IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v23y2004i4p596-610.html
   My bibliography  Save this article

How Dynamic Consumer Response, Competitor Response, Company Support, and Company Inertia Shape Long-Term Marketing Effectiveness

Author

Listed:
  • Koen Pauwels

    (Tuck School of Business, Dartmouth University, Hanover, New Hampshire 03755)

Abstract

Long-term marketing effectiveness is a high-priority research topic for managers, and emerges from the complex interplay among dynamic reactions of several market players. This paper introduces restricted policy simulations to distinguish four dynamic forces: consumer response, competitor response, company inertia, and company support. A rich marketing dataset allows the analysis of price, display, feature, advertising, and product-line extensions. The first finding is that consumer response differs significantly from the net effectiveness of product-line extensions, price, feature, and advertising. In particular, net sales effects are stronger and longer-lasting than consumer response. Second, this difference is not due to competitor response, but to company action. For tactical actions (price and feature), it takes the form of , as promotions last for several weeks. For strategic actions (advertising and product-line extensions), by other marketing instruments greatly enhances dynamic consumer response. This company action negates the postpromotion dip in consumer response, and enhances the long-term sales benefits of product-line extensions, feature, and advertising. Therefore, managers are urged to evaluate company decision rules for inertia and support when assessing long-term marketing effectiveness.

Suggested Citation

  • Koen Pauwels, 2004. "How Dynamic Consumer Response, Competitor Response, Company Support, and Company Inertia Shape Long-Term Marketing Effectiveness," Marketing Science, INFORMS, vol. 23(4), pages 596-610, June.
  • Handle: RePEc:inm:ormksc:v:23:y:2004:i:4:p:596-610
    DOI: 10.1287/mksc.1040.0075
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.1040.0075
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mksc.1040.0075?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    2. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    3. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    4. M. Hashem Pesaran & Ron P. Smith, 1998. "Structural Analysis of Cointegrating VARs," Journal of Economic Surveys, Wiley Blackwell, vol. 12(5), pages 471-505, December.
    5. Søren Johansen & Rocco Mosconi & Bent Nielsen, 2000. "Cointegration analysis in the presence of structural breaks in the deterministic trend," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 216-249.
    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. Vincent R. Nijs & Shuba Srinivasan & Koen Pauwels, 2007. "Retail-Price Drivers and Retailer Profits," Marketing Science, INFORMS, vol. 26(4), pages 473-487, 07-08.
    2. Koen Pauwels & Shuba Srinivasan, 2004. "Who Benefits from Store Brand Entry?," Marketing Science, INFORMS, vol. 23(3), pages 364-390, July.
    3. M.G. Dekimpe & D.M. Hanssens, 2005. "Persistence Models and Marketing Strategy," Review of Business and Economic Literature, KU Leuven, Faculty of Economics and Business (FEB), Review of Business and Economic Literature, vol. 0(5), pages 855-884.
    4. Pauwels, Koen & Leeflang, Peter S.H. & Teerling, Marije L. & Huizingh, K.R. Eelko, 2011. "Does Online Information Drive Offline Revenues?," Journal of Retailing, Elsevier, vol. 87(1), pages 1-17.
    5. Shuba Srinivasan & Koen Pauwels & Dominique M. Hanssens & Marnik G. Dekimpe, 2004. "Do Promotions Benefit Manufacturers, Retailers, or Both?," Management Science, INFORMS, vol. 50(5), pages 617-629, May.
    6. 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.
    7. repec:rnp:ppaper:mak8 is not listed on IDEAS
    8. Pauwels, Koen & Neslin, Scott A., 2015. "Building With Bricks and Mortar: The Revenue Impact of Opening Physical Stores in a Multichannel Environment," Journal of Retailing, Elsevier, vol. 91(2), pages 182-197.
    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. Koen Pauwels & Dominique M. Hanssens, 2007. "Performance Regimes and Marketing Policy Shifts," Marketing Science, INFORMS, vol. 26(3), pages 293-311, 05-06.
    11. Steven M. Shugan, 2005. "Comments on Competitive Responsiveness," Marketing Science, INFORMS, vol. 24(1), pages 3-7.
    12. Pauwels, Koen & Aksehirli, Zeynep & Lackman, Andrew, 2016. "Like the ad or the brand? Marketing stimulates different electronic word-of-mouth content to drive online and offline performance," International Journal of Research in Marketing, Elsevier, vol. 33(3), pages 639-655.
    13. Fantazzini, Dean & Toktamysova, Zhamal, 2015. "Forecasting German car sales using Google data and multivariate models," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 97-135.
    14. KIYGI CALLI, Meltem & WEVERBERGH, Marcel & FRANSES, Philip Hans, 2008. "Modeling the effectiveness of hourly direct-response radio commercials," Working Papers 2008005, University of Antwerp, Faculty of Business and Economics.
    15. 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.
    16. Koen Pauwels & Imran Currim & Marnik Dekimpe & Dominique Hanssens & Natalie Mizik & Eric Ghysels & Prasad Naik, 2004. "Modeling Marketing Dynamics by Time Series Econometrics," Marketing Letters, Springer, vol. 15(4), pages 167-183, December.
    17. Kornelis, Marcel & Dekimpe, Marnik G. & Leeflang, Peter S.H., 2008. "Does competitive entry structurally change key marketing metrics?," International Journal of Research in Marketing, Elsevier, vol. 25(3), pages 173-182.
    18. Garratt, Anthony & Lee, Kevin C & Pesaran, M. Hashem & Shin, Yongcheol, 1998. "A Structural Cointegrating VAR Approach to Macroeconometric Modelling," Cambridge Working Papers in Economics 9823, Faculty of Economics, University of Cambridge.
    19. 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.
    20. Gelper, Sarah & Wilms, Ines & Croux, Christophe, 2016. "Identifying Demand Effects in a Large Network of Product Categories," Journal of Retailing, Elsevier, vol. 92(1), pages 25-39.
    21. Tan, Madeleine Sui-Lay, 2016. "Policy coordination among the ASEAN-5: A global VAR analysis," Journal of Asian Economics, Elsevier, vol. 44(C), pages 20-40.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:inm:ormksc:v:23:y:2004:i:4:p:596-610. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.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.