IDEAS home Printed from https://ideas.repec.org/a/spr/opmare/v15y2022i1d10.1007_s12063-020-00170-z.html
   My bibliography  Save this article

Capturing attitudinal characteristics of decision-makers in group decision making: application to select policy recommendations to enhance supply chain resilience under COVID-19 outbreak

Author

Listed:
  • Zhi Wen

    (Sichuan University)

  • Huchang Liao

    (Sichuan University)

Abstract

The impact of COVID-19 on the global outbreak of supply chain is enormous. It is crucial for governments to take policy recommendations to enhance the supply chain resilience to mitigate the negative impact of COVID-19. For such a major issue, it is a common occurrence that a large number of decision-makers (DMs) are invited to participate in the decision-making process so as to ensure the comprehensiveness and reliability of decision results. Since the attitudinal characteristics of DMs are important factors affecting decision results, this study focuses on capturing the attitudinal characteristics of DMs in the large-scale group decision making process. The capturing process combines the ordinal k-means clustering algorithm, gained and lost dominance score method and personalized quantifiers. To enable DMs to express their cognitions in depth, we use the probabilistic linguistic term set to express the evaluation information of DMs. A case study on selecting the optimal policy recommendation for improving the integration capability of supply chain is given to illustrate the applicability of the proposed process. The superiority of the proposed algorithm is highlighted through sensitive analysis and comparative analysis.

