Advanced Search
MyIDEAS: Login to save this paper or follow this series

Relevance of Functional Flexibility for Heterogeneous Sales Response Models - A Comparision of Parametric and Seminoparametric Models

Contents:

Author Info

  • Hruschka, Harald
Registered author(s):

    Abstract

    So far studies estimating sales response functions on the basis of store-specific data either consider heterogeneity or functional flexibility. That is why in this contribution a model is developed possessing both these features. It is a multilayer perceptron with store-specific coefficients which is specified in a hierarchical Bayesian framework. An appropriate Markov Chain Monte Carlo estimation technique is introduced capable to satisfy theoretical constraints (e.g. sign constraints on elasticities). The empirical study refers to a data base consisting of weekly observations of sales and prices for nine leading brands of a packaged consumer good category. The data were acquired in 81 stores over a time span of at least 61 weeks. The multilayer perceptron is compared to a strict parametric multiplicative model and approaches the maximum value of posterior model probability. This indicates the benefits of using a flexible model even if heterogeneity is dealt with. Estimated sales curves and elasticities demonstrate that both models differ in their implications about price response. Bisher haben Untersuchungen zur Schätzung von Absatzreaktionsfunktionen auf Grundlage outletspezifischer Daten entweder Heterogenität oder funktionale Flexibilität berücksichtigt. Daher entwickelt der vorliegende Beitrag ein Modell, das beide Eigenschaften besitzt. Es handelt sich um ein Mehrschichtperzeptron mit outletspezifischen Koeffizienten, das mittels eines hierarchischen Bayesschen Ansatzes spezifiziert wird. Zur Schätzung dieses Modells wird eine geeignete Markov-Ketten-Monte-Carlo Technik eingeführt, die theoretisch begründete Restriktionen einhält (z.B. Vorzeichenrestriktionen von Elastizitäten). Die empirische Untersuchung bezieht sich auf einen Datensatz, der aus wöchentlichen Beobachtungen von Absatzmengen und Preisen für neun Marken einer Konsumgüterkategorie besteht. Diese Daten wurden in 81 Outlets über eine Zeitspanne von mindestens 61 Wochen erhoben. Das Mehrschichtperzeptron wird mit einem strikt parametrischen multiplikativen Modell verglichen und erreicht den Maximalwert der a-posteriori Modellwahrscheinlichkeit. Dieses Ergebnis zeigt die Vorteilhaftigkeit der Verwendung eines flexiblen Modells auch bei Berücksichtigung von Heterogenität auf. Geschätzte Absatzkurven und Elastizitäten verdeutlichen, dass beide Modelle jeweils unterschiedliche Preiseffekte implizieren.

    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://epub.uni-regensburg.de/4509/1/hh2.pdf
    Download Restriction: no

    Bibliographic Info

    Paper provided by University of Regensburg, Department of Economics in its series University of Regensburg Working Papers in Business, Economics and Management Information Systems with number 394.

    as in new window
    Length:
    Date of creation: 2004
    Date of revision:
    Handle: RePEc:bay:rdwiwi:463

    Contact details of provider:
    Postal: Universitäts-Str. 31, D-93040 Regensburg
    Phone: +49 941 943-2392
    Fax: +49 941 943-4752
    Email:
    Web page: http://www-wiwi.uni-regensburg.de/
    More information through EDIRC

    Related research

    Keywords: Marketing; Absatzreaktion ; Hierarchische Bayesche Modellierung ; Mehrschichtperzeptron ; Neuronale Netzwerke ; Marketing; Sales Response ; Hierarchical Bayes ; Multilayer Perceptron ; Neural Networks ; Marketing;

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    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:bay:rdwiwi:463. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Gernot Deinzer).

    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.