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Flexibility planning for managing R&D projects under risk

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  • Wang, Juite
  • Yang, Chung-Yu

Abstract

Incorporating managerial flexibility in an innovative R&D project is important, because managers face greater uncertainty in today's competitive and dynamic changing environment. It is essential to bring managerial flexibility into R&D project planning to decrease technical and market risks, while increasing potential market value. The objective of this paper is to develop a flexibility planning methodology based on real option analysis to improve managerial flexibility for R&D projects. The proposed methodology identifies potential risks that may occur during every R&D stage. It also recognizes a cascading option structure to resolve the identified risks, and evaluates and selects adequate options that maximize the potential value of the project. Instead of using a traditional option pricing method, a dynamic programming model that considers multidimensional product performance and market payoff is used to evaluate the R&D project value. Using the proposed methodology, managers can identify future scenarios as a function of their management actions. The proposed flexibility planning methodology can help managers improve managerial flexibility of R&D project and increase the success rate of product launch. A drug development project is used to illustrate the proposed methodology.

Suggested Citation

  • Wang, Juite & Yang, Chung-Yu, 2012. "Flexibility planning for managing R&D projects under risk," International Journal of Production Economics, Elsevier, vol. 135(2), pages 823-831.
    • Handle: RePEc:eee:proeco:v:135:y:2012:i:2:p:823-831
    DOI: 10.1016/j.ijpe.2011.10.020
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    Cited by:

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    2. Junseok Shin & Sungjoo Lee & Byungun Yoon, 2018. "Identification and Prioritisation of Risk Factors in R&D Projects Based on an R&D Process Model," Sustainability, MDPI, vol. 10(4), pages 1-18, March.
    3. Gulzhan Isatayeva & Velena Seitova & Gulzhamal Koptayeva & Altynai Turlybekova & Aigul Mutaliyeva, 2019. "Financing of young knowledge-based companies after the financial crisis: the case of Kazakhstan," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 6(3), pages 1226-1234, March.
    4. Trigeorgis, Lenos & Tsekrekos, Andrianos E., 2018. "Real Options in Operations Research: A Review," European Journal of Operational Research, Elsevier, vol. 270(1), pages 1-24.
    5. Hanne Lamberts-Van Assche & Tine Compernolle, 2022. "Using Real Options Thinking to Value Investment Flexibility in Carbon Capture and Utilization Projects: A Review," Sustainability, MDPI, vol. 14(4), pages 1-24, February.
    6. Parast, Mahour Mellat, 2020. "The impact of R&D investment on mitigating supply chain disruptions: Empirical evidence from U.S. firms," International Journal of Production Economics, Elsevier, vol. 227(C).
    7. Chuan-Chuan Ko & Tyrone T. Lin & Fu-Min Zeng & Chien-Yu Liu, 2018. "Optimum Technology Product Life Cycle Technology Innovation Investment-Using Compound Binomial Options," Risks, MDPI, vol. 6(3), pages 1-14, September.
    8. Shimizu, Takashi & Park, Youngwon & Choi, SukBong, 2014. "Project managers and risk management: A comparative study between Japanese and Korean firms," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 437-447.

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