Modelling Dynamic Market Potential: Identifying Hidden Automata Networks in the Diffusion of Pharmaceutical Drugs

This paper proposes an extension of the Guseo–Guidolin model (GGM; Guseo and Guidolin, 2009), with reference to the communication component, which is based on an assumption of complete connectivity of the hidden network supporting the growth of awareness focussed on specific pharmaceutical drugs or products with wide communication investments. The basic ideas are grounded on the extension of the Fibich–Gibori distribution (Fibich and Gibori, 2010) obtained for a minimally connected one dimensional, 1D, network topology and a subsequent inclusion, in a convex combination, with the Bemmaor–Lee distribution (Bemmaor and Lee, 2002), which takes into account unobserved heterogeneity aspects of agents in a market under a complete connectivity. Based on a continuum between opposite extremes, the extended final model, the network automata NA-GGM, allows the modulation of the involved network in a communication process that determines dynamic market potential applications of GGM are then given for some antidiabetic drugs in Italy. A specific application of the new model is discussed in detail with reference to a statin, Rextat, in the central part of Italy. The proposed extension, NA-GGM, is statistically globally significant with respect to the GGM and is more coherent in commercial behaviour forecasting.