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Design of supply chain resilience strategies from the product life cycle perspective

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  • Yang, Yi
  • Peng, Chen
  • Cao, En-Zhi

Abstract

Supply chain (SC) resilience strategies are frequently employed to hedge against disruptions. Despite a substantial body of literature examining the design of SC resilience strategies, there is a paucity of literature exploring the impact of the product life cycle (PLC) on the design of such strategies. This paper presents scenario-based and time-dependent mixed integer programming mathematical models for optimizing performance in terms of costs and service levels. The models consider the distinctive characteristics of each PLC phase. Simulation-based analyses are utilized to simulate disruptions at different stages of the PLC and to explore the impact of the PLC on SC resilience strategies design. Moreover, a resilience multi-portfolio method is modified using simulation techniques to determine optimal resilience portfolios from the PLC perspective. Through computational examples and sensitivity analysis, our models are capable of achieving resilience supply and production portfolios by making a trade-off between costs and service levels from the PLC perspective. The results illustrate that our approaches facilitate the identification of critical relationships between the severity of disruptions and the formulation of SC resilience strategies in terms of the PLC. The findings are instructive for SC managers when considering the impact of disruptions from the perspective of the PLC.

Suggested Citation

  • Yang, Yi & Peng, Chen & Cao, En-Zhi, 2025. "Design of supply chain resilience strategies from the product life cycle perspective," International Journal of Production Economics, Elsevier, vol. 282(C).
  • Handle: RePEc:eee:proeco:v:282:y:2025:i:c:s0925527325000179
    DOI: 10.1016/j.ijpe.2025.109532
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    1. Aitken, James & Childerhouse, Paul & Towill, Denis, 2003. "The impact of product life cycle on supply chain strategy," International Journal of Production Economics, Elsevier, vol. 85(2), pages 127-140, August.
    2. Yi Yang & Chen Peng, 2023. "A prediction-based supply chain recovery strategy under disruption risks," International Journal of Production Research, Taylor & Francis Journals, vol. 61(22), pages 7670-7684, November.
    3. Sanjoy Kumar Paul & Shams Rahman, 2018. "A quantitative and simulation model for managing sudden supply delay with fuzzy demand and safety stock," International Journal of Production Research, Taylor & Francis Journals, vol. 56(13), pages 4377-4395, July.
    4. Ivanov, Dmitry & Keskin, Burcu B., 2023. "Post-pandemic adaptation and development of supply chain viability theory," Omega, Elsevier, vol. 116(C).
    5. Ramani, Vinay & Ghosh, Debabrata & Sodhi, ManMohan S., 2022. "Understanding systemic disruption from the Covid-19-induced semiconductor shortage for the auto industry," Omega, Elsevier, vol. 113(C).
    6. ., 2021. "Introduction to Sustainable Consumption, Production and Supply Chain Management," Chapters, in: Sustainable Consumption, Production and Supply Chain Management, chapter 1, pages 1-6, Edward Elgar Publishing.
    7. Ivanov, Dmitry & Dolgui, Alexandre, 2021. "OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications," International Journal of Production Economics, Elsevier, vol. 232(C).
    8. Salomée Ruel & Jamal El Baz & Dmitry Ivanov & Ajay Das, 2024. "Supply chain viability: conceptualization, measurement, and nomological validation," Annals of Operations Research, Springer, vol. 335(3), pages 1107-1136, April.
    9. Gholamreza Shafipour & Abdolvahhab Fetanat, 2016. "Survival analysis in supply chains using statistical flowgraph models: Predicting time to supply chain disruption," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(21), pages 6183-6208, November.
    10. Marco Ardolino & Andrea Bacchetti & Dmitry Ivanov, 2022. "Analysis of the COVID-19 pandemic’s impacts on manufacturing: a systematic literature review and future research agenda," Operations Management Research, Springer, vol. 15(1), pages 551-566, June.
    11. Ivanov, Dmitry, 2024. "Supply chain resilience: Conceptual and formal models drawing from immune system analogy," Omega, Elsevier, vol. 127(C).
    12. Bartosz Sawik, 2024. "Optimizing Last-Mile Delivery: A Multi-Criteria Approach with Automated Smart Lockers, Capillary Distribution and Crowdshipping," Logistics, MDPI, vol. 8(2), pages 1-29, May.
