We model the relationship between natural resource user´s individual time preferences and their use of destructive extraction method in the context of small-scale fisheries.

This model is a replication of Torsten Hägerstrand’s 1965 model–one of the earliest known calibrated and validated simulations with implicit “agent based” methodology.

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 model simulates consumer demand for Smart Metering tariffs. It utilizes the Bass Diffusion Model and Rogers´s adopter categories. Integration of empirical census microdata enables a validated socio-economic background for each consumer.

A simplified Arthur & Polak logic circuit model of combinatory technology build-out via incremental development. Only some inventions trigger radical effects, suggesting they depend on whole interdependent systems rather than specific innovations.

Using nodes from the 2002 General Social Survey sample, the code establishes a network of ties with a given homophily bias, and simulates Internet adoption rates in that network under three conditions: (i) no network externalities, (ii) general network externalities, where an individual’s reservation price is a function of the overall adoption rate in the network, (iii) specific network externalities, where reservation price is a function of the adoption rate in individual’s personal […]

Models the connection between health agency communication, personal protective behaviour (eg vaccination, hand hygiene) and influenza transmission.

A model of innovation diffusion in a structured population with two groups who are averse to adopting a produce popular with the outgroup.

The model is an experimental ground to study the impact of network structure on diffusion. It allows to construct a social network that already has some measurable level of homophily, and simulate a diffusion process over this social network.

An ABM, derived from a case study and a series of surveys with greenhouse growers in the Westland, Netherlands. Experiments using this model showshow that the greenhouse horticulture industry displays diversity, adaptive complexity and an uneven distribution, which all suggest that the industry is an evolving system.