IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v28y2009i5p846-867.html
   My bibliography  Save this article

A Dynamic Model of Consumer Replacement Cycles in the PC Processor Industry

Author

Listed:
  • Brett R. Gordon

    () (Columbia Business School, New York, New York 10027)

Abstract

As high-tech markets mature, replacement purchases inevitably become the dominant proportion of sales. Despite the clear importance of product replacement, little empirical work examines the separate roles of adoption and replacement. A consumer's replacement decision is dynamic and driven by product obsolescence because these markets frequently undergo rapid improvements in quality and falling prices. The goal of this paper is to construct a model of consumer product replacement and to investigate the implications of replacement cycles for firms. To this end, I develop and estimate a dynamic model of consumer demand that explicitly accounts for the replacement decision when consumers are uncertain about future price and quality. Using a unique data set from the PC processor industry, I show how to combine aggregate data on sales and product ownership to infer replacement behavior. The results reveal substantial variation in replacement behavior over time, and this heterogeneity provides an opportunity for managers to tailor their product introduction and pricing strategies to target the consumers of a particular segment that are most likely to replace in the near future.

Suggested Citation

  • Brett R. Gordon, 2009. "A Dynamic Model of Consumer Replacement Cycles in the PC Processor Industry," Marketing Science, INFORMS, vol. 28(5), pages 846-867, 09-10.
  • Handle: RePEc:inm:ormksc:v:28:y:2009:i:5:p:846-867
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.1080.0448
    Download Restriction: no