Suggested Citation

  • Zhi Wen & Huchang Liao, 2022. "Capturing attitudinal characteristics of decision-makers in group decision making: application to select policy recommendations to enhance supply chain resilience under COVID-19 outbreak," Operations Management Research, Springer, vol. 15(1), pages 179-194, June.
    • Handle: RePEc:spr:opmare:v:15:y:2022:i:1:d:10.1007_s12063-020-00170-z
    DOI: 10.1007/s12063-020-00170-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12063-020-00170-z
    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/s12063-020-00170-z?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. Liang, Gin-Shuh & Chou, Tsung-Yu & Han, Tzeu-Chen, 2005. "Cluster analysis based on fuzzy equivalence relation," European Journal of Operational Research, Elsevier, vol. 166(1), pages 160-171, October.
    2. Syed Abdul Rehman Khan & Arshian Sharif & Hêriş Golpîra & Anil Kumar, 2019. "A green ideology in Asian emerging economies: From environmental policy and sustainable development," Sustainable Development, John Wiley & Sons, Ltd., vol. 27(6), pages 1063-1075, November.
    3. Guo, Kaihong, 2016. "Quantifiers induced by subjective expected value of sample information with Bernstein polynomials," European Journal of Operational Research, Elsevier, vol. 254(1), pages 226-235.
    4. Sarrazin, R. & De Smet, Y. & Rosenfeld, J., 2018. "An extension of PROMETHEE to interval clustering," Omega, Elsevier, vol. 80(C), pages 12-21.
    5. Govindan, Kannan & Mina, Hassan & Alavi, Behrouz, 2020. "A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19)," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    6. Wu, Xingli & Liao, Huchang, 2019. "A consensus-based probabilistic linguistic gained and lost dominance score method," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1017-1027.
    7. 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.
    8. Jill E. Hobbs, 2020. "Food supply chains during the COVID‐19 pandemic," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 68(2), pages 171-176, June.
    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. Tang, Ming & Liao, Huchang, 2021. "From conventional group decision making to large-scale group decision making: What are the challenges and how to meet them in big data era? A state-of-the-art survey," Omega, Elsevier, vol. 100(C).
    2. Md. Tarek Chowdhury & Aditi Sarkar & Sanjoy Kumar Paul & Md. Abdul Moktadir, 2022. "A case study on strategies to deal with the impacts of COVID-19 pandemic in the food and beverage industry," Operations Management Research, Springer, vol. 15(1), pages 166-178, June.
    3. Muhammad Umar Farooq & Amjad Hussain & Tariq Masood & Muhammad Salman Habib, 2021. "Supply Chain Operations Management in Pandemics: A State-of-the-Art Review Inspired by COVID-19," Sustainability, MDPI, vol. 13(5), pages 1-33, February.
    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. Anker, Thomas Boysen, 2021. "At the boundary: Post-COVID agenda for business and management research in Europe and beyond," European Management Journal, Elsevier, vol. 39(2), pages 171-178.
    6. Fang, Da & Guo, Yan, 2022. "Flow of goods to the shock of COVID-19 and toll-free highway policy: Evidence from logistics data in China," Research in Transportation Economics, Elsevier, vol. 93(C).
    7. Paul, Ananna & Shukla, Nagesh & Trianni, Andrea, 2023. "Modelling supply chain sustainability challenges in the food processing sector amid the COVID-19 outbreak," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    8. Tang, Lianhua & Li, Yantong & Bai, Danyu & Liu, Tao & Coelho, Leandro C., 2022. "Bi-objective optimization for a multi-period COVID-19 vaccination planning problem," Omega, Elsevier, vol. 110(C).
    9. Rozhkov, Maxim & Ivanov, Dmitry & Blackhurst, Jennifer & Nair, Anand, 2022. "Adapting supply chain operations in anticipation of and during the COVID-19 pandemic," Omega, Elsevier, vol. 110(C).
    10. Bianco, Débora & Bueno, Adauto & Godinho Filho, Moacir & Latan, Hengky & Miller Devós Ganga, Gilberto & Frank, Alejandro G. & Chiappetta Jabbour, Charbel Jose, 2023. "The role of Industry 4.0 in developing resilience for manufacturing companies during COVID-19," International Journal of Production Economics, Elsevier, vol. 256(C).
    11. Rudsari, Saba & Fuqua, Donovan & Pimentel, Victor & Brewer, Barry, 2023. "Resilience and Recovery: Understanding the Underlying Drivers of Long-term Instability in Food Supply Chains," Journal of Food Distribution Research, Food Distribution Research Society, vol. 54(2), July.
    12. 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.
    13. Katarzyna Grzybowska, 2021. "Identification and Classification of Global Theoretical Trends and Supply Chain Development Directions," Energies, MDPI, vol. 14(15), pages 1-19, July.
    14. Gilani, Hani & Sahebi, Hadi, 2022. "A data-driven robust optimization model by cutting hyperplanes on vaccine access uncertainty in COVID-19 vaccine supply chain," Omega, Elsevier, vol. 110(C).
    15. Walid Gani, 2021. "The causal relationship between corruption and irresponsible behavior in the time of COVID‐19: Evidence from Tunisia," African Development Review, African Development Bank, vol. 33(S1), pages 165-176, April.
    16. Ekinci, Esra & Mangla, Sachin Kumar & Kazancoglu, Yigit & Sarma, P.R.S. & Sezer, Muruvvet Deniz & Ozbiltekin-Pala, Melisa, 2022. "Resilience and complexity measurement for energy efficient global supply chains in disruptive events," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    17. Burgos, Diana & Ivanov, Dmitry, 2021. "Food retail supply chain resilience and the COVID-19 pandemic: A digital twin-based impact analysis and improvement directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    18. Takaki Nagao & Hiromasa Ijuin & Tetsuo Yamada & Keisuke Nagasawa & Lei Zhou, 2021. "COVID-19 Disruption Strategy for Redesigning Global Supply Chain Network across TPP Countries," Logistics, MDPI, vol. 6(1), pages 1-26, December.
    19. Amjad Hussain & Muhammad Umar Farooq & Muhammad Salman Habib & Tariq Masood & Catalin I. Pruncu, 2021. "COVID-19 Challenges: Can Industry 4.0 Technologies Help with Business Continuity?," Sustainability, MDPI, vol. 13(21), pages 1-25, October.
    20. Margarida Rodrigues & Mário Franco & Nuno Sousa & Rui Silva, 2021. "Reviewing COVID-19 Literature on Business Management: What It Portends for Future Research?," Sustainability, MDPI, vol. 13(11), pages 1-21, May.

    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_s12063-020-00170-z. 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.