    13. Sawik, Tadeusz, 2022. "Stochastic optimization of supply chain resilience under ripple effect: A COVID-19 pandemic related study," Omega, Elsevier, vol. 109(C).
    14. Tadeusz Sawik & Bartosz Sawik, 2024. "Risk-averse decision-making to maintain supply chain viability under propagated disruptions," International Journal of Production Research, Taylor & Francis Journals, vol. 62(8), pages 2853-2867, April.
    15. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry, 2023. "Efficient resilience portfolio design in the supply chain with consideration of preparedness and recovery investments," Omega, Elsevier, vol. 117(C).
    16. Ivanov, Dmitry, 2023. "Intelligent digital twin (iDT) for supply chain stress-testing, resilience, and viability," International Journal of Production Economics, Elsevier, vol. 263(C).
    17. Sawik, Tadeusz, 2021. "On the risk-averse selection of resilient multi-tier supply portfolio," Omega, Elsevier, vol. 101(C).
    18. Dmitry Ivanov, 2024. "Two views of supply chain resilience," International Journal of Production Research, Taylor & Francis Journals, vol. 62(11), pages 4031-4045, June.
    19. Sawik, Tadeusz, 2013. "Selection of resilient supply portfolio under disruption risks," Omega, Elsevier, vol. 41(2), pages 259-269.
    20. Nepal, Bimal & Monplaisir, Leslie & Famuyiwa, Oluwafemi, 2012. "Matching product architecture with supply chain design," European Journal of Operational Research, Elsevier, vol. 216(2), pages 312-325.
    21. Dmitry Ivanov, 2017. "Simulation-based ripple effect modelling in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 2083-2101, April.
    22. Gholami-Zanjani, Seyed Mohammad & Klibi, Walid & Jabalameli, Mohammad Saeed & Pishvaee, Mir Saman, 2021. "The design of resilient food supply chain networks prone to epidemic disruptions," International Journal of Production Economics, Elsevier, vol. 233(C).
    23. Ivanov, Dmitry, 2020. "Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    24. Seyedmohsen Hosseini & Dmitry Ivanov & Alexandre Dolgui, 2020. "Ripple effect modelling of supplier disruption: integrated Markov chain and dynamic Bayesian network approach," International Journal of Production Research, Taylor & Francis Journals, vol. 58(11), pages 3284-3303, June.
    25. Jafar Namdar & S. Ali Torabi & Navid Sahebjamnia & Ninad Nilkanth Pradhan, 2021. "Business continuity-inspired resilient supply chain network design," International Journal of Production Research, Taylor & Francis Journals, vol. 59(5), pages 1331-1367, March.
    26. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry & Zennaro, Ilenia, 2021. "Costs of resilience and disruptions in supply chain network design models: A review and future research directions," International Journal of Production Economics, Elsevier, vol. 235(C).
    27. Sawik, Tadeusz, 2011. "Selection of supply portfolio under disruption risks," Omega, Elsevier, vol. 39(2), pages 194-208, April.
    28. Tadeusz Sawik, 2023. "A stochastic optimisation approach to maintain supply chain viability under the ripple effect," International Journal of Production Research, Taylor & Francis Journals, vol. 61(8), pages 2452-2469, April.
    29. Dmitry Ivanov & Alexandre Dolgui, 2020. "Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak," International Journal of Production Research, Taylor & Francis Journals, vol. 58(10), pages 2904-2915, May.
    30. Brian Tomlin, 2009. "Disruption‐management strategies for short life‐cycle products," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(4), pages 318-347, June.
    31. Hosseini, Seyedmohsen & Morshedlou, Nazanin & Ivanov, Dmitry & Sarder, M.D. & Barker, Kash & Khaled, Abdullah Al, 2019. "Resilient supplier selection and optimal order allocation under disruption risks," International Journal of Production Economics, Elsevier, vol. 213(C), pages 124-137.
    32. Arrate Llaguno & Josefa Mula & Francisco Campuzano-Bolarin, 2022. "State of the art, conceptual framework and simulation analysis of the ripple effect on supply chains," International Journal of Production Research, Taylor & Francis Journals, vol. 60(6), pages 2044-2066, March.
    33. Sanjoy Kumar Paul & Md. Abdul Moktadir & Karam Sallam & Tsan-Ming Choi & Ripon Kumar Chakrabortty, 2023. "A recovery planning model for online business operations under the COVID-19 outbreak," International Journal of Production Research, Taylor & Francis Journals, vol. 61(8), pages 2613-2635, April.
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