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Networks & Agent Based Models

For these reasons, ABMs have been used to analyse the patterns of seasonal migration, transmission of disease, combat, urban segmentation, stock market volatility, the spread of fads and fashions and the evolution of language and culture. These dynamic systems are modelled in computer simulations so that the relationships between the simple, micro-level rules and the complex outcomes that emerge can be better understood. In this way, hypotheses can be tested about the impact of changes in the rules of agent behaviour on overall system robustness, as well as the effect of intervention at various stages in the system’s evolution and the types of path dependency that may result.

 

In the business context, ABMs have been used to inform a wide variety of strategic decisions, including formulation of more effective and adaptive marketing campaigns, evaluating the impact of social connections on healthcare outcomes, providing improved inputs into new product development processes, assessing the penetration of products in new markets and maximising traffic to geographically dispersed retail outlets. One of the most powerful features of agent-based modelling is the flexibility it offers, allowing different scales of analysis and application to diverse and complex business problems.

 

Read more about Volterra’s approach to social networks, our techniques for analysing new product penetration, Tacit Knowledge Mapping, market trading models and the spread of ideas and behaviour, or read about our new report on the benefits of choice in financial services.