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Modeling seasonality in new product diffusion

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Show simple item record Peers, Y. Fok, D. Franses, P. H. 2012-11-30T03:03:34Z 2012-11-30T03:03:34Z 2012-04-02 2012
dc.identifier.citation Peers, Y., Fok, D., & Franses, P. H. (2012). Modeling Seasonality in New Product Diffusion. Marketing Science, 31(2), 351-364. en_NZ
dc.identifier.issn 1526-548X
dc.description.abstract We propose a method to include seasonality in any diffusion model that has a closed-form solution. The resulting diffusion model captures seasonality in a way that naturally matches the original diffusion model’s pattern. The method assumes that additional sales at seasonal peaks are drawn from previous or future periods. This implies that the seasonal pattern does not influence the underlying diffusion pattern. The model is compared with alternative approaches through simulations and empirical examples. As alternatives, we consider the standard Generalized Bass Model (GBM) and the basic Bass Model, which ignores seasonality. One of the main findings is that modeling seasonality in a GBM generates good predictions but gives biased estimates. In particular, the market potential parameter is underestimated. Ignoring seasonality in cases where data of the entire diffusion period are available gives unbiased parameter estimates in most relevant scenarios. However,ignoring seasonality leads to biased parameter estimates and predictions when only part of the diffusion period is available. We demonstrate that our model gives correct estimates and predictions even if the full diffusion process is not yet available. en_NZ
dc.language.iso en
dc.publisher INFORMS en_NZ
dc.relation.ispartof Marketing Science
dc.relation.uri en_NZ
dc.subject diffusion models en_NZ
dc.subject seasonality en_NZ
dc.subject forecasting en_NZ
dc.title Modeling seasonality in new product diffusion en_NZ
dc.type Journal Article en_NZ
dc.identifier.doi 10.1287/mksc.1110.0696 en_NZ

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