Publication: Integrating Behavioral Experimental Findings into Dynamical Models to Inform Social Change Interventions
Integrating Behavioral Experimental Findings into Dynamical Models to Inform Social Change Interventions
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Tanase, R., Algesheimer, R., & Mariani, M. S. (2024). Integrating Behavioral Experimental Findings into Dynamical Models to Inform Social Change Interventions (No. 4837583; SSRN). https://doi.org/10.2139/ssrn.4837583
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Addressing global challenges – from public health to climate change – often involves stimulating the large-scale adoption of new products or behaviors. Research traditions that focus on individual decision making suggest that achieving this objective requires better identifying the drivers of individual adoption choices. On the other hand, computational approaches rooted in complexity science focus on maximizing the propagation of a given product or behavior throughout social networks of interconnected adopters. The integration of the
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Tanase, R., Algesheimer, R., & Mariani, M. S. (2024). Integrating Behavioral Experimental Findings into Dynamical Models to Inform Social Change Interventions (No. 4837583; SSRN). https://doi.org/10.2139/ssrn.4837583
