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.
The Labour Markets and Ethnic Segmentation (LaMESt) Model is a model of a simplified labour market, where only jobs of the lowest skill level are considered. Immigrants of two different ethnicities (“Latino”, “Asian”) compete with a majority (“White”) and minority (“Black”) native population for these jobs. The model’s purpose is to investigate the effect of ethnically homogeneous social networks on the emergence of ethnic segmentation in such a labour market. It is inspired by Waldinger & Lichter’s study of immigration and the social organisation of labour in 1990’s Los Angeles.
This agent-based model examines the impact of seasonal aggregation, dispersion, and learning opportunities on the richness and evenness of artifact styles under random social learning (unbiased transmission).
A first version of a model that describes how coalitions are formed during open, networked innovation
We build a stylized model of a network of business angel investors and start-up entrepreneurs. Decisions are based on trust as a decision making tool under true uncertainty.