Publication: Integrating behavioural experimental findings into dynamical models to inform social change interventions
Integrating behavioural experimental findings into dynamical models to inform social change interventions
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Tanase, R., Algesheimer, R., & Mariani, M. (2026). Integrating behavioural experimental findings into dynamical models to inform social change interventions. Nature Human Behaviour, Epub ahead of print. https://doi.org/10.1038/s41562-026-02417-4
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Addressing global challenges often involves stimulating the large-scale adoption of new products or behaviours. Research traditions that focus on individual decision-making suggest that achieving this objective requires identifying the drivers of individual discrete adoption choices. However, computational approaches rooted in complexity science focus on maximizing the propagation of a given product or behaviour throughout social networks of interconnected adopters. Here, by integrating discrete-choice modelling into the complex conta
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Tanase, R., Algesheimer, R., & Mariani, M. (2026). Integrating behavioural experimental findings into dynamical models to inform social change interventions. Nature Human Behaviour, Epub ahead of print. https://doi.org/10.1038/s41562-026-02417-4
