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The complexity perspective on business

and organisationsNigel Gilbert

Centre for Research on Social SimulationUniversity of Surrey

Guildford, UK

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Principles

• The micro and the macro• Interaction• Emergence• Evolution

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Micro and macro

macro bodies firms sectors nations market

micro organs people firms cities traders

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Simple economics re-thought

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Epstein JM, and R Axtell. Growing artificial societies: social science from the bottom up. Cambridge, MA: MIT Press, 1996.

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Examples of successes• Supply chain management• Traffic modelling• Regulated markets

Electricity, gas, telecom, • Environmental resource management Water, land use

• Innovation and R&D policy

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Interaction and emergence• Simple rules lead to simple (or complicated) phenomena

• Interaction leads to emergence• Variation and selection leads learning

Complex adaptive systems

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Downward causation and immergence

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Explanation• ““If you can’t generate it, you If you can’t generate it, you haven’t explained it”haven’t explained it”

• Path dependency• Point predictions are rarely possible, but

Distributions Ranges Scenarios Attractorsmay be

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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

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More information from…

European Social Simulation Association

http://www.essa.eu.org