Оглавление
Pierre Massotte. Complex Decision-Making in Economy and Finance
Table of Contents
List of Tables
List of Illustrations
Guide
Pages
Complex Decision-Making in Economy and Finance
Introduction: New Beginnings. I.1. A present-day situation
I.2. A basic awareness: the governance of a system
I.3. What lies ahead of us?
I.3.1. Factors that cause complexity
I.3.2. What is missing or penalizing us today
I.4. Guidelines and ways forward. I.4.1. Strategic risk management
I.4.2. The role of intelligence
I.4.3. The role of public institutions
I.4.4. Structure of the book
1. Engineering Complexity within Present-Day Industrial Systems. 1.1. Introduction
1.1.1. Reference definitions
1.1.2. What are the problems to be solved?
1.1.3. What is the “engineering” approach developed here?
1.2. Basic properties of complex industrial systems
1.2.1. Structure and organization of system functions
1.2.1.1. Importance of interactions in social behavior
1.2.1.2. Interconnections
1.3. The complexity of systems
1.3.1. The basic principles of complexification
1.3.2. The complexification process
1.3.3. The smoothing property of chaotic characteristics
1.4. Analysis of some industrial dynamic systems. 1.4.1. Introduction
1.4.2. Interactions in industrial workshops
1.4.3. Product flow in a flexible production system
1.4.4. Message flows in complex information systems. 1.4.4.1. Distributed information processing
1.4.4.2. Emergence of collaborative work
1.5. Applications of new concepts in industrial systems. 1.5.1. New features and functionalities to consider
1.5.2. Design of complex industrial systems management tools
1.5.3. The contribution of chaos and self-organization
1.5.4. Consequences
2. Designing Complex Products and Services. 2.1. Complex systems engineering: the basics. 2.1.1. Relationship between organization and product: basic principles
2.1.2. Reminder of the operating rules of an organization
2.1.2.1. Zero delay
2.1.2.2. Zero cost
2.1.2.3. Zero crack criterion
2.1.2.4. Zero friction criterion
2.1.3. The challenges of such organizations
2.1.3.1. Dynamic stability and transversal culture
2.1.3.2. Dynamic stability and quality
2.1.3.3. Dynamic stability and time
2.1.4. Concepts of sociability and emergence of order
2.1.5. The genesis and evolution of complex systems
2.1.6. How and where do structures emerge?
2.2. The implementation conditions for self-organization
2.2.1. Emergence of self-organized patterns
2.2.2. Best stability conditions: homeostasis
2.3. Advantages and benefits of a complexity approach
3. Engineering and Complexity Theory: A Field Design Approach
3.1. Design approach for a complex system
3.1.1. Methodological elements for the design of a complex system
3.1.2. Example: how can we propose a “customized product”?
3.2. Applications and solutions
3.2.1. Case 1: current approaches based on “design on demand”
3.2.2. Case 2: “design by assembly according to demand” approach
3.2.2.1. Classifications
3.2.2.2. Technical changes
3.2.2.3. Consequence: decoupling and process division
3.2.3. Case 3: product reconfiguration and on-demand adaptation
3.2.3.1. Circuit redundancy
3.2.3.2. Mass customization of computers
3.2.3.3. The design of reconfigurable computers
3.2.4. Case 4: product auto-configuration and adaptation for use. Prerequisites
3.2.5. Case 5: designing self-propagating computers
3.3. Application: organization and management in companies
3.4. Main conclusions related to the first three chapters
4. Organizational Constraints and Complexity Theory: Modeling with Agents
4.1. A preamble to modeling
4.2. Introducing collective intelligence
4.3. Studying the agent concept
4.3.1. Some definitions of an agent
4.3.2. The different categories and models of agents available
4.3.2.1. Cognitive agents
4.3.2.2. Reactive agents
4.3.2.3. Summary and comments
4.3.2.4. Hybrid agents
4.4. Applications using agents
4.4.1. Modeling the behavior of a living organism
4.4.2. Modeling of an industrial management and control system
4.5. Conclusion: information related to the use and usage of modeling
4.5.1. Free Trade considerations
4.5.2. Harmonization of situations and objectives
4.5.3. Emergence of the ecology and “patriotism”
4.5.4. Comments and expectations on modeling expectations
5. Complexity and the Theory of Organizations: Implementation of Collective Intelligence
5.1. Introducing the notion of collective intelligence
5.2. Definition of a multi-agent system. 5.2.1. Introduction
5.2.2. What’s in a multi-agent system?
5.2.3. MAS areas of application
5.2.4. Negotiation protocols between agents
5.2.4.1. Auction-based protocols
What are the compared benefits?
