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Modeling Strategic Investment Decisions Under Sequential Technological Change

Author

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  • Suresh K. Nair

    (Department of Operations and Information Management, School of Business Administration, U41-IM, University of Connecticut, Storrs, Connecticut 06269-0241)

Abstract

Strategic decisions to invest in new equipment are critical not only because of the large initial capital costs incurred but even more importantly because they affect future unit production costs, revenues, and the ability of the firm to perform operations that were not possible earlier. Thus these decisions determine the very competitiveness of the firm. Further, decisions regarding the choice of technology are very expensive to correct if incorrect decisions are identified. These decisions have become increasingly urgent and complex because the state of the art in technology is changing rapidly. However, many models available for evaluating these decisions are either too complex and inefficient or too restrictive in the number, types, and the way appearance of future technologies is modeled. This research attempts to relax some of these restrictions using forecast horizon procedures to model capital investment decisions where any number of technologies may appear in the future with purchase costs and revenues that may vary over time. The appearance of these future technologies are considered uncertain with probabilities that may also vary with time. However, we assume that the order in which they appear is sequential, much like the different generations of microchips for microcomputers. We develop a new approach using nonunique terminal rewards to solve a dynamic programming model of the problem by introducing "converse" difference functions and present an algorithm that is both simple and efficient. Despite the increase in state space from the use of "converse" functions, we show that the computational burden of the algorithm does not increase. Numerical examples are given to illustrate our algorithm. Sensitivity of the optimal decision to changes in probabilities, costs, and revenues are also discussed.

Suggested Citation

  • Suresh K. Nair, 1995. "Modeling Strategic Investment Decisions Under Sequential Technological Change," Management Science, INFORMS, vol. 41(2), pages 282-297, February.
    • Handle: RePEc:inm:ormnsc:v:41:y:1995:i:2:p:282-297
    DOI: 10.1287/mnsc.41.2.282
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    Citations

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    Cited by:

    1. Rahman, Atiqur & Loulou, Richard, 2001. "Technology acquisition with technological progress: effects of expectations, rivalry and uncertainty," European Journal of Operational Research, Elsevier, vol. 129(1), pages 159-185, February.
    2. Huisman, Kuno J. M. & Kort, Peter M., 2003. "Strategic investment in technological innovations," European Journal of Operational Research, Elsevier, vol. 144(1), pages 209-223, January.
    3. Sampath Rajagopalan & Medini R. Singh & Thomas E. Morton, 1998. "Capacity Expansion and Replacement in Growing Markets with Uncertain Technological Breakthroughs," Management Science, INFORMS, vol. 44(1), pages 12-30, January.
    4. Nguyen, T.P.K. & Castanier, Bruno & Yeung, Thomas G., 2014. "Maintaining a system subject to uncertain technological evolution," Reliability Engineering and System Safety, Elsevier, vol. 128(C), pages 56-65.
    5. Liu, Heng & Özer, Özalp, 2009. "Managing a product family under stochastic technological changes," International Journal of Production Economics, Elsevier, vol. 122(2), pages 567-580, December.
    6. Gabriela Prelipcean & Mircea Boscoianu, 2012. "Aspects Regarding the Impact of the "Rabla" Program and the "Casa Verde" Program on the Ecological Consumption in Romania," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 14(31), pages 25-37, February.
    7. Gilvan C. Souza & Barry L. Bayus & Harvey M. Wagner, 2004. "New-Product Strategy and Industry Clockspeed," Management Science, INFORMS, vol. 50(4), pages 537-549, April.
    8. Unay-Gailhard, İlkay & Bojnec, Štefan, 2016. "Sustainable participation behaviour in agri-environmental measures," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 138, pages 47-58.
    9. Souza, Gilvan C., 2004. "Product introduction decisions in a duopoly," European Journal of Operational Research, Elsevier, vol. 152(3), pages 745-757, February.
    10. Asadi, Amin & Nurre Pinkley, Sarah, 2021. "A stochastic scheduling, allocation, and inventory replenishment problem for battery swap stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).
    11. Margaret S. Trench & Shane P. Pederson & Edward T. Lau & Lizhi Ma & Hui Wang & Suresh K. Nair, 2003. "Managing Credit Lines and Prices for Bank One Credit Cards," Interfaces, INFORMS, vol. 33(5), pages 4-21, October.
    12. Susan H. Xu & Zhaolin Li, 2007. "Managing a Single-Product Assemble-to-Order System with Technology Innovations," Management Science, INFORMS, vol. 53(9), pages 1467-1485, September.
    13. Nguyen, T.P. Khanh & Yeung, Thomas G. & Castanier, Bruno, 2013. "Optimal maintenance and replacement decisions under technological change with consideration of spare parts inventories," International Journal of Production Economics, Elsevier, vol. 143(2), pages 472-477.
    14. Mellal, Mohamed Arezki, 2020. "Obsolescence – A review of the literature," Technology in Society, Elsevier, vol. 63(C).
    15. Suresh Chand & Vernon Ning Hsu & Suresh Sethi, 2002. "Forecast, Solution, and Rolling Horizons in Operations Management Problems: A Classified Bibliography," Manufacturing & Service Operations Management, INFORMS, vol. 4(1), pages 25-43, September.
    16. Soo-Haeng Cho & Kevin F. McCardle, 2009. "The Adoption of Multiple Dependent Technologies," Operations Research, INFORMS, vol. 57(1), pages 157-169, February.
    17. Öner, K.B. & Kiesmüller, G.P. & van Houtum, G.J., 2015. "On the upgrading policy after the redesign of a component for reliability improvement," European Journal of Operational Research, Elsevier, vol. 244(3), pages 867-880.

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