1. DBA Strategic Road Maps March 2018
PROFESSOR ROBIN MATTHEWS
KINGSTON UNIVERSITY BUSINESS SCHOOL LONDON
ACADEMY OF NATIONAL ECONOMY MOSCOW
MOSI YOSHKAR-OLA
ECONOMIC STRATEGIES
PRESIDENT OF THE LEAGUE OF CORPORATE STRATEGY AND ACCOUNTING
http/
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2. (current system state) T
Past
Future
upside
System state
possible futures
possible causes
probable futures
Probable causes
possible causes
possible futures
Now
(current system state) T
downside
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3. THE FUTURE (outer dynamics) 1. What is the future outlook and 2
THE FUTURE (outer dynamics) 1.What is the future outlook and 2. What are the risks for business? Use the diagram below in your presentation
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4. The global system is a complex system OPEN SYSTEMS
BUSINESS
Global business is a complex subsystem
of the global system
The global system is
a complex system
OPEN SYSTEMS
21/09/2018
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5. Complex adaptive systems can self organise spontaneously
Complex systems have a large number of parts
Interdependence between parts of the system
Hierarchies of systems; systems within systems
Continuous and dynamic interaction within and between levels of hierarchy
Emergence of unpredictable/surprizing events
The scale of effects can’t be predicted for example.
Positive and negative feedbacks. Unpredictable time lags
Systems and subsystems are open
Systems co-evolve.
Complex systems operate far from equilibrium.
Unpredictable patterns emerge which become attractors influence future directions.
Attractors may be orderly or chaotic.
No single entity has complete knowledge of the system.
Path dependence.
Complexity catastrophe

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9. PRODUCTS AND SERVICES (VALUE ADDED IN SUPPLY CHAIN)
SUPPLIERS
RETAILERS
FINAL CUSTOMERS
DISTRIBUTORS
FIRM’S VALUE CHAIN
VLUED VLUE
PRODUCTS AND SERVICES (VALUE ADDED IN SUPPLY CHAIN)
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10. energy company
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12. https://hbr.org/2007/01/how-leaders-create-and-use-networks
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13. META MODEL PAYOFFS INNER DYNAMICS DYNAMICS GRAMMAR OUTER DYNAMICSOUTER
Mandala
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16. Haldane (2009)
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17. Adjacency matrix F
Adjacency matrix E2 E1
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18. k = degree of a node; the number of connected edges
P(k) ≈ Ck – α
𝑃(𝑘)​ ​=​  𝐶 𝑘 𝛼
The internet
k = degree of a node; the number of connected edges
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19. Small world networks highly clustered, short path lengths
Degree of a node is the number of edges (k) connecting it to other nodes.
High degree nodes have many connections (high k); low degree nodes have few (low k)
P(k) probability of degree k follows a power law
P(k) ≈ k – α..
P(k) ≈ Ck – α..
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