1. The complexity perspective on business and organisations
Nigel Gilbert
Centre for Research on Social Simulation
University of Surrey
Guildford, UK

2. Principles
The micro and the macro
Interaction
Emergence
Evolution

3. Micro and macro macro bodies firms sectors nations market micro organs
people
cities
traders

4. Simple economics re-thought
Epstein JM, and R Axtell. Growing artificial societies: social science from the bottom up. Cambridge, MA: MIT Press, 1996.

5. Examples of successes Supply chain management Traffic modelling
Regulated markets
Electricity, gas, telecom,
Environmental resource management
Water, land use
Innovation and R&D policy

6. Interaction and emergence
Simple rules lead to simple (or complicated) phenomena
Interaction leads to emergence
Variation and selection leads learning
Complex adaptive systems

7. Downward causation and immergence

8. Explanation “If you can’t generate it, you haven’t explained it”
Path dependency
Point predictions are rarely possible, but
Distributions
Ranges
Scenarios
Attractors
may be

9. Implications
Thinking about the social world and business has been over-reliant on linear models
The complexity perspective can be enlightening in explaining
Positive feedbacks and network effects
Why things rarely repeat themselves exactly
The link between individual action and society

10. More information from…
European Social Simulation Association