Advanced Search
MyIDEAS: Login

Modeling Seasonality in New Product Diffusion

Contents:

Author Info

  • Peers, Y.
  • Fok, D.
  • Franses, Ph.H.B.F.

Abstract

Although high frequency diffusion data is nowadays available, common practice is still to only use yearly figures in order to get rid of seasonality. This paper proposes a diffusion model that captures seasonality in a way that naturally matches the overall S-shaped pattern. The model is based on the assumption 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 and ignoring seasonality by using the basic Bass model. One of our main findings is that modeling seasonality in a Generalized Bass Model does generate good predictions, but gives biased estimates. In particular, the market potential parameter will be underestimated. Ignoring seasonality gives the true parameter estimates if the data is available of the entire diffusion period. However, when only part of the diffusion period is available estimates and predictions become biased. Our model gives correct estimates and predictions even if the full diffusion process is not yet available.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://hdl.handle.net/1765/20378
Download Restriction: no

Bibliographic Info

Paper provided by Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam. in its series Research Paper with number ERS-2010-029-MKT.

as in new window
Length:
Date of creation: 15 Jul 2010
Date of revision:
Handle: RePEc:dgr:eureri:1765020378

Contact details of provider:
Web page: http://www.erim.eur.nl/

Related research

Keywords: seasonality; new product diffusion;

Other versions of this item:

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Fok, D. & Franses, Ph.H.B.F., 2005. "Seasonality on non-linear price effects in scanner-data based market-response models," Econometric Institute Report EI 2005-45, Erasmus University Rotterdam, Econometric Institute.
Full references (including those not matched with items on IDEAS)

Citations

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:dgr:eureri:1765020378

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (ERIM Series Handler at the ERIM Office).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.