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Blazing Saddles: the early and mainstream markets in the High-Tech product life cycle

Author

Listed:
  • Jacob Goldenberg

    (Hebrew University, Jerusalem)

  • Barak Libai

    (Tel Aviv University)

  • Eitan Muller

    (Tel Aviv University)

  • Renana Peres

    (Tel Aviv University)

Abstract

In this article, we showed the results of our study on the saddle phenomenon by an analytical model of two markets? early and mainstream? and the relationships between them. This model creates a growth pattern wherein a saddle can be discerned. We tested this model empirically on seven product categories, and in only one (cell phones) was a clear saddle not observed whose length was at least one year. Moreover, of the six remaining products, the partial communication break model of the dual market succeeded in explaining clearly the dropoff in sales in four categories: PCs, VCRs, video games, and cordless phones. Of the two remaining categories (CD players and answering machines), a dual market was observed, yet the model did not yield a dropoff in sales, but rather a clear delay in the adoption process.

Suggested Citation

  • Jacob Goldenberg & Barak Libai & Eitan Muller & Renana Peres, 2006. "Blazing Saddles: the early and mainstream markets in the High-Tech product life cycle," Israel Economic Review, Bank of Israel, vol. 4(2), pages 85-108.
  • Handle: RePEc:boi:isrerv:v:4:y:2006:i:2:p:85-108
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    References listed on IDEAS

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    1. Gatignon, Hubert & Robertson, Thomas S, 1985. "A Propositional Inventory for New Diffusion Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 11(4), pages 849-867, March.
    2. Dipak C. Jain & Eitan Muller & Naufel J. Vilcassim, 1999. "Pricing Patterns of Cellular Phones and Phonecalls: A Segment-Level Analysis," Management Science, INFORMS, vol. 45(2), pages 131-141, February.
    3. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    4. Peter N. Golder & Gerard J. Tellis, 1997. "Will It Every Fly? Modeling the Takeoff of Really New Consumer Durables," Marketing Science, INFORMS, vol. 16(3), pages 256-270.
    5. Jain, Dipak C & Rao, Ram C, 1990. "Effect of Price on the Demand for Durables: Modeling, Estimation, and Findings," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 163-170, April.
    6. V. Srinivasan & Charlotte H. Mason, 1986. "Technical Note—Nonlinear Least Squares Estimation of New Product Diffusion Models," Marketing Science, INFORMS, vol. 5(2), pages 169-178.
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    Cited by:

    1. Torben Klarl, 2014. "Knowledge diffusion and knowledge transfer revisited: two sides of the medal," Journal of Evolutionary Economics, Springer, vol. 24(4), pages 737-760, September.
    2. Gil Appel & Eitan Muller, 2021. "Adoption patterns over time: a replication," Marketing Letters, Springer, vol. 32(4), pages 499-511, December.
    3. Hong, Jungsik & Koo, Hoonyoung & Kim, Taegu, 2016. "Easy, reliable method for mid-term demand forecasting based on the Bass model: A hybrid approach of NLS and OLS," European Journal of Operational Research, Elsevier, vol. 248(2), pages 681-690.

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