IDEAS home Printed from https://ideas.repec.org/a/boi/isrerv/v4y2006i2p85-108.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://boiwebrepec.azurefd.net/RePEc/boi/isrerv/IsER_4_2006_2_085-108.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    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. 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.
    4. 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.
    5. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    6. 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.
    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. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. John Hauser & Gerard J. Tellis & Abbie Griffin, 2006. "Research on Innovation: A Review and Agenda for," Marketing Science, INFORMS, vol. 25(6), pages 687-717, 11-12.
    2. Krishnan, Trichy V. & Feng, Shanfei & Jain, Dipak C., 2023. "Peak sales time prediction in new product sales: Can a product manager rely on it?," Journal of Business Research, Elsevier, vol. 165(C).
    3. Kim, Namwoon & Srivastava, Rajendra K., 2007. "Modeling cross-price effects on inter-category dynamics: The case of three computing platforms," Omega, Elsevier, vol. 35(3), pages 290-301, June.
    4. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - Leibniz Information Centre for Economics.
    5. Venkatesan, Rajkumar & Kumar, V., 2002. "A genetic algorithms approach to growth phase forecasting of wireless subscribers," International Journal of Forecasting, Elsevier, vol. 18(4), pages 625-646.
    6. Namwoon Kim & Dae Ryun Chang & Allan D. Shocker, 2000. "Modeling Intercategory and Generational Dynamics for A Growing Information Technology Industry," Management Science, INFORMS, vol. 46(4), pages 496-512, April.
    7. Tellis, Gerard J. & Chandrasekaran, Deepa, 2010. "Extent and impact of response biases in cross-national survey research," International Journal of Research in Marketing, Elsevier, vol. 27(4), pages 329-341.
    8. Rzayev, Khaladdin & Sakkas, Athanasios & Urquhart, Andrew, 2025. "An adoption model of cryptocurrencies," European Journal of Operational Research, Elsevier, vol. 323(1), pages 253-266.
    9. Collins, Matthew & Curtis, John, 2017. "Advertising and investment spillovers in the diffusion of residential energy efficiency renovations," Papers WP569, Economic and Social Research Institute (ESRI).
    10. Shakshi Singhal & Yasmeen Bano & Ompal Singh, 2024. "Demand forecasting of technological products considering re-purchasing and dynamic pricing: a modified diffusion model," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(5), pages 1981-1998, May.
    11. Shun-Chen Niu, 2006. "A Piecewise-Diffusion Model of New-Product Demands," Operations Research, INFORMS, vol. 54(4), pages 678-695, August.
    12. Elmar Kiesling & Markus Günther & Christian Stummer & Lea Wakolbinger, 2012. "Agent-based simulation of innovation diffusion: a review," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(2), pages 183-230, June.
    13. Shiva & Neetu Gupta & Anu G. Aggarwal, 2024. "A generalized product adoption model under random marketing conditions," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(10), pages 4897-4904, October.
    14. Bacha, Radia & Gasmi, Farid, 2022. "The broadband diffusion process and its determinants in Algeria: A simultaneous estimation," TSE Working Papers 22-1309, Toulouse School of Economics (TSE).
    15. Theoharakis, Vasilis & Vakratsas, Demetrios & Wong, Veronica, 2007. "Market-level information and the diffusion of competing technologies: An exploratory analysis of the LAN industry," Research Policy, Elsevier, vol. 36(5), pages 742-757, June.
    16. Singhal, Shakshi & Anand, Adarsh & Singh, Ompal, 2020. "Studying dynamic market size-based adoption modeling & product diffusion under stochastic environment," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    17. Jinah Yang & Daiki Min & Jeenyoung Kim, 2020. "The Use of Big Data and Its Effects in a Diffusion Forecasting Model for Korean Reverse Mortgage Subscribers," Sustainability, MDPI, vol. 12(3), pages 1-17, January.
    18. Prins, Remco & Verhoef, Peter C. & Franses, Philip Hans, 2009. "The impact of adoption timing on new service usage and early disadoption," International Journal of Research in Marketing, Elsevier, vol. 26(4), pages 304-313.
    19. Mesak, Hani I. & Bari, Abdullahel & Babin, Barry J. & Birou, Laura M. & Jurkus, Anthony, 2011. "Optimum advertising policy over time for subscriber service innovations in the presence of service cost learning and customers' disadoption," European Journal of Operational Research, Elsevier, vol. 211(3), pages 642-649, June.
    20. Y. Li & C.J.M. Kool & P.J. Engelen, 2016. "Hydrogen-Fuel Infrastructure Investment with Endogenous Demand: A Real Options Approach," Working Papers 16-12, Utrecht School of Economics.

    More about this item

    Statistics

    Access and download statistics

    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:boi:isrerv:v:4:y:2006:i:2:p:85-108. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Yossi Yakhin (email available below). General contact details of provider: https://edirc.repec.org/data/boigvil.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.