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Innovations and technological comebacks

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  • Renaud Foucart

    (HU Berlin - Humboldt-Universität zu Berlin = Humboldt University of Berlin = Université Humboldt de Berlin)

  • Cheng Wan

    (Shanghai University of Finance and Economics)

  • Shidong Wang

    (University of Oxford)

Abstract

Motivated by the comeback of the vinyl, we explore the idea that the success of a third-generation technology (digital music) can have adverse effects on the second generation (CD) but positive effects on the first one (vinyl). This phenomenon arises in a market if the process of innovation is not transitive. In particular, we identify a condition such that the second generation completely substitutes the first one, the third generation completely substitutes the second one, but the first and the third generations have enough complementarities to coexist. Beyond the case of music industry, our model has implications on product positioning and product design.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Renaud Foucart & Cheng Wan & Shidong Wang, 2018. "Innovations and technological comebacks," Post-Print hal-02887611, HAL.
  • Handle: RePEc:hal:journl:hal-02887611
    DOI: 10.1016/j.ijresmar.2017.11.002
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    1. Michalek, Jeremy J. & Ebbes, Peter & Adigüzel, Feray & Feinberg, Fred M. & Papalambros, Panos Y., 2011. "Enhancing marketing with engineering: Optimal product line design for heterogeneous markets," International Journal of Research in Marketing, Elsevier, vol. 28(1), pages 1-12.
    2. Justin P. Johnson & David P. Myatt, 2006. "On the Simple Economics of Advertising, Marketing, and Product Design," American Economic Review, American Economic Association, vol. 96(3), pages 756-784, June.
    3. H. Peyton Young, 2009. "Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning," American Economic Review, American Economic Association, vol. 99(5), pages 1899-1924, December.
    4. Guidolin, Mariangela & Guseo, Renato, 2015. "Technological change in the U.S. music industry: Within-product, cross-product and churn effects between competing blockbusters," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 35-46.
    5. Geroski, P. A., 2000. "Models of technology diffusion," Research Policy, Elsevier, vol. 29(4-5), pages 603-625, April.
    6. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    7. Wlömert, Nils & Papies, Dominik, 2016. "On-demand streaming services and music industry revenues — Insights from Spotify's market entry," International Journal of Research in Marketing, Elsevier, vol. 33(2), pages 314-327.
    8. Moldovan, Sarit & Goldenberg, Jacob & Chattopadhyay, Amitava, 2011. "The different roles of product originality and usefulness in generating word-of-mouth," International Journal of Research in Marketing, Elsevier, vol. 28(2), pages 109-119.
    9. Paul E. Green & Abba M. Krieger, 1992. "An Application of a Product Positioning Model to Pharmaceutical Products," Marketing Science, INFORMS, vol. 11(2), pages 117-132.
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    2. Martin Heinberg & Constantine S. Katsikeas & H. Erkan Ozkaya & Markus Taube, 2020. "How nostalgic brand positioning shapes brand equity: differences between emerging and developed markets," Journal of the Academy of Marketing Science, Springer, vol. 48(5), pages 869-890, September.

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