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Description:
Companies employ international diffusion models to assess the local market potential and local diffusion speed to support their decision making on market entry. After their entry into a country, they use the model forecasts for their performance controlling. To this end, empirical applications of international diffusion models aim to link differential diffusion patterns across countries to various exogenous drivers. In the literature, macro- and socioeconomic variables like population characteristics, culture, economic development, etc. have been linked to differential penetration developments across countries. But as companies cannot influence these drivers, their marketing decisions that shape national diffusion patterns are ignored. Is this reasonable? What then, is the role of marketing instruments in an international diffusion context? We address this issue and compare the influence of these prominent exogenous drivers of international diffusion with that of industry and marketing-mix variables. To account for all of these factors and simultaneously accommodate the influence of varying cross-country interactions, we develop a more flexible yet parsimonious model of international diffusion. Finally, to avoid technical issues in implementing spatially dependent error terms we introduce the test concept of Moran's I to international diffusion model. We demonstrate that the lead-lag effect in conjunction with spatial neighborhood effects controls most of the spatial autocorrelation. Using this combined approach we find that - for cellulars - industry and marketing-mix variables explain international diffusion patterns better than macro- and socioeconomic drivers.