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The Adoption of Multiple Dependent Technologies

Author

Listed:
  • Soo-Haeng Cho

    (Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

  • Kevin F. McCardle

    (Anderson School of Management, University of California, Los Angeles, California 90095)

Abstract

A firm often makes an adoption decision regarding an improvement of one technology depending on changes in other technologies. For example, a manufacturer with a serial production line considers jointly upgrading multiple machines, or a firm producing an assembled product considers improving several components simultaneously. Economies or diseconomies of scope in the fixed cost of adoption when multiple improvements are undertaken at the same time generate an economic dependence among the technological innovations. Although the literature on technological innovations has attributed slow adoption mainly to uncertainties outside the firm, this paper shows that the economic dependence that inherently defines cost relationships inside the firm can significantly influence the timing of adoption. Furthermore, this impact is not unidirectional: economic dependence can either expedite or delay the adoption of an improved technology.

Suggested Citation

  • Soo-Haeng Cho & Kevin F. McCardle, 2009. "The Adoption of Multiple Dependent Technologies," Operations Research, INFORMS, vol. 57(1), pages 157-169, February.
    • Handle: RePEc:inm:oropre:v:57:y:2009:i:1:p:157-169
    DOI: 10.1287/opre.1080.0534
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    References listed on IDEAS

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    Cited by:

    1. Wenjie Tang & Tong Wang & Wenxin Xu, 2022. "Sooner or Later? The Role of Adoption Timing in New Technology Introduction," Production and Operations Management, Production and Operations Management Society, vol. 31(4), pages 1663-1678, April.
    2. Hagspiel, Verena & Huisman, Kuno J.M. & Kort, Peter M. & Lavrutich, Maria N. & Nunes, Cláudia & Pimentel, Rita, 2020. "Technology adoption in a declining market," European Journal of Operational Research, Elsevier, vol. 285(1), pages 380-392.
    3. James E. Smith & Canan Ulu, 2017. "Risk Aversion, Information Acquisition, and Technology Adoption," Operations Research, INFORMS, vol. 65(4), pages 1011-1028, August.
    4. Brozynski, Max T. & Leibowicz, Benjamin D., 2020. "Markov models of policy support for technology transitions," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1052-1069.
    5. Hagspiel, V. & Huisman, Kuno & Kort, Peter M. & Nunes, Claudia & Pimentel, Rita, 2018. "Product Innovation of an Incumbent Firm : A Dynamic Analysis," Discussion Paper 2018-048, Tilburg University, Center for Economic Research.
    6. H. Dharma Kwon, 2010. "Invest or Exit? Optimal Decisions in the Face of a Declining Profit Stream," Operations Research, INFORMS, vol. 58(3), pages 638-649, June.
    7. James E. Smith & Canan Ulu, 2012. "Technology Adoption with Uncertain Future Costs and Quality," Operations Research, INFORMS, vol. 60(2), pages 262-274, April.
    8. Hagspiel, Verena & Huisman, Kuno J.M. & Nunes, Clàudia, 2015. "Optimal technology adoption when the arrival rate of new technologies changes," European Journal of Operational Research, Elsevier, vol. 243(3), pages 897-911.

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