Consequences
5.2.4.2. Mediation-based protocols
5.2.4.3. Protocol based on arguments and dialogue games
5.2.4.4. Protocol based on strategy determination
Case-based reasoning
Adaptive learning/evolutionary approach
Game theory
5.3. Behavioral and interaction strategies between agents
5.3.1. Applying the above principles
5.3.2. Application example: workshop reconfiguration
5.3.3. Influence of the individual characteristics of agents on the decision process
5.3.3.1. Study of individual and affective behaviors in a population
1 – Honesty and trickery
2 – Management of the emotions, stress, and sleep
3 – Individualism (selfishness) and altruism, empathy, and withdrawing
5.3.3.2. Study of the impacts and structuring effects in communities of agents
5.4. Concluding comments
6. Complexity and the Theory of Organizations: The Notion of Collective Patterns
6.1. The emergence of collective patterns
6.1.1. Conditions and method of emergence of patterns
6.1.1.1. Which steps in the pattern emergence process?
6.1.1.2. The sought purposes
6.1.1.2.1. Protection against risks
6.1.1.2.2. Competitive aggressiveness
6.1.1.2.3. Recruitment and growth phenomena
6.1.1.2.4. Occupation of new territories and market shares
6.1.1.2.5. Optimization of innovative and reproductive capacities
6.1.1.2.6. Survival in a competitive and hostile environment
6.1.1.2.7. Stabilization of a population
6.1.1.2.8. Environmental control
6.2. System complexity factors and their measurement
6.3. Conclusion: towards the notion of “complex adaptive systems” (CAS)
Examples of typical CAS applications
1 – The QUETA project1
2 – The PABADIS project2
3 – Virtual production system modeling
4 – The Internet of Things and collaborative warehousing
5 – Deshmukh work
7. Complexity and Theory of Organizations: Structure and Architecture of an Enterprise
7.1. Notions of structure in organizations. 7.1.1. The “enabling” environment for Information and Decision Systems
7.1.2. The structural environment
7.1.3. The company and the global context
7.2. Structure of distributed complex systems. 7.2.1. Introduction
7.2.2. The centralized structure
Advantages and disadvantages
7.2.3. The non-centralized structure; the hierarchical structure
Characteristics of hierarchical models
An evolution: the “modified” hierarchical models
Advantages and disadvantages of hierarchical models
7.2.4. The heterarchical non-centralized structure
7.2.5. The n-cube structure
7.3. Conclusion
8. Complexity and the Theory of Organizations: Applications
8.1. Applications: trends and models. 8.1.1. Application of the principles to steering systems
8.1.1.1. Flexible and reconfigurable workshops
Advantages and disadvantages
8.1.1.2. Hybrid steering structures
Advantages and disadvantages
8.1.1.3. Discussion
8.2. Application and implementation of concepts in the “Fractal Factory” 8.2.1. The case of the Fractal Factory – organization
8.2.2. Consequences for production management
Discussion
9. Complexity and the Theory of Organizations: Complex Systems Reengineering
9.1. The reengineering of complex systems
9.1.1. Introduction
9.1.2. The approach and the initial conditions
9.1.3. The RECOS reengineering methodology
9.2. Comments on the technologies used. 9.2.1. Modeling techniques and tools
At the initiation of the study stage
At the exploration stage
For modeling and simulations
9.2.2. Role and contribution of IT in BPR
9.3. Theory of constraints and complexity management
Box 9.1.Implementation of some rules from the theory of constraints
9.4. Measurement of the complexity of a new organization
9.5. Concluding remark
10. Evaluating and Measuring Complexity: The CINSYS Methodology
10.1. A brief overview of the CINSYS system
10.2. What can be found in a CINSYS model?
10.3. Functional analysis of the method: interpretation by the CINSYS symbolic and structural diagram
10.3.1. The vertical axis is the axis of the “structure”
10.3.2. The horizontal axis is the axis of “explanations”
10.3.3. The ascending bisector axis
10.3.4. The “descriptive inversion” axis
10.4. Illustration of the method
10.4.1. Evaluating project proposals
10.4.2. The RAGTIME proposal
10.4.3. The BOLERO proposal
10.5. What are the advantages of using the method?
10.6. “The network metaphor” as the general application context of the method
10.7. Perspectives beyond the CINSYS method
10.7.1. A generic methodology for dealing with complex problems
10.7.2. Analysis of how, or design of new systems
10.7.3. Systems development: organization
10.8. Conclusion
11. Underlying Mechanisms in Finance. 11.1. Introduction to finance theory and its evolution
11.2. What are the best candidates for the so-called econophysics?
11.3. Action plans in financial regulation and bank regulation: are they ok?
11.4. Back to physics and matter: their contribution
11.5. From matter up to living beings: how can big events be generated?
Carbon
Benzonitrile
Polycyclic aromatic hydrocarbons
Fullerenes
Cosmic dust
11.6. The evolution of an economic system – the problem of CRISIS
11.6.1. Pre-industrial crises
11.6.2. Industrial crises
11.7. Role of complexity and diversity in Nature
Diversity
Sensitivity to Initial Conditions (SIC)
