Complexity-Based Modelling Approaches for Commercial Applications

Complexity-Based Modelling Approaches for Commercial Applications

D. Collings (BT PLC, UK)
DOI: 10.4018/978-1-59140-984-7.ch054
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Abstract

Understanding complex socio-economic systems is a key problem for commercial organizations. In this chapter we discuss the use of agent-based modelling to produce decision support tools to enhance this understanding. We consider the important aspects of the model creation process which include the facilitation of dialogue necessary to extract knowledge, the building of understanding, and the identification of model limitations. It is these aspects that are crucial in the establishment of trust in a model. We use the example of modelling opinion diffusion within a customer population and its effect on product adoption to illustrate how the agent-based modelling technique can be an ideal tool to create models of complex socioeconomic systems. We consider the advantages compared to alternative, more conventional approaches available to analysts and management decision makers.

Key Terms in this Chapter

Social Networks: The links between individuals in a population.

Agent-Based Models: Simulations consisting of a number of discrete entities, each with their own rules of behaviour. These rules determine the interactions between the elements, and between the elements (agents) and the environment in which they are contained.

Emergent Behaviour: The macroscopic behaviour of a complex system emerges from the individual interactions of its constituent elements.

Network externalities: The circumstance where a product’s utility changes as the number of agents consuming it changes. A classic example of a product that exhibits network externalities is the fax machine: as more people purchase fax machines, users can communicate with a greater number of people, and the utility of the device increases.

Complexity: Refers to tools, techniques, and approaches from the field of Complexity Science. Complexity Science is a highly interdisciplinary field dedicated to understanding complex systems. In this context a complex system is defined as a set of elements that often exhibit adaptation and interact in a non-linear fashion. The overall behaviour of a complex system can be counter-intuitive and difficult to predict by studying the individual components in isolation.

Small-World Networks: The concept of a small-world network is now widely accepted and is defined as a social network where the chains of intermediate acquaintances required to connect any two individuals are small compared to the total number of people.

Socio-Economic System: A type of complex system (see Complexity) that consists of social and economic elements. Descriptions of these systems tend to have significant qualitative elements and are difficult to analyse using traditional macroscopic techniques.

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