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Demystifying Disruption: A New Model for Understanding and Predicting Disruptive Technologies

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  • Ashish Sood

    (Goizueta School of Business, Emory University, Atlanta, Georgia 30322)

  • Gerard J. Tellis

    (Marshall School of Business, University of Southern California, Los Angeles, California 90089)

Abstract

The failure of firms in the face of technological change has been a topic of intense research and debate, spawning the theory (among others) of disruptive technologies. However, the theory suffers from circular definitions, inadequate empirical evidence, and lack of a predictive model. We develop a new schema to address these limitations. The schema generates seven hypotheses and a testable model relating to platform technologies. We test this model and hypotheses with data on 36 technologies from seven markets. Contrary to extant theory, technologies that adopt a lower attack ("potentially disruptive technologies") (1) are introduced as frequently by incumbents as by entrants, (2) are not cheaper than older technologies, and (3) rarely disrupt firms; and (4) both entrants and lower attacks significantly reduce the hazard of disruption. Moreover, technology disruption is not permanent because of multiple crossings in technology performance and numerous rival technologies coexisting without one disrupting the other. The proposed predictive model of disruption shows good out-of-sample predictive accuracy. We discuss the implications of these findings.

Suggested Citation

  • Ashish Sood & Gerard J. Tellis, 2011. "Demystifying Disruption: A New Model for Understanding and Predicting Disruptive Technologies," Marketing Science, INFORMS, vol. 30(2), pages 339-354, 03-04.
    • Handle: RePEc:inm:ormksc:v:30:y:2011:i:2:p:339-354
    DOI: 10.1287/mksc.1100.0617
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    1. Christensen, Clayton M. & Rosenbloom, Richard S., 1995. "Explaining the attacker's advantage: Technological paradigms, organizational dynamics, and the value network," Research Policy, Elsevier, vol. 24(2), pages 233-257, March.
    2. Mokyr, Joel, 1990. "Punctuated Equilibria and Technological Progress," American Economic Review, American Economic Association, vol. 80(2), pages 350-354, May.
    3. Zoltan J. Acs & David B. Audretsch, 2008. "Innovation in Large and Small Firms: An Empirical Analysis," Chapters, in: Entrepreneurship, Growth and Public Policy, chapter 1, pages 3-15, Edward Elgar Publishing.
    4. James M. Utterback & Happy J. Acee, 2005. "Disruptive Technologies: An Expanded View," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 9(01), pages 1-17.
    5. Frank T. Rothaermel & Charles W. L. Hill, 2005. "Technological Discontinuities and Complementary Assets: A Longitudinal Study of Industry and Firm Performance," Organization Science, INFORMS, vol. 16(1), pages 52-70, February.
    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.
    7. Andrew A. King & Christopher L. Tucci, 2002. "Incumbent Entry into New Market Niches: The Role of Experience and Managerial Choice in the Creation of Dynamic Capabilities," Management Science, INFORMS, vol. 48(2), pages 171-186, February.
    8. Rothaermel, Frank T., 2001. "Complementary assets, strategic alliances, and the incumbent's advantage: an empirical study of industry and firm effects in the biopharmaceutical industry," Research Policy, Elsevier, vol. 30(8), pages 1235-1251, October.
    9. Mary Tripsas, 1997. "Unraveling The Process Of Creative Destruction: Complementary Assets And Incumbent Survival In The Typesetter Industry," Strategic Management Journal, Wiley Blackwell, vol. 18(S1), pages 119-142, July.
    10. Pankaj Ghemawat, 1991. "Market Incumbency and Technological Inertia," Marketing Science, INFORMS, vol. 10(2), pages 161-171.
    11. Ashish Sood & Gerard J. Tellis, 2009. "Do Innovations Really Pay Off? Total Stock Market Returns to Innovation," Marketing Science, INFORMS, vol. 28(3), pages 442-456, 05-06.
    12. Ron Adner & Peter Zemsky, 2005. "Disruptive Technologies and the Emergence of Competition," RAND Journal of Economics, The RAND Corporation, vol. 36(2), pages 229-254, Summer.
    13. David A. Schweidel & Peter S. Fader & Eric T. Bradlow, 2008. "A Bivariate Timing Model of Customer Acquisition and Retention," Marketing Science, INFORMS, vol. 27(5), pages 829-843, 09-10.
    14. Levinthal, Daniel A, 1998. "The Slow Pace of Rapid Technological Change: Gradualism and Punctuation in Technological Change," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 7(2), pages 217-247, June.
    15. Dosi, Giovanni, 1993. "Technological paradigms and technological trajectories : A suggested interpretation of the determinants and directions of technical change," Research Policy, Elsevier, vol. 22(2), pages 102-103, April.
    16. Rebecca Henderson, 1993. "Underinvestment and Incompetence as Responses to Radical Innovation: Evidence from the Photolithographic Alignment Equipment Industry," RAND Journal of Economics, The RAND Corporation, vol. 24(2), pages 248-270, Summer.
    17. Ashish Sood & Gareth M. James & Gerard J. Tellis, 2009. "Functional Regression: A New Model for Predicting Market Penetration of New Products," Marketing Science, INFORMS, vol. 28(1), pages 36-51, 01-02.
    18. Lillard, Lee A., 1993. "Simultaneous equations for hazards : Marriage duration and fertility timing," Journal of Econometrics, Elsevier, vol. 56(1-2), pages 189-217, March.
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