Innovation diffusion models are used in business statistics and quantitative marketing to describe and forecast the growth dynamics of new products and technologies when launched into markets. Such models are useful, as they shed light on the mechanisms that generate and enhance the penetration of an innovation into a social system. The most famous diffusion model is that by Bass (1969), which forms the basis of several extensions of it. One of these, the Guseo-Guidolin model (2009), assumes a dynamic market potential, which is generated by a communication process among consumers. This model has proven a useful improvement of the Bass model in different industrial applications (e.g., pharmaceutical, ICTs). We propose new applications of the Guseo-Guidolin model in three industrial sectors, where timely analyses and forecasts on consumption dynamics are of strategic importance for business and policy choices: energy, entertainment, pharmaceutical. In particular, we show the forecasting improvement obtained with respect to the simpler Bass model and give a precise interpretation of the parameters involved in all applications.
A Diffusion Model with Dynamic Potential: New Applications to Industrial Sectors
GUIDOLIN, MARIANGELA
2014
Abstract
Innovation diffusion models are used in business statistics and quantitative marketing to describe and forecast the growth dynamics of new products and technologies when launched into markets. Such models are useful, as they shed light on the mechanisms that generate and enhance the penetration of an innovation into a social system. The most famous diffusion model is that by Bass (1969), which forms the basis of several extensions of it. One of these, the Guseo-Guidolin model (2009), assumes a dynamic market potential, which is generated by a communication process among consumers. This model has proven a useful improvement of the Bass model in different industrial applications (e.g., pharmaceutical, ICTs). We propose new applications of the Guseo-Guidolin model in three industrial sectors, where timely analyses and forecasts on consumption dynamics are of strategic importance for business and policy choices: energy, entertainment, pharmaceutical. In particular, we show the forecasting improvement obtained with respect to the simpler Bass model and give a precise interpretation of the parameters involved in all applications.
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