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Our mission is to help computational modelers at all levels engage in the establishment and adoption of community standards and good practices for developing and sharing computational models. Model authors can freely publish their model source code in the Computational Model Library alongside narrative documentation, open science metadata, and other emerging open science norms that facilitate software citation, reproducibility, interoperability, and reuse. Model authors can also request peer review of their computational models to receive a DOI.
All users of models published in the library must cite model authors when they use and benefit from their code.
Please check out our model publishing tutorial and contact us if you have any questions or concerns about publishing your model(s) in the Computational Model Library.
We also maintain a curated database of over 7500 publications of agent-based and individual based models with additional detailed metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
Displaying 6 of 6 results diffusion of innovations clear
Diffusion of goods with multiple characteristics and price premiums
Pedro López Merino | Published Friday, February 18, 2022An agent-based model for the diffusion of innovations with multiple characteristics and price-premiums
Reflexivity in a diffusion of innovations model
Carlos Cordoba Cesar Garcia-Diaz | Published Thursday, May 07, 2020In this agent-based model, agents decide to adopt a new product according to a utility function that depends on two kinds of social influences. First, there is a local influence exerted on an agent by her closest neighbors that have already adopted, and also by herself if she feels the product suits her personal needs. Second, there is a global influence which leads agents to adopt when they become aware of emerging trends happening in the system. For this, we endow agents with a reflexive capacity that allows them to recognize a trend, even if they can not perceive a significant change in their neighborhood.
Results reveal the appearance of slowdown periods along the adoption rate curve, in contrast with the classic stylized bell-shaped behavior. Results also show that network structure plays an important role in the effect of reflexivity: while some structures (e.g., scale-free networks) may amplify it, others (e.g., small-world structure) weaken such an effect.
Diffusion of innovations
Marco Janssen | Published Tuesday, January 14, 20203 simple models to illustrate diffusion of innovations.
The models are discussed in Introduction to Agent-Based Modeling by Marco Janssen. For more information see https://intro2abm.com/
Diffusion of Innovations on Social Networks
Hang Xiong | Published Saturday, April 16, 2016This is model that simulates how multiple kinds of peer effects shape the diffusion of innovations through different types of social relationships.
Adoption as a social marker
Paul Smaldino | Published Monday, October 17, 2016A model of innovation diffusion in a structured population with two groups who are averse to adopting a produce popular with the outgroup.
(Policy induced) Diffusion of Innovations - An integrated demand-supply Model based on Cournot Competition
Martin Rixin | Published Monday, August 29, 2011 | Last modified Saturday, April 27, 2013Objective is to simulate policy interventions in an integrated demand-supply model. The underlying demand function links both sides. Diffusion proceeds if interactions distribute awareness (Epidemic effect) and rivalry reduces the market price (Probit effect). Endogeneity is given due to the fact that consumer awareness as well as their willingness-to-pay drives supply-side rivalry. Firm´s entry and exit decisions as well as quantity and price settings are driven by Cournot competition.