Modeling Seasonality in New Product Diffusion

Posted: 24 Oct 2012

See all articles by Yuri Peers

Yuri Peers

affiliation not provided to SSRN

D. Fok

Econometric Institute - Erasmus University Rotterdam; Erasmus Research Institute of Management (ERIM); Tinbergen Institute Rotterdam

Philip Hans Franses

Erasmus University Rotterdam (EUR) - Department of Econometrics

Date Written: 2012

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.

Keywords: diffusion models, seasonality, forecasting

Suggested Citation

Peers, Yuri and Fok, Dennis and Franses, Philip Hans, Modeling Seasonality in New Product Diffusion (2012). Marketing Science, Vol. 31, No. 2, 2012; pp. 351-364; DOI: 10.1287/mksc.1110.0696. Available at SSRN: https://ssrn.com/abstract=2160824

Yuri Peers (Contact Author)

affiliation not provided to SSRN ( email )

Dennis Fok

Econometric Institute - Erasmus University Rotterdam ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

Erasmus Research Institute of Management (ERIM) ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands
+31 10 408 1333 (Phone)
+31 10 408 9162 (Fax)

Tinbergen Institute Rotterdam ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

Philip Hans Franses

Erasmus University Rotterdam (EUR) - Department of Econometrics ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands
+31 10 408 1278 (Phone)
+31 10 408 9162 (Fax)

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