IDEAS home Printed from https://ideas.repec.org/a/spr/opmare/v15y2022i1d10.1007_s12063-021-00195-y.html
   My bibliography  Save this article

A scenario-based robust time–cost tradeoff model to handle the effect of COVID-19 on supply chains project management

Author

Listed:
  • Seyed Hossein Razavi Hajiagha

    (Faculty of Management and Finance, Khatam University)

  • Hannan Amoozad Mahdiraji

    (De Montfort University
    University of Tehran)

  • Maryam Behnam

    (University of Tehran)

  • Boshra Nekoughadirli

    (University of Tehran)

  • Rohit Joshi

    (Indian Institute of Management Shillong)

Abstract

The COVID-19 pandemic outbreak deeply impressed supply chains in different aspects. In response to this unexpected situation, supply chain managers have decided to recover and reinforce their supply chains. Considering the expanse of these decisions, project management principle and tools seems inevitable to successfully manage the transformation from before pandemic to post-pandemic supply chains (SCs). In this study, the problem of time–cost tradeoff is extended to time, cost, and risk tradeoff. The risk factor is considered to convey the uncertainty arising from the COVID-19 pandemic situation. Since projects are affected by the level of pandemic expansion and different countries ruled out various quarantine policies (isolation, quarantine, social distancing, and lock-down), the tradeoff problem is influenced accordingly. Therefore, a scenario-based robust optimization model is proposed to deal with time, cost, and risk tradeoff problems to reflect the effects of the global pandemic of COVID-19 on managing projects in supply chains. In addition, various quarantine policies (isolation, quarantine, social distancing, and lock-down) as a prevalent response to the pandemic have been investigated separately. To illustrate the model, a real-world case study in the emerging economy of Iran is examined using the proposed approach. The results indicated that supply chain managers can use the designed model and approach as a tool for a flexible and adaptable decision-making framework dealing with a global pandemic such as COVID-19.

