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Persistence Modeling for Assessing Marketing Strategy Performance

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  • Dekimpe, M.G.
  • Hanssens, D.M.

Abstract

The question of long-run market response lies at the heart of any marketing strategy that tries to create a sustainable competitive advantage for the firm or brand. A key challenge, however, is that only short-run results of marketing actions are readily observable. Persistence modeling addresses the problem of long-run market-response quantification by combining into one measure of “net long-run impact” the chain reaction of consumer response, firm feedback and competitor response that emerges following the initial marketing action. In this paper, we (i) summarize recent marketing-strategic insights that have been accumulated through various persistence modeling applications, (ii) provide an introduction to some of the most frequently used persistence modeling techniques, and (iii) identify some other strategic research questions where persistence modeling may prove to be particularly valuable.

Suggested Citation

  • 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.
  • Handle: RePEc:ems:eureri:1063
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    References listed on IDEAS

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    1. 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.
    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. Keiko Powers & Dominique M. Hanssens & Yih-Ing Hser & M. Douglas Anglin, 1991. "Measuring the Long-Term Effects of Public Policy: The Case of Narcotics Use and Property Crime," Management Science, INFORMS, vol. 37(6), pages 627-644, June.
    4. 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.
    5. Pesaran, M. H. & Pierse, R. G. & Lee, K. C., 1993. "Persistence, cointegration, and aggregation : A disaggregated analysis of output fluctuations in the U.S. economy," Journal of Econometrics, Elsevier, vol. 56(1-2), pages 57-88, March.
    6. Baghestani, Hamid, 1991. "Cointegration Analysis of the Advertising-Sales Relationship," Journal of Industrial Economics, Wiley Blackwell, vol. 39(6), pages 671-681, December.
    7. Dick Wittink & Csilla Horvath & Peter S.H. Leeflang, 2001. "Dynamic Analysis of a Competitive Marketing System," Yale School of Management Working Papers ysm226, Yale School of Management.
    8. Marnik G. Dekimpe & Dominique M. Hanssens, 1995. "The Persistence of Marketing Effects on Sales," Marketing Science, INFORMS, vol. 14(1), pages 1-21.
    9. Deleersnyder, B. & Geyskens, I. & Gielens, K. & Dekimpe, M.G., 2002. "How Cannibalistic is the Internet Channel?," ERIM Report Series Research in Management ERS-2002-22-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.
    10. Gregory, Allan W & Hansen, Bruce E, 1996. "Tests for Cointegration in Models with Regime and Trend Shifts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(3), pages 555-560, August.
    11. Deleersnyder, B. & Geyskens, I. & Gielens, K.J.P. & Dekimpe, M.G., 2002. "How cannibalistic is the internet channel? A study of the newspaper industry in the United Kingdom and the Netherlands," Other publications TiSEM 16dcb25c-7ea9-4c75-bdf6-5, Tilburg University, School of Economics and Management.
    12. Evans, Lewis & Wells, Graeme, 1983. "An alternative approach to simulating var models," Economics Letters, Elsevier, vol. 12(1), pages 23-29.
    13. Engle, Robert F. & Yoo, Byung Sam, 1987. "Forecasting and testing in co-integrated systems," Journal of Econometrics, Elsevier, vol. 35(1), pages 143-159, May.
    14. Franses, Philip Hans & Kloek, Teun & Lucas, Andre, 1998. "Outlier robust analysis of long-run marketing effects for weekly scanning data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 293-315, November.
    15. Koen Pauwels & Shuba Srinivasan, 2004. "Who Benefits from Store Brand Entry?," Marketing Science, INFORMS, vol. 23(3), pages 364-390, July.
    16. Marnik G. Dekimpe & Dominique M. Hanssens, 1995. "Empirical Generalizations About Market Evolution and Stationarity," Marketing Science, INFORMS, vol. 14(3_supplem), pages 109-121.
    17. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    18. Philip Hans Franses, 2001. "How to deal with intercept and trend in practical cointegration analysis?," Applied Economics, Taylor & Francis Journals, vol. 33(5), pages 577-579.
    19. Stanley C. Hollander & Kathleen M. Rassuli (ed.), 1993. "Marketing," Books, Edward Elgar Publishing, volume 0, number 512.
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    1. Long Gao & Birendra K. Mishra, 2019. "The Role of Market Evolution in Channel Contracting," Management Science, INFORMS, vol. 67(5), pages 2432-2441, May.

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    More about this item

    Keywords

    long-run effectiveness; marketing strategy; time-series analysis;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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