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A Micromodel of New Product Adoption with Heterogeneous and Forward-Looking Consumers: Application to the Digital Camera Category


  • Inseong Song


  • Pradeep Chintagunta



We develop an empirical model for the adoption process of a new durable product that accounts for consumer heterogeneity as well as consumers” forward-looking behavior. Accounting for heterogeneity is important for two reasons. As the mix of consumers with different preferences and price sensitivities could change over time, firms need to update their marketing strategies. Further, it allows for a variety of shapes for the aggregate adoption process over time. As prices for durable and technology products fall over time with firms continually introducing enhanced products, consumers may anticipate these prices and improvements and delay their purchases in the product category. Forward-looking consumers optimize purchase timing by trading off their utilities from buying the product and their expectations on future prices, quality levels, and brand availability. Such forward-looking behavior will result in price dynamics in the marketplace as price changes today influence future purchases. And it results in different shapes of the new product sales pattern over time by influencing the time to take-off. We show how the parameters of our model can be estimated using aggregate data on the sales, prices, and attributes of brands in a product category. We apply our model to market data from the digital camera category. Our data are consistent with the presence of both heterogeneity and forward looking behavior among consumers. At the product category level, we are able to decompose the effects of the entry of Sony into primary demand expansion and switching from other brands. At the brand level, we find that there exist several segments in the market with different preferences for the brands and different price sensitivities leading to differences in adoption timing and brand choice across segments. For a given brand, we show how the changing customer mix over time has implications for that brand”s pricing strategies. We characterize how price effects vary across brands and over time and how price changes in a given time period influence sales in subsequent periods. Model comparison and validation results are also provided. Copyright Kluwer Academic Publishers 2003

Suggested Citation

  • 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.
  • Handle: RePEc:kap:qmktec:v:1:y:2003:i:4:p:371-407 DOI: 10.1023/B:QMEC.0000004843.41279.f3

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    1. 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.
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    3. Adam Copeland, 2008. "The Dynamics of Automobile Expenditures," 2008 Meeting Papers 852, Society for Economic Dynamics.
    4. Günter J. Hitsch, 2006. "An Empirical Model of Optimal Dynamic Product Launch and Exit Under Demand Uncertainty," Marketing Science, INFORMS, vol. 25(1), pages 25-50, 01-02.
    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. Nektarios Oraiopoulos & Mark E. Ferguson & L. Beril Toktay, 2012. "Relicensing as a Secondary Market Strategy," Management Science, INFORMS, vol. 58(5), pages 1022-1037, May.
    7. 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.
    8. 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.
    9. Goodwin, Paul & Meeran, Sheik & Dyussekeneva, Karima, 2014. "The challenges of pre-launch forecasting of adoption time series for new durable products," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1082-1097.
    10. Sam K. Hui & Jehoshua Eliashberg & Edward I. George, 2008. "Modeling DVD Preorder and Sales: An Optimal Stopping Approach," Marketing Science, INFORMS, vol. 27(6), pages 1097-1110, 11-12.
    11. 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.
    12. Andrew Ching & Susumu Imai & Masakazu Ishihara & Neelam Jain, 2012. "A practitioner’s guide to Bayesian estimation of discrete choice dynamic programming models," Quantitative Marketing and Economics (QME), Springer, vol. 10(2), pages 151-196, June.
    13. Adam J. Mersereau & Dan Zhang, 2012. "Markdown Pricing with Unknown Fraction of Strategic Customers," Manufacturing & Service Operations Management, INFORMS, vol. 14(3), pages 355-370, July.
    14. 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.
    15. Min Ding & Jehoshua Eliashberg, 2008. "A Dynamic Competitive Forecasting Model Incorporating Dyadic Decision Making," Management Science, INFORMS, vol. 54(4), pages 820-834, April.
    16. Sam K. Hui & Peter S. Fader & Eric T. Bradlow, 2009. "Path Data in Marketing: An Integrative Framework and Prospectus for Model Building," Marketing Science, INFORMS, vol. 28(2), pages 320-335, 03-04.
    17. Huang, Yufeng, 2015. "Empirical analysis of consumer behavior," Other publications TiSEM 9cc96a79-43d7-436d-87d3-3, Tilburg University, School of Economics and Management.
    18. Pradeep Chintagunta & Tülin Erdem & Peter E. Rossi & Michel Wedel, 2006. "Structural Modeling in Marketing: Review and Assessment," Marketing Science, INFORMS, vol. 25(6), pages 604-616, 11-12.
    19. Jean-Pierre Dubé & Günter Hitsch & Pranav Jindal, 2014. "The Joint identification of utility and discount functions from stated choice data: An application to durable goods adoption," Quantitative Marketing and Economics (QME), Springer, vol. 12(4), pages 331-377, December.
    20. S. Sriram & Pradeep K. Chintagunta & Ramya Neelamegham, 2006. "Effects of Brand Preference, Product Attributes, and Marketing Mix Variables in Technology Product Markets," Marketing Science, INFORMS, vol. 25(5), pages 440-456, September.
    21. Gonca P. Soysal & Lakshman Krishnamurthi, 2012. "Demand Dynamics in the Seasonal Goods Industry: An Empirical Analysis," Marketing Science, INFORMS, vol. 31(2), pages 293-316, March.


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