Ising-like agent-based technology diffusion model: Adoption patterns vs. seeding strategies

Authored by Santiago L. Rovere, Carlos E. Laciana

Date Published: 2011-03-15

DOI: 10.1016/j.physa.2010.11.006

Sponsors: United States National Science Foundation (NSF)

Platforms: Repast

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

The well-known Ising model used in statistical physics was adapted to a social dynamics context to simulate the adoption of a technological innovation. The model explicitly combines (a) an individual's perception of the advantages of an innovation and (b) social influence from members of the decision-maker's social network. The micro-level adoption dynamics are embedded into an agent-based model that allows exploration of macro-level patterns of technology diffusion throughout systems with different configurations (number and distributions of early adopters, social network topologies). In the present work we carry out many numerical simulations. We find that when the gap between the individual's perception of the options is high, the adoption speed increases if the dispersion of early adopters grows. Another test was based on changing the network topology by means of stochastic connections to a common opinion reference (hub), which resulted in an increment in the adoption speed. Finally, we performed a simulation of competition between options for both regular and small world networks. (C) 2010 Elsevier B.V. All rights reserved.

Tags

networks Ising model Technology adoption Collective decision Early adopters