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When introducing a new product into market, substantial amounts of resources are put at stake. Innovation managers therefore seek for reliable predictions of the respective innovation diffusion process. Making such predictions, however, is challenging, because the diffusion trajectory is affected by various factors such as the type of innovation, its perceived attributes, marketing activities and their impact, or consumers’ individual communication and adoption behaviors. Modeling the diffusion of innovations accordingly is of interest for both practitioners and management scholars.

 An agent-based model can overcome many limitations of traditional approaches. It accounts for heterogeneity in consumer preferences as well as in the social structure of their interactions and allows for modeling consumers as boundedly rational agents who make decisions under uncertainty and are influenced by micro-level drivers of …