IDEAS home Printed from https://ideas.repec.org/p/rug/rugwps/04-276.html
   My bibliography  Save this paper

Dynamic cross-sales effects of price promotions: Empirical generalizations

Author

Listed:
  • B. VINDEVOGEL
  • D. VAN DEN POEL
  • G. WETS

Abstract

In this research we use the framework of market-basket analysis and techniques from modern multivariate time-series analysis to measure and explain the dynamic impact of a price promotion on the sales of a complementary product. The large scale of this research enables us to derive empirical generalizations. We contribute to the literature in drawing the following conclusions: Firstly, we illustrate that using an intense promotion strategy, characterized by deeper and more frequent price promotions, has a negative impact on the cross-price effect. Secondly, we show that using the same brand name (umbrella branding) for two complements has a beneficial influence on the cross-price effect. Finally, we show that price levels of the products are important moderators in explaining persistent cross-price effects.

Suggested Citation

  • B. Vindevogel & D. Van Den Poel & G. Wets, 2004. "Dynamic cross-sales effects of price promotions: Empirical generalizations," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/276, Ghent University, Faculty of Economics and Business Administration.
  • Handle: RePEc:rug:rugwps:04/276
    as

    Download full text from publisher

    File URL: http://wps-feb.ugent.be/Papers/wp_04_276.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. B. Vindevogel & D. Van Den Poel & G. Wets, 2004. "Why promotion strategies based on market basket analysis do not work," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/262, Ghent University, Faculty of Economics and Business Administration.
    2. Magid M. Abraham & Leonard M. Lodish, 1993. "An Implemented System for Improving Promotion Productivity Using Store Scanner Data," Marketing Science, INFORMS, vol. 12(3), pages 248-269.
    3. David J. Hand & Heikki Mannila & Padhraic Smyth, 2001. "Principles of Data Mining," MIT Press Books, The MIT Press, edition 1, volume 1, number 026208290x, December.
    4. D. VAN DEN POEL & Jan J. DE SCHAMPHELAERE & G. WETS, 2003. "Direct and Indirect Effects of Retail Promotions," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 03/202, Ghent University, Faculty of Economics and Business Administration.
    5. G. Dekimpe, Marnik & Hanssens, Dominique M. & Silva-Risso, Jorge M., 1998. "Long-run effects of price promotions in scanner markets," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 269-291, November.
    6. Evans, Lewis & Wells, Graeme, 1983. "An alternative approach to simulating var models," Economics Letters, Elsevier, vol. 12(1), pages 23-29.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. B. Vindevogel & D. Van Den Poel & G. Wets, 2004. "Why promotion strategies based on market basket analysis do not work," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/262, Ghent University, Faculty of Economics and Business Administration.
    2. Vincent R. Nijs & Marnik G. Dekimpe & Jan-Benedict E.M. Steenkamps & Dominique M. Hanssens, 2001. "The Category-Demand Effects of Price Promotions," Marketing Science, INFORMS, vol. 20(1), pages 1-22, September.
    3. Dekimpe, M.G. & Hanssens, D.M., 2003. "Persistence Modeling for Assessing Marketing Strategy Performance," ERIM Report Series Research in Management ERS-2003-088-MKT, 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.
    4. Koen Pauwels & Shuba Srinivasan, 2004. "Who Benefits from Store Brand Entry?," Marketing Science, INFORMS, vol. 23(3), pages 364-390, July.
    5. Leeflang, Peter S.H. & Parreño Selva, Josefa & Van Dijk, Albert & Wittink, Dick R., 2008. "Decomposing the sales promotion bump accounting for cross-category effects," International Journal of Research in Marketing, Elsevier, vol. 25(3), pages 201-214.
    6. Srinivasan, S. & Pauwels, K.H. & Hanssens, D.M. & Dekimpe, M.G., 2002. "Do Promotions Benefit Manufacturers, Retailers or Both?," ERIM Report Series Research in Management ERS-2002-21-MKT, 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.
    7. Putsis, William Jr. & Dhar, Ravi, 2001. "An empirical analysis of the determinants of category expenditure," Journal of Business Research, Elsevier, vol. 52(3), pages 277-291, June.
    8. Sridhar, Shrihari & Naik, Prasad A. & Kelkar, Ajay, 2017. "Metrics unreliability and marketing overspending," International Journal of Research in Marketing, Elsevier, vol. 34(4), pages 761-779.
    9. Kenneth F. Wallis & Jan P. A. M. Jacobs, 2005. "Comparing SVARs and SEMs: two models of the UK economy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 209-228.
    10. Kurt A. Jetta & Erick W. Rengifo, 2009. "Improved Baseline Sales," Fordham Economics Discussion Paper Series dp2009-02, Fordham University, Department of Economics.
    11. Fernandez del Pozo, J. A. & Bielza, C. & Gomez, M., 2005. "A list-based compact representation for large decision tables management," European Journal of Operational Research, Elsevier, vol. 160(3), pages 638-662, February.
    12. Le, Hong Hanh & Viviani, Jean-Laurent, 2018. "Predicting bank failure: An improvement by implementing a machine-learning approach to classical financial ratios," Research in International Business and Finance, Elsevier, vol. 44(C), pages 16-25.
    13. Fischer, Greg & Karlan, Dean & McConnell, Margaret & Raffler, Pia, 2019. "Short-term subsidies and seller type: A health products experiment in Uganda," Journal of Development Economics, Elsevier, vol. 137(C), pages 110-124.
    14. Li, Hui & Sun, Jie, 2009. "Hybridizing principles of the Electre method with case-based reasoning for data mining: Electre-CBR-I and Electre-CBR-II," European Journal of Operational Research, Elsevier, vol. 197(1), pages 214-224, August.
    15. Zhang, Xiaolong & Burke, Gerard J., 2011. "Analysis of compound bullwhip effect causes," European Journal of Operational Research, Elsevier, vol. 210(3), pages 514-526, May.
    16. Matthias Staat & Maik Hammerschmidt, 2004. "A Super Efficiency Model for Product Evaluation," Microeconomics 0402011, University Library of Munich, Germany.
    17. Chen, Chien-Ming & van Dalen, Jan, 2010. "Measuring dynamic efficiency: Theories and an integrated methodology," European Journal of Operational Research, Elsevier, vol. 203(3), pages 749-760, June.
    18. Xue, Puning & Zhou, Zhigang & Fang, Xiumu & Chen, Xin & Liu, Lin & Liu, Yaowen & Liu, Jing, 2017. "Fault detection and operation optimization in district heating substations based on data mining techniques," Applied Energy, Elsevier, vol. 205(C), pages 926-940.
    19. Min-feng Lee & Guey-shya Chen & Shao-pin Lin & Wei-jie Wang, 2022. "A Data Mining Study on House Price in Central Regions of Taiwan Using Education Categorical Data, Environmental Indicators, and House Features Data," Sustainability, MDPI, vol. 14(11), pages 1-15, May.
    20. Caruso, Germán & Scartascini, Carlos & Tommasi, Mariano, 2015. "Are we all playing the same game? The economic effects of constitutions depend on the degree of institutionalization," European Journal of Political Economy, Elsevier, vol. 38(C), pages 212-228.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rug:rugwps:04/276. See general information about how to correct material in RePEc.

    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 CitEc recognized a bibliographic reference but did not link an item in RePEc 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Nathalie Verhaeghe (email available below). General contact details of provider: https://edirc.repec.org/data/ferugbe.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.