also analyzes crises and how to manage them. This book is of benefit to companies and public bodies with regards to saving assets, reviving fortunes and laying the groundwork for robust, sustainable societal dividends. Examples, case studies, practical hints and guidelines illustrate the topics, particularly in finance.
Table of Contents
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
