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Persistence Modeling for Assessing Marketing Strategy Performance

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Author Info
Dekimpe, M.G.
Hanssens, D.M. (Erasmus Research Institute of Management (ERIM), RSM Erasmus University)

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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.

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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-2003-088-MKT Revision_Date: 2009-07-29.

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Date of creation: 27 Nov 2003
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Handle: RePEc:dgr:eureri:30001178

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Related research
Keywords: long-run effectiveness; time-series analysis; marketing strategy;

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  1. Deleersnyder, B. & Geyskens, I. & Gielens, K. & Dekimpe, M.G., 2002. "How Cannibalistic is the Internet Channel?," Research Paper ERS-2002-22-MKT Revision_, 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 Uni. [Downloadable!]
  2. Franses, Philip Hans, 2001. "How to Deal with Intercept and Trend in Practical Cointegration Analysis?," Applied Economics, Taylor and Francis Journals, vol. 33(5), pages 577-79, April. [Downloadable!] (restricted)
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  3. Dekimpe, M.G. & Franses, Ph.H.B.F. & Hanssens, D.M. & Naik, P., 2006. "Time-Series Models in Marketing," Research Paper ERS-2006-049-MKT Revision, 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 Uni. [Downloadable!]
  4. Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March. [Downloadable!] (restricted)
  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. [Downloadable!] (restricted)
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  6. 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. [Downloadable!] (restricted)
  7. Zivot, Eric & Andrews, Donald W K, 1992. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 251-70, July.
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  8. 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 555-60, August.
  9. 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. [Downloadable!]
  10. Evans, Lewis & Wells, Graeme, 1983. "An alternative approach to simulating var models," Economics Letters, Elsevier, vol. 12(1), pages 23-29. [Downloadable!] (restricted)
  11. 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. [Downloadable!] (restricted)
  12. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254. [Downloadable!] (restricted)
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  1. 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. [Downloadable!] (restricted)
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