Suggested Citation

  • Seyed Hossein Razavi Hajiagha & Hannan Amoozad Mahdiraji & Maryam Behnam & Boshra Nekoughadirli & Rohit Joshi, 2022. "A scenario-based robust time–cost tradeoff model to handle the effect of COVID-19 on supply chains project management," Operations Management Research, Springer, vol. 15(1), pages 357-377, June.
  • Handle: RePEc:spr:opmare:v:15:y:2022:i:1:d:10.1007_s12063-021-00195-y
    DOI: 10.1007/s12063-021-00195-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12063-021-00195-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s12063-021-00195-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sharma, Amalesh & Adhikary, Anirban & Borah, Sourav Bikash, 2020. "Covid-19′s impact on supply chain decisions: Strategic insights from NASDAQ 100 firms using Twitter data," Journal of Business Research, Elsevier, vol. 117(C), pages 443-449.
    2. Yuanwei Qin & Xiangming Xiao & Jean-Pierre Wigneron & Philippe Ciais & Martin Brandt & Lei Fan & Xiaojun Li & Sean Crowell & Xiaocui Wu & Russell Doughty & Yao Zhang & Fang Liu & Stephen Sitch & Berri, 2021. "Carbon loss from forest degradation exceeds that from deforestation in the Brazilian Amazon," Nature Climate Change, Nature, vol. 11(5), pages 442-448, May.
    3. Farnaz Torabi Yeganeh & Seyed Hessameddin Zegordi, 2020. "A multi-objective optimization approach to project scheduling with resiliency criteria under uncertain activity duration," Annals of Operations Research, Springer, vol. 285(1), pages 161-196, February.
    4. Peter R. A. Oeij & Jeff B. R. Gaspersz & Tinka van Vuuren & Steven Dhondt, 2017. "Leadership in innovation projects: an illustration of the reflective practitioner and the relation to organizational learning," Journal of Innovation and Entrepreneurship, Springer, vol. 6(1), pages 1-20, December.
    5. Sameer Prasad & Jason Woldt & Jasmine Tata & Nezih Altay, 2019. "Application of project management to disaster resilience," Annals of Operations Research, Springer, vol. 283(1), pages 561-590, December.
    6. Emenike, Scholastica N. & Falcone, Gioia, 2020. "A review on energy supply chain resilience through optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    7. Jeunet, Jully & Bou Orm, Mayassa, 2020. "Optimizing temporary work and overtime in the Time Cost Quality Trade-off Problem," European Journal of Operational Research, Elsevier, vol. 284(2), pages 743-761.
    8. Emmanuel Kwasi Mensah & Lawrence Adu Asamoah & Vahid Jafari-Sadeghi, 2021. "Entrepreneurial opportunity decisions under uncertainty: Recognizing the complementing role of personality traits and cognitive skills," Journal of Entrepreneurship, Management and Innovation, Fundacja Upowszechniająca Wiedzę i Naukę "Cognitione", vol. 17(1), pages 25-55.
    9. Hasani, Aliakbar & Khosrojerdi, Amirhossein, 2016. "Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 20-52.
    10. Öncü Hazır & Mohamed Haouari & Erdal Erel, 2015. "Robust Optimization for the Discrete Time-Cost Tradeoff Problem with Cost Uncertainty," International Handbooks on Information Systems, in: Christoph Schwindt & Jürgen Zimmermann (ed.), Handbook on Project Management and Scheduling Vol. 2, edition 127, chapter 0, pages 865-874, Springer.
    11. Chen, Hsi Yueh & Das, Ajay & Ivanov, Dmitry, 2019. "Building resilience and managing post-disruption supply chain recovery: Lessons from the information and communication technology industry," International Journal of Information Management, Elsevier, vol. 49(C), pages 330-342.
    12. Choi, Byung-Cheon & Park, Myoung-Ju, 2015. "A continuous time–cost tradeoff problem with multiple milestones and completely ordered jobs," European Journal of Operational Research, Elsevier, vol. 244(3), pages 748-752.
    13. Syed Ali Naqi Kazmi & Asia Baig & Muhammad Zia-Ur Rehman, 2018. "The Economy of Projects: Analyzing Project Management Resilience, Stress Management and Project Sustainability," Global Economics Review, Humanity Only, vol. 3(1), pages 50-61, June.
    14. Marly Monteiro de Carvalho & Roque Rabechini Junior, 2015. "Impact of risk management on project performance: the importance of soft skills," International Journal of Production Research, Taylor & Francis Journals, vol. 53(2), pages 321-340, January.
    15. Maureen S. Golan & Laura H. Jernegan & Igor Linkov, 2020. "Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic," Environment Systems and Decisions, Springer, vol. 40(2), pages 222-243, June.
    16. 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).
    17. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Marina Ivanova, 2017. "Literature review on disruption recovery in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6158-6174, October.
    18. Wong, Christina W.Y. & Lirn, Taih-Cherng & Yang, Ching-Chiao & Shang, Kuo-Chung, 2020. "Supply chain and external conditions under which supply chain resilience pays: An organizational information processing theorization," International Journal of Production Economics, Elsevier, vol. 226(C).
    19. Majid Askarifard & Hamidreza Abbasianjahromi & Mehran Sepehri & Ehsanollah Zeighami, 2021. "A robust multi-objective optimization model for project scheduling considering risk and sustainable development criteria," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 11494-11524, August.