Global control
Management: evolution of practices and the environmental assumptions
11.8. Application: how should we proceed when faced with crises and financial crashes/crises?
11.8.1. Definition of a crisis and frequencies of occurrence
11.8.2. Future possible crisis
11.9. Crisis as the end of an evolution
11.10. Collapse theory and modeling – a theory of the “end”
11.10.1. Modeling the collapse
11.10.2. Application
11.10.3. Comments
11.11. Design of financial products: the example of world interconnections
11.12. Conclusion
12. Physics and Social Networks: Domain Similarities. 12.1. Introducing a similarity of domains
12.1.1. Problems of complexity and connectivity
12.2. On the principle of emergence
12.3. Finance, economics and physics: the quantification of emergence. 12.3.1. Emergence and complexity
12.3.2. Complexity as a quality – self-organization and emergence
12.3.3. Emergence and thermodynamics: a general view
12.3.4. A few applications
First example: the ideal gas. Box 12.1.Extract from Standish’s “On complexity and emergence” paper [STA 01]
Second example: the Game of Life
12.4. About Gödel theorems
12.5. Conclusion
13. Managing Behavioral Risks: Uncertainty and Catastrophes
13.1. Introduction
13.1.1. Uncertainty is not disorder
13.1.2. The different realities
13.1.3. World time
Box 13.1.Translated excerpt from Le défi énergétique. Publisher’s presentation on the cost of raw materials and the associated risks of shortages [LAR 06]
Box 13.2.An example of a warning on the energy crisis and the associated discussions
13.2. Implications for intellectual approaches
13.3. The uncertainties
13.3.1. Social acceptability
13.3.2. From ordinary risk…
13.3.3. …To major risk
13.3.4. Risk management
14. On Managing Risk in the Energy Domain: Conventional Problems Encountered
14.1. From a new oil crisis (peak oil) and the resulting energy crisis
14.1.1. At present, what do we mean by energy crisis?
14.1.2. Energy crisis: impacts on prices and the economy
14.1.3. Biofuels: how can we prepare for and manage the shortage?
14.1.4. What about raw materials and resulting products?
14.2. The future: limit of price increases? Implications of the shortage
14.3. Modeling the problem correctly
14.4. Crisis or heuristic tactics? Large-scale oil shock?
14.5. A few conclusive remarks
15. On Managing Risk in the Financial Domain
15.1. Taking about disasters – from risks to catastrophes in finance
15.2. An interesting approach: financial analysis of losses
15.3. When the drama occurs
15.4. How to conduct a risk consequence analysis process?
Box 15.1.Analysis of the consequences of risks by their impact in 10 points
15.5. Conservatory measures: risk and diversification
15.6. An additional risk: the decline and inversion rate at the stock exchange
15.7. Concluding with additional risks of the shared economy
16. Why Current Tools Are Inadequate
16.1. On the shortcomings of current tools: risk and probability
16.2. A thematic illustration
Box 16.1.Analogy case 1: stellar interdependence in astrophysics: stellar collisions
Box 16.2.Analogy case 2: stellar interdependence in astrophysics: galactic collisions
16.3. What regularities?
16.4. Characteristics of rational expectations in economics
16.5. Risk characteristics in the industry
16.6. A philosophical summary: chance and necessity
16.7. The environment’s new challenge
17. How to Manage Crises?
17.1. The fundamental principles of crisis management
17.2. Early warning risk signals and the basics of risk management
17.2.1. Several families of crises
17.2.2. Mechanisms and crisis preparation
17.2.3. Detecting early warning signals and containing damage
17.3. Five fundamental elements that describe a company
17.4. About stakeholders
18. Managing Crises in Finance and Other Domains
18.1. Reorienting company aims
18.1.1. The growing importance of the shareholder
18.1.2. The specialization of companies in the new economy
18.1.3. The advantages and consequences of this evolution
18.1.4. Cultivating diversity
18.2. Interactions: towards a crisis model?
18.2.1. Effects of the crisis of confidence
18.2.2. Banks’ subprime exposure
18.2.3. Subprime effects within banks and the stock exchange
18.2.4. Subprime effects, at the level of individuals
18.2.5. Subprime effects, at bank level
18.2.6. Effects of changes in securities
19. Technological, Monetary and Financial Crashes. 19.1. Yet another view to complexity
19.1.1. Global complexity of economy
19.2. The reference financial systems are continuously changing. 19.2.1. The US Dollar and Chinese Yuan
19.2.2. Lifetime of a currency. Importance of gold?
19.2.3. Distribution of GDP around the world
19.2.4. In terms of economical and overtime evolution
19.3. Conclusive discussion
19.3.1. Problem of gold and rare earth materials
19.3.2. Summary and main conclusions
19.3.3. T-bonds versus Eurobonds and Chinese bonds, etc
19.3.4. Application and comments
Conclusion: Different Types of Crises. C.1. The crises mesh
C.1.1. Crisis of currency
C.1.2. Crisis of civilization
C.1.3. Crisis of innovation and technologies
C.2. Changing economic and industrial cultures
List of Abbreviations
References
Index. A, B, C
D, E, F
G, H, I
K, L, M
N, O, P
R, S, T
U, V, W, Z
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