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Real options approach to evaluate postponement as supply chain disruptions mitigation strategy

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  • Nunzia Carbonara
  • Roberta Pellegrino

Abstract

The purpose of this paper is to assess the value of postponement as strategy for mitigating supply chain disruptions. To accomplish this objective, we develop a real option computational model that quantifies the value of postponement in mitigating both supply and demand disruptions by taking into account the value of managerial flexibility to decide whether exploiting or not the strategy, if and when disruptions occur, and whenever product differentiation proves valuable based on information available at that time. Numerical experiments show the importance of incorporating an option valuation method when pricing the value of postponement. This ensures managers implement postponement only when it is valuable, thus avoiding burdening the company with its initial sunk costs. By modelling the postponement implementation under different conditions, we identify the situations in which postponement performs better as supply chain disruptions mitigation strategy. We derive the operational configurations, in terms of decoupling point position, and external conditions, in terms of riskiness of the environment, which make the postponement an effective mitigation strategy.

Suggested Citation

  • Nunzia Carbonara & Roberta Pellegrino, 2018. "Real options approach to evaluate postponement as supply chain disruptions mitigation strategy," International Journal of Production Research, Taylor & Francis Journals, vol. 56(15), pages 5249-5271, August.
  • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:15:p:5249-5271
    DOI: 10.1080/00207543.2017.1403663
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    Citations

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    Cited by:

    1. Lauren Chenarides & Mark Manfredo & Timothy J. Richards, 2021. "COVID‐19 and Food Supply Chains," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(1), pages 270-279, March.
    2. Jafari, Hamid & Eslami, Mohammad H. & Paulraj, Antony, 2022. "Postponement and logistics flexibility in retailing: The moderating role of logistics integration and demand uncertainty," International Journal of Production Economics, Elsevier, vol. 243(C).
    3. Muhammad Junaid & Ye Xue & Muzzammil Wasim Syed & Ji Zu Li & Muhammad Ziaullah, 2019. "A Neutrosophic AHP and TOPSIS Framework for Supply Chain Risk Assessment in Automotive Industry of Pakistan," Sustainability, MDPI, vol. 12(1), pages 1-26, December.
    4. Gorupec Natalia & Tiberius Victor & Brehmer Nataliia & Kraus Sascha, 2022. "Tackling uncertain future scenarios with real options: A review and research framework," The Irish Journal of Management, Sciendo, vol. 41(1), pages 69-88, July.
    5. Andrejs Čirjevskis, 2021. "Exploring the Link of Real Options Theory with Dynamic Capabilities Framework in Open Innovation-Type Merger and Acquisition Deals," JRFM, MDPI, vol. 14(4), pages 1-16, April.
    6. Eugene Furman & Alex Cressman & Saeha Shin & Alexey Kuznetsov & Fahad Razak & Amol Verma & Adam Diamant, 2021. "Prediction of personal protective equipment use in hospitals during COVID-19," Health Care Management Science, Springer, vol. 24(2), pages 439-453, June.
    7. Méndez-Suárez, Mariano & Crespo-Tejero, Natividad, 2021. "Why do banks retain unprofitable customers? A customer lifetime value real options approach," Journal of Business Research, Elsevier, vol. 122(C), pages 621-626.
    8. Pratibha Wasan & Ashwani Kumar & Sunil Luthra, 2023. "How can banks and finance companies incorporate value chain factors in their risk management strategy? The case of agro‐food firms," Business Strategy and the Environment, Wiley Blackwell, vol. 32(1), pages 858-877, January.
    9. Munyaradzi Bvuchete & Sara Saartjie Grobbelaar & Joubert van Eeden, 2021. "A Network Maturity Mapping Tool for Demand-Driven Supply Chain Management: A Case for the Public Healthcare Sector," Sustainability, MDPI, vol. 13(21), pages 1-29, October.

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