    References listed on IDEAS

    as
    1. Gautam Gowrisankaran & Marc Rysman, 2012. "Dynamics of Consumer Demand for New Durable Goods," Journal of Political Economy, University of Chicago Press, vol. 120(6), pages 1173-1219.
    2. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
    3. John A. Norton & Frank M. Bass, 1987. "A Diffusion Theory Model of Adoption and Substitution for Successive Generations of High-Technology Products," Management Science, INFORMS, vol. 33(9), pages 1069-1086, September.
    4. Igal Hendel & Aviv Nevo, 2006. "Measuring the Implications of Sales and Consumer Inventory Behavior," Econometrica, Econometric Society, vol. 74(6), pages 1637-1673, November.
    5. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    6. Newey, Whitney K & West, Kenneth D, 1987. "Hypothesis Testing with Efficient Method of Moments Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(3), pages 777-787, October.
    7. Nitin Mehta & Surendra Rajiv & Kannan Srinivasan, 2004. "Role of Forgetting in Memory-Based Choice Decisions: A Structural Model," Quantitative Marketing and Economics (QME), Springer, vol. 2(2), pages 107-140, June.
    8. Dan Horsky, 1990. "A Diffusion Model Incorporating Product Benefits, Price, Income and Information," Marketing Science, INFORMS, vol. 9(4), pages 342-365.
    9. Harikesh Nair, 2007. "Intertemporal price discrimination with forward-looking consumers: Application to the US market for console video-games," Quantitative Marketing and Economics (QME), Springer, vol. 5(3), pages 239-292, September.
    10. Rabik Ar Chatterjee & Jehoshua Eliashberg, 1990. "The Innovation Diffusion Process in a Heterogeneous Population: A Micromodeling Approach," Management Science, INFORMS, vol. 36(9), pages 1057-1079, September.
    11. Jerome Adda & Russell Cooper, 2000. "The Dynamics of Car Sales: A Discrete Choice Approach," NBER Working Papers 7785, National Bureau of Economic Research, Inc.
    12. Baohong Sun, 2005. "Promotion Effect on Endogenous Consumption," Marketing Science, INFORMS, vol. 24(3), pages 430-443, July.
    13. Tülin Erdem & Susumu Imai & Michael Keane, 2003. "Brand and Quantity Choice Dynamics Under Price Uncertainty," Quantitative Marketing and Economics (QME), Springer, vol. 1(1), pages 5-64, March.
    14. Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
    15. John Rust, 1997. "Using Randomization to Break the Curse of Dimensionality," Econometrica, Econometric Society, vol. 65(3), pages 487-516, May.
    16. Susanna Esteban & Matthew Shum, 2007. "Durable-goods oligopoly with secondary markets: the case of automobiles," RAND Journal of Economics, RAND Corporation, vol. 38(2), pages 332-354, June.
    17. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    18. Minjae Song, 2007. "Measuring consumerwelfareinthe CPU market: anapplication of the pure-characteristics demand model," RAND Journal of Economics, RAND Corporation, vol. 38(2), pages 429-446, June.
    19. Jeffrey T. Prince, 2008. "Repeat Purchase amid Rapid Quality Improvement: Structural Estimation of Demand for Personal Computers," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 17(1), pages 1-33, March.
    20. Inseong Song & Pradeep Chintagunta, 2003. "A Micromodel of New Product Adoption with Heterogeneous and Forward-Looking Consumers: Application to the Digital Camera Category," Quantitative Marketing and Economics (QME), Springer, vol. 1(4), pages 371-407, December.
    21. Füsun Gönül & Kannan Srinivasan, 1996. "Estimating the Impact of Consumer Expectations of Coupons on Purchase Behavior: A Dynamic Structural Model," Marketing Science, INFORMS, vol. 15(3), pages 262-279.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Stephen Ryan & Catherine Tucker, 2012. "Heterogeneity and the dynamics of technology adoption," Quantitative Marketing and Economics (QME), Springer, vol. 10(1), pages 63-109, March.
    2. Prince, Jeffrey T., 2009. "How do households choose quality and time to replacement for a rapidly improving durable good?," International Journal of Industrial Organization, Elsevier, vol. 27(2), pages 302-311, March.
    3. repec:eee:ijrema:v:30:y:2013:i:1:p:19-35 is not listed on IDEAS
    4. Wesley R. Hartmann & Harikesh S. Nair, 2010. "Retail Competition and the Dynamics of Demand for Tied Goods," Marketing Science, INFORMS, vol. 29(2), pages 366-386, 03-04.
    5. Gautam Gowrisankaran & Marc Rysman, 2012. "Dynamics of Consumer Demand for New Durable Goods," Journal of Political Economy, University of Chicago Press, vol. 120(6), pages 1173-1219.
    6. Pradeep K. Chintagunta & Harikesh S. Nair, 2011. "Structural Workshop Paper --Discrete-Choice Models of Consumer Demand in Marketing," Marketing Science, INFORMS, vol. 30(6), pages 977-996, November.
    7. Andrew Ching & Masakazu Ishihara, 2014. "Dynamic Demand for New and Used Durable Goods without Physical Depreciation: The Case of Japanese Video Games," 2014 Meeting Papers 782, Society for Economic Dynamics.
    8. S. Sriram & Pradeep K. Chintagunta & Manoj K. Agarwal, 2010. "Investigating Consumer Purchase Behavior in Related Technology Product Categories," Marketing Science, INFORMS, vol. 29(2), pages 291-314, 03-04.
    9. Bryan Bollinger, 2015. "Green technology adoption: An empirical study of the Southern California garment cleaning industry," Quantitative Marketing and Economics (QME), Springer, vol. 13(4), pages 319-358, December.
    10. Qi, Lian & Sawhill, James, 2014. "How durable should durable products be made under different scenarios of technological advance?," International Journal of Production Economics, Elsevier, vol. 156(C), pages 75-82.
    11. repec:kap:qmktec:v:15:y:2017:i:3:d:10.1007_s11129-017-9186-9 is not listed on IDEAS
    12. Hartmann, Wesley R. & Nair, Harikesh S., 2007. "Retail Competition and the Dynamics of Consumer Demand for Tied Goods," Research Papers 1990, Stanford University, Graduate School of Business.
    13. Unni Pillai, 2013. "A Model of Technological Progress in the Microprocessor Industry," Journal of Industrial Economics, Wiley Blackwell, vol. 61(4), pages 877-912, December.
    14. Jean-Pierre H. Dubé & Günter J. Hitsch & Pradeep K. Chintagunta, 2010. "Tipping and Concentration in Markets with Indirect Network Effects," Marketing Science, INFORMS, vol. 29(2), pages 216-249, 03-04.
    15. Tat Chan & Ravi Dhar & William Putsis, 2015. "The Technological Conundrum: How Rapidly Advancing Technology Can Lead to Commoditization," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(2), pages 119-132, June.
    16. Eric W. Bond & Toshiaki Iizuka, 2014. "Durable Goods Price Cycles: Theory And Evidence From The Textbook Market," Economic Inquiry, Western Economic Association International, vol. 52(2), pages 518-538, April.
    17. Pasquale Schiraldi, 2011. "Automobile replacement: a dynamic structural approach," RAND Journal of Economics, RAND Corporation, vol. 42(2), pages 266-291, June.
    18. Tilson, Vera & Zheng, Xiaobo, 2014. "Monopoly production and pricing of finitely durable goods with strategic consumers׳ fluctuating willingness to pay," International Journal of Production Economics, Elsevier, vol. 154(C), pages 217-232.
    19. Copeland, Adam & Shapiro, Adam Hale, 2013. "Price Setting in an Innovative Market," Working Paper Series 2013-04, Federal Reserve Bank of San Francisco.
    20. repec:gam:jsusta:v:9:y:2017:i:6:p:1038-:d:101654 is not listed on IDEAS
    21. Bart Bronnenberg & Jean Dubé & Carl Mela & Paulo Albuquerque & Tulin Erdem & Brett Gordon & Dominique Hanssens & Guenter Hitsch & Han Hong & Baohong Sun, 2008. "Measuring long-run marketing effects and their implications for long-run marketing decisions," Marketing Letters, Springer, vol. 19(3), pages 367-382, December.
    22. repec:eee:joinma:v:25:y:2011:i:2:p:95-109 is not listed on IDEAS
    23. Riikonen, Antti & Smura, Timo & Töyli, Juuso, 2016. "The effects of price, popularity, and technological sophistication on mobile handset replacement and unit lifetime," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 313-323.
    24. Pinar Karaca-Mandic, 2011. "Role of complementarities in technology adoption: The case of DVD players," Quantitative Marketing and Economics (QME), Springer, vol. 9(2), pages 179-210, June.

    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:28:y:2009:i:5:p:846-867. 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: (Mirko Janc). General contact details of provider: http://edirc.repec.org/data/inforea.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.