Computational Model Library

This is an agent-based model with two types of agents: customers and insurers. Insurers are price-takers who choose how much to spend on their service quality, and customers evaluate insurers based on premium, brand preference, and their perceived service quality. Customers are also connected in a small-world network and may share their opinions with their network.

The ABM contains two types of agents: insurers and customers. These act within the environment of a motor insurance market. At each simulation, the model undergoes the following steps:

  1. Network generation: At the start of the simulation, the model generates a small world network of social links between the customers, and randomly assigns each customer to an initial insurer
  2. ...

This model simulates different seeding strategies for information diffusion in a social network adjusted to a case study area in rural Zambia. It systematically evaluates different criteria for seed selection (centrality measures and hierarchy), number of seeds, and interaction effects between seed selection criteria and set size.

Studies on word-of-mouth identify two behaviors leading to transmission of information between individuals: proactive transmission of information, and information seeking. Individuals who are aware might be curious of it and start seeking for information; they might find around them the expertise held by another individual. Field studies indicate individuals do not adopt an innovation if they don’t hold the corresponding expertise. This model describes this information seeking behavior, and enables the exploration of the dynamics which emerges out of it.

Diffusion dynamics in small-world networks with heterogeneous consumers

Sebastiano Delre | Published Sat Sep 10 10:38:57 2011 | Last modified Sat Apr 27 20:18:30 2013

This model simulates diffusion curves and it allows to test how social influence, network structure and consumer heterogeneity affect their spreads and their speeds.

An agent-based framework that aggregates social network-level individual interactions to run targeting and rewarding programs for a freemium social app. Git source code in https://bitbucket.org/mchserrano/socialdynamicsfreemiumapps

9 Maturity levels in Empirical Validation - An innovation diffusion example

Martin Rixin | Published Wed Oct 19 13:42:28 2011 | Last modified Sat Apr 27 20:18:17 2013

Several taxonomies for empirical validation have been published. Our model integrates different methods to calibrate an innovation diffusion model, ranging from simple randomized input validation to complex calibration with the use of microdata.

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