Exploring the Interdependencies among Mechanisms Underlying Innovation Diffusion Dynamics

Understanding the dynamic nature of the innovation diffusion processes, and the mechanism underlying these dynamics is crucial in both corporate strategy and public policy contexts. However, the dynamic complexity of the diffusion processes due to the intrinsic non-linearity and feedback relations make this a challenging task. As an attempt to develop a better comprehension, a set of basic simulation models that incorporate relevant mechanisms such as information diffusion, word-of-mouth, increasing returns due to network externalities, learning-by-doing, learning-by-using, etc. is used as experimental grounds. This paper discusses the results obtained as a result of an exploration process conducted using one of these models focusing on the information diffusion via learning processes. The model can be characterized as a dynamic internal influence model, which incorporates imperfect information on both potential adopters' and adopters' sides. The model is used to explore the way diffusion dynamics and learning processes interact under different scenarios related to the state of the knowledge about the innovation. Experiments reveal some conditions where these simple lead up to counterintuitive diffusion dynamics as a consequence of the interdependencies between these mechanisms. Although the study does not focus on a specific diffusion case, the results obtained from the extensive experiments provide valuable insight regarding the potential of learning and information diffusion processes in strongly influencing the overall dynamics of a diffusion process.