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Investigating Consumer Purchase Behavior in Related Technology Product Categories

Author

Listed:
  • S. Sriram

    (Ross School of Business, University of Michigan, Ann Arbor, Michigan 48109)

  • Pradeep K. Chintagunta

    (Booth School of Business, University of Chicago, Chicago, Illinois 60637)

  • Manoj K. Agarwal

    (School of Management, Binghamton University, State University of New York, Binghamton, New York 13902)

Abstract

We present a framework of durable goods purchasing behavior in related technology product categories that incorporates the following aspects unique to technology product purchases. First, it accounts for consumers' anticipation of declining prices (or increasing quality) over time. Second, the durable nature of technology products implies that even if two categories are related as complements, consumers may stagger their purchases over several periods. Third, the forward-looking consumer decision process, as well as the durable nature of technology products, implies that a consumer's purchase in one category will depend on the anticipated price and quality trajectories of all categories. As a potential aid to future researchers, we also lay out the data requirements for empirically estimating the parameters of our model and the consequences of not having various elements of these data on our ability to estimate the parameters. The data available for our empirical analysis are household-level information on -level first-time decisions in three categories—personal computers, digital cameras, and printers. Our results reveal a strong complementary relationship between the three categories. Policy simulations based on a temporary price decrease in any one category provide interesting insights into how consumers would modify their adoption behavior over time and also across categories as a consequence of the price decrease.

Suggested Citation

  • 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.
  • Handle: RePEc:inm:ormksc:v:29:y:2010:i:2:p:291-314
    DOI: 10.1287/mksc.1090.0506
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    12. Reinhardt, Ronny & Gurtner, Sebastian, 2018. "The overlooked role of embeddedness in disruptive innovation theory," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 268-283.
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    16. Ma, Yu & Seetharaman, P.B. & Narasimhan, Chakravarthi, 2012. "Modeling Dependencies in Brand Choice Outcomes Across Complementary Categories," Journal of Retailing, Elsevier, vol. 88(1), pages 47-62.
    17. V. Kumar & S. Sriram & Anita Luo & Pradeep K. Chintagunta, 2011. "Assessing the Effect of Marketing Investments in a Business Marketing Context," Marketing Science, INFORMS, vol. 30(5), pages 924-940, September.
    18. Reinhardt, Ronny & Gurtner, Sebastian, 2015. "Differences between early adopters of disruptive and sustaining innovations," Journal of Business Research, Elsevier, vol. 68(1), pages 137-145.
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    22. Gal OEstreicher-Singer & Barak Libai, 2011. "Assessing Value in Product Networks," Working Papers 11-29, NET Institute, revised Sep 2011.
    23. Davis, Robert & Lang, Bodo, 2012. "Modeling the effect of self-efficacy on game usage and purchase behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 19(1), pages 67-77.

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