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

Principles The micro and the macro Interaction Emergence Evolution

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

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

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

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

Downward causation and immergence

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

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

More information from… European Social Simulation Association http://www.essa.eu.org