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When and how much to invest? Investment and capacity choice under product life cycle uncertainty

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  • Lukas, Elmar
  • Spengler, Thomas Stefan
  • Kupfer, Stefan
  • Kieckhäfer, Karsten

Abstract

While empirical research indicates that innovations typically follow a product life cycle that is subject to uncertainty in many industries, endless cash flow growth is still at the heart of most papers guiding investment decisions under uncertainty. This paper studies the effect of an uncertain technological life cycle on the decision to invest in new product introduction, taking into account the combined effects of flexible investment timing and optimal capacity choice. Based on a numerical example referring to investment decisions in facilities for the production of electric vehicle batteries, we find that the optimal investment threshold follows an S-curve over the product life cycle and derive the optimal capacity choice for the given investment decision.

Suggested Citation

  • Lukas, Elmar & Spengler, Thomas Stefan & Kupfer, Stefan & Kieckhäfer, Karsten, 2017. "When and how much to invest? Investment and capacity choice under product life cycle uncertainty," European Journal of Operational Research, Elsevier, vol. 260(3), pages 1105-1114.
    • Handle: RePEc:eee:ejores:v:260:y:2017:i:3:p:1105-1114
    DOI: 10.1016/j.ejor.2017.01.027
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    Cited by:

    1. Adkins, Roger & Paxson, Dean, 2019. "Rescaling-contraction with a lower cost technology when revenue declines," European Journal of Operational Research, Elsevier, vol. 277(2), pages 574-586.
    2. Hans Ulrich Buhl & Valerie Graf-Drasch & Christian Wiethe, 2023. "What to say and what to do: the disparity of the communication and investment in sustainability targets, given customer expectations," Journal of Business Economics, Springer, vol. 93(3), pages 485-507, April.
    3. Hu, Fan & Wu, Yaoyao & Zhou, Lei, 2022. "Irreversible investment and capacity choice with Bayesian learning," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    4. Lukas, Elmar & Thiergart, Sascha, 2019. "The interaction of debt financing, cash grants and the optimal investment policy under uncertainty," European Journal of Operational Research, Elsevier, vol. 276(1), pages 284-299.
    5. Michi Nishihara, 2017. "Valuation of an R&D project with three types of uncertainty," Discussion Papers in Economics and Business 17-15, Osaka University, Graduate School of Economics.
    6. Thijssen, Jacco J.J., 2022. "Optimal investment and abandonment decisions for projects with construction uncertainty," European Journal of Operational Research, Elsevier, vol. 298(1), pages 368-379.
    7. Michi Nishihara, 2018. "Valuation of an R&D project with three types of uncertainty," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 93-113, June.
    8. Feng Liu & Yingshuang Tan & Sudipto Sarkar & Xueqing Zhang & Xingjun Huang, 2023. "When to invest in electric vehicles under dual credit policy: A real options approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(4), pages 2186-2198, June.
    9. Bettina Freitag & Lukas Häfner & Verena Pfeuffer & Jochen Übelhör, 2020. "Evaluating investments in flexible on-demand production capacity: a real options approach," Business Research, Springer;German Academic Association for Business Research, vol. 13(1), pages 133-161, April.
    10. Chevalier-Roignant, Benoît & Flath, Christoph M. & Kort, Peter M. & Trigeorgis, Lenos, 2021. "Capacity investment choices under cost heterogeneity and output flexibility in oligopoly," European Journal of Operational Research, Elsevier, vol. 290(3), pages 1154-1173.
    11. Cristina Mihale-Wilson & Patrick Felka & Oliver Hinz & Martin Spann, 2022. "The Impact of Strategic Core-Component Reuse on Product Life Cycles," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(2), pages 223-237, April.
    12. Briest, Gordon & Lauven, Lars-Peter & Kupfer, Stefan & Lukas, Elmar, 2022. "Leaving well-worn paths: Reversal of the investment-uncertainty relationship and flexible biogas plant operation," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1162-1176.
    13. Gordon Briest & Elmar Lukas & Sascha H. Mölls & Timo Willershausen, 2020. "Innovation speed under uncertainty and competition," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(8), pages 1517-1527, December.
    14. Ping Shi & Bo Yan & Jun Zhao, 2020. "Appropriate timing for SMEs to introduce an Internet-based online channel under uncertain operating costs: a real options analysis," Electronic Commerce Research, Springer, vol. 20(4), pages 969-999, December.
    15. Dong, Ming & Mao, Shunjie & Li, Shan, 2023. "Supplier's technology upgrading investment strategy considering product life cycle," International Journal of Production Economics, Elsevier, vol. 263(C).
    16. Sendstad, Lars Hegnes & Chronopoulos, Michail, 2021. "Strategic technology switching under risk aversion and uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 126(C).

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    More about this item

    Keywords

    OR in research and development; Bass model based product life cycle; Electric vehicle battery; Real option; Capacity choice;
    All these keywords.

    JEL classification:

    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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