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Capacity Expansion and Replacement in Growing Markets with Uncertain Technological Breakthroughs

Listed author(s):
  • Sampath Rajagopalan

    (Marshall School of Business, University of Southern California, Los Angeles, California 90089-1421)

  • Medini R. Singh

    (The Amos Tuck School of Business Administration, Dartmouth College, Hanover, New Hampshire 03755)

  • Thomas E. Morton

    (Graduate School of Industrial Administration, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

Registered author(s):

    The accelerated pace of technological change has led to rapid obsolescence of productive capacity in electronics and other industries. Managers must consider the impact of future technologies while making acquisition and replacement decisions in such environments. We consider a problem where a sequence of technological breakthroughs are anticipated but their magnitude and timing are uncertain. A firm, operating in such an environment, must decide how much capacity of the current technology to acquire to meet future demand growth. It must also determine whether to upgrade any of the older vintages. We formulate this problem and present some structural results. Using these results, we then develop a highly efficient regeneration point-based dynamic programming algorithm. The effectiveness of the proposed algorithm is illustrated through a computational study. The sensitivity of the first period decision to various parameters is also explored.

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    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 44 (1998)
    Issue (Month): 1 (January)
    Pages: 12-30

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    Handle: RePEc:inm:ormnsc:v:44:y:1998:i:1:p:12-30
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    1. Nair, Suresh K. & Hopp, Wallace J., 1992. "A model for equipment replacement due to technological obsolescence," European Journal of Operational Research, Elsevier, vol. 63(2), pages 207-221, December.
    2. Lieberman, Marvin B, 1987. "Market Growth, Economies of Scale, and Plant Size in the Chemical Processing Industries," Journal of Industrial Economics, Wiley Blackwell, vol. 36(2), pages 175-191, December.
    3. Klincewicz, John G. & Luss, Hanan, 1985. "Optimal timing decisions for the introduction of new technologies," European Journal of Operational Research, Elsevier, vol. 20(2), pages 211-220, May.
    4. Balcer, Yves & Lippman, Steven A., 1984. "Technological expectations and adoption of improved technology," Journal of Economic Theory, Elsevier, vol. 34(2), pages 292-318, December.
    5. Cainarca, Gian Carlo & Colombo, Massimo G. & Mariotti, Sergio, 1989. "An evolutionary pattern of innovation diffusion. The case of flexible automation," Research Policy, Elsevier, vol. 18(2), pages 59-86, April.
    6. Methe, David T., 1992. "The influence of technology and demand factors on firm size and industrial structure in the DRAM market -- 1973-1988," Research Policy, Elsevier, vol. 21(1), pages 13-25, February.
    7. John F. Muth, 1986. "Search Theory and the Manufacturing Progress Function," Management Science, INFORMS, vol. 32(8), pages 948-962, August.
    8. Karlson, Stephen H, 1986. "Adoption of Competing Inventions by United States Steel Producers," The Review of Economics and Statistics, MIT Press, vol. 68(3), pages 415-422, August.
    9. Antonelli, Cristiano, 1989. "The role of technological expectations in a mixed model of international diffusion of process innovations: The case of open-end spinning rotors," Research Policy, Elsevier, vol. 18(5), pages 273-288, October.
    10. Suresh K. Nair, 1995. "Modeling Strategic Investment Decisions Under Sequential Technological Change," Management Science, INFORMS, vol. 41(2), pages 282-297, February.
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