    20. John M. Mulvey & Robert J. Vanderbei & Stavros A. Zenios, 1995. "Robust Optimization of Large-Scale Systems," Operations Research, INFORMS, vol. 43(2), pages 264-281, April.
    21. 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.
    22. Rezapour, Shabnam & Farahani, Reza Zanjirani & Pourakbar, Morteza, 2017. "Resilient supply chain network design under competition: A case study," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1017-1035.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yılmaz, Ömer Faruk & Yeni, Fatma Betül & Gürsoy Yılmaz, Beren & Özçelik, Gökhan, 2023. "An optimization-based methodology equipped with lean tools to strengthen medical supply chain resilience during a pandemic: A case study from Turkey," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    2. 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).
    3. Zhu, Xiaoyan & Cao, Yunzhi, 2021. "The optimal recovery-fund based strategy for uncertain supply chain disruptions: A risk-averse two-stage stochastic programming approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    4. Chowdhury, Priyabrata & Paul, Sanjoy Kumar & Kaisar, Shahriar & Moktadir, Md. Abdul, 2021. "COVID-19 pandemic related supply chain studies: A systematic review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    5. Antonio Zavala-Alcívar & María-José Verdecho & Juan-José Alfaro-Saiz, 2020. "A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain," Sustainability, MDPI, vol. 12(16), pages 1-38, August.
    6. Maureen S. Golan & Laura H. Jernegan & Igor Linkov, 2020. "Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic," Environment Systems and Decisions, Springer, vol. 40(2), pages 222-243, June.
    7. Clavijo-Buritica, Nicolás & Triana-Sanchez, Laura & Escobar, John Willmer, 2023. "A hybrid modeling approach for resilient agri-supply network design in emerging countries: Colombian coffee supply chain," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    8. Paul, Sanjoy Kumar & Chowdhury, Priyabrata & Moktadir, Md. Abdul & Lau, Kwok Hung, 2021. "Supply chain recovery challenges in the wake of COVID-19 pandemic," Journal of Business Research, Elsevier, vol. 136(C), pages 316-329.
    9. Garvey, Myles D. & Carnovale, Steven, 2020. "The rippled newsvendor: A new inventory framework for modeling supply chain risk severity in the presence of risk propagation," International Journal of Production Economics, Elsevier, vol. 228(C).
    10. Alexander Pavlov & Dmitry Ivanov & Frank Werner & Alexandre Dolgui & Boris Sokolov, 2022. "Integrated detection of disruption scenarios, the ripple effect dispersal and recovery paths in supply chains," Annals of Operations Research, Springer, vol. 319(1), pages 609-631, December.
    11. Gupta, Varun & Ivanov, Dmitry & Choi, Tsan-Ming, 2021. "Competitive pricing of substitute products under supply disruption," Omega, Elsevier, vol. 101(C).
    12. Hosseini, Seyedmohsen & Ivanov, Dmitry & Dolgui, Alexandre, 2019. "Review of quantitative methods for supply chain resilience analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 285-307.
    13. Cagri Gurbuz, Mustafa & Yurt, Oznur & Ozdemir, Sena & Sena, Vania & Yu, Wantao, 2023. "Global supply chains risks and COVID-19: Supply chain structure as a mitigating strategy for small and medium-sized enterprises," Journal of Business Research, Elsevier, vol. 155(PB).
    14. Kanokporn Kungwalsong & Chen-Yang Cheng & Chumpol Yuangyai & Udom Janjarassuk, 2021. "Two-Stage Stochastic Program for Supply Chain Network Design under Facility Disruptions," Sustainability, MDPI, vol. 13(5), pages 1-19, March.
    15. Li Cui & Hao Wu & Lin Wu & Ajay Kumar & Kim Hua Tan, 2023. "Investigating the relationship between digital technologies, supply chain integration and firm resilience in the context of COVID-19," Annals of Operations Research, Springer, vol. 327(2), pages 825-853, August.
    16. Papanagnou, Christos & Seiler, Andreas & Spanaki, Konstantina & Papadopoulos, Thanos & Bourlakis, Michael, 2022. "Data-driven digital transformation for emergency situations: The case of the UK retail sector," International Journal of Production Economics, Elsevier, vol. 250(C).
    17. Lydia Novoszel & Tina Wakolbinger, 2022. "Meta-analysis of Supply Chain Disruption Research," SN Operations Research Forum, Springer, vol. 3(1), pages 1-25, March.
    18. Lin, Yongjia & Fan, Di & Shi, Xuanyi & Fu, Maggie, 2021. "The effects of supply chain diversification during the COVID-19 crisis: Evidence from Chinese manufacturers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
    19. Aida Rezaei & Amir Aghsami & Masoud Rabbani, 2021. "Supplier selection and order allocation model with disruption and environmental risks in centralized supply chain," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(6), pages 1036-1072, December.
    20. Govindan, Kannan & Gholizadeh, Hadi, 2021. "Robust network design for sustainable-resilient reverse logistics network using big data: A case study of end-of-life vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:opmare:v:15:y:2022:i:1:d:10.1007_s12063-021-00195-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.