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Market diffusion of new products is driven by the actions and reactions of consumers, distributors, competitors, and other stakeholders, all of whom can be heterogeneous in their individual characteristics, attitudes, needs, and objectives. These actors may also interact with others in various ways (e.g., through word of mouth or social influence). Thus, a typical consumer market constitutes a complex system whose behavior is difficult to foresee because stochastic impulses may give rise to complex emergent patterns of system reactions over time. Agent-based modeling, a relatively novel approach to understanding complex systems, is well equipped to deal with this complexity and, therefore, may serve as a valuable tool for both researchers studying particular market effects and practitioners seeking decision support for determining features of products under development or the appropriate combination of measures to accelerate product diffusion in a market. This paper provides an overview of the strengths and criticisms of such tools. It aims to encourage researchers in the field of innovation management, as well as practitioners, to consider agent-based modeling and simulation as a method for gaining deeper insights into market behavior and making better-informed decisions.

Agent‐based modeling of new product market diffusion: an overview of strengths and criticisms