IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i4p2081-d499825.html
   My bibliography  Save this article

The Formulation of Epidemic Prevention Work of COVID-19 for Colleges and Universities: Priorities and Recommendations

Author

Listed:
  • Wan-Chi Jackie Hsu

    (Graduate Institute of Cultural and Educational Management, Central Taiwan University of Sciences and Technology, Taichung 40601, Taiwan
    College of Management, National Taipei University of Technology, Taipei 10608, Taiwan)

  • Huai-Wei Lo

    (Department of Industrial Engineering and Management, Chaoyang University of Technology, Taichung 413310, Taiwan)

  • Chin-Cheng Yang

    (Department of Leisure Services Management, Chaoyang University of Technology, Taichung 413310, Taiwan
    Graduate School of Technological and Vocational Education, National Yunlin University of Science and Technology, Yunlin 64002, Taiwan)

Abstract

As the Coronavirus disease 2019 (COVID-19) epidemic spreads all over the world, governments of various countries are actively adopting epidemic prevention measures to curb the spread of the disease. However, colleges and universities are one of the most likely places for cluster infections. The main reason is that college students have frequent social activities, and many students come from different countries, which may very likely cause college campuses to be entry points of disease transmission. Therefore, this study proposes a framework of epidemic prevention work, and further explores the importance and priority of epidemic prevention works. First of all, 32 persons in charge of epidemic prevention from various universities in Taiwan were invited to jointly formulate a campus epidemic prevention framework and determined 5 dimensions and 36 epidemic prevention works/measures/criteria. Next, Bayesian best worst method (BWM) was used to generate a set of optimal group criteria weights. This method can not only integrate the opinions of multiple experts, but also effectively reduce the complexity of expert interviews to obtain more reliable results. The results show that the five most important measures for campus epidemic prevention are the establishment of a campus epidemic prevention organization, comprehensive disinfection of the campus environment, maintenance of indoor ventilation, proper isolation of contacts with confirmed cases, and management of immigration regulations for overseas students. This study provides colleges and universities around the world to formulate anti-epidemic measures to effectively reduce the probability of COVID-19 transmission on campuses to protect students’ right to education.

Suggested Citation

  • Wan-Chi Jackie Hsu & Huai-Wei Lo & Chin-Cheng Yang, 2021. "The Formulation of Epidemic Prevention Work of COVID-19 for Colleges and Universities: Priorities and Recommendations," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:4:p:2081-:d:499825
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/4/2081/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/4/2081/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lili-Ann Wolff, 2020. "Sustainability Education in Risks and Crises: Lessons from Covid-19," Sustainability, MDPI, vol. 12(12), pages 1-6, June.
    2. Sen Guo & Wenyue Zhang & Xiao Gao, 2020. "Business Risk Evaluation of Electricity Retail Company in China Using a Hybrid MCDM Method," Sustainability, MDPI, vol. 12(5), pages 1-21, March.
    3. Luigi Cirrincione & Fulvio Plescia & Caterina Ledda & Venerando Rapisarda & Daniela Martorana & Raluca Emilia Moldovan & Kelly Theodoridou & Emanuele Cannizzaro, 2020. "COVID-19 Pandemic: Prevention and Protection Measures to Be Adopted at the Workplace," Sustainability, MDPI, vol. 12(9), pages 1-18, April.
    4. Ocampo, Lanndon & Yamagishi, Kafferine, 2020. "Modeling the lockdown relaxation protocols of the Philippine government in response to the COVID-19 pandemic: An intuitionistic fuzzy DEMATEL analysis," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
    5. Mohammadi, Majid & Rezaei, Jafar, 2020. "Bayesian best-worst method: A probabilistic group decision making model," Omega, Elsevier, vol. 96(C).
    6. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Halit Serdar Saner & Melih Yucesan & Muhammet Gul, 2022. "A Bayesian BWM and VIKOR-based model for assessing hospital preparedness in the face of disasters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(2), pages 1603-1635, March.
    2. Göçmen Polat, Elifcan & Yücesan, Melih & Gül, Muhammet, 2023. "A comparative framework for criticality assessment of strategic raw materials in Turkey," Resources Policy, Elsevier, vol. 82(C).
    3. Md Shihab Shakur & Maishat Lubaba & Binoy Debnath & A. B. M. Mainul Bari & M. Azizur Rahman, 2024. "Exploring the Challenges of Industry 4.0 Adoption in the FMCG Sector: Implications for Resilient Supply Chain in Emerging Economy," Logistics, MDPI, vol. 8(1), pages 1-28, March.

    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. Gul, Muhammet & Yucesan, Melih, 2022. "Performance evaluation of Turkish Universities by an integrated Bayesian BWM-TOPSIS model," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    2. Yana Duan & Yang Sun & Yu Zhang & Xiaoqi Fan & Qinghuan Dong & Sen Guo, 2021. "Risk Evaluation of Electric Power Grid Investment in China Employing a Hybrid Novel MCDM Method," Mathematics, MDPI, vol. 9(5), pages 1-22, February.
    3. Sarfaraz Hashemkhani Zolfani & Ramin Bazrafshan & Fatih Ecer & Çağlar Karamaşa, 2022. "The Suitability-Feasibility-Acceptability Strategy Integrated with Bayesian BWM-MARCOS Methods to Determine the Optimal Lithium Battery Plant Located in South America," Mathematics, MDPI, vol. 10(14), pages 1-18, July.
    4. Vieira, Fabiana C. & Ferreira, Fernando A.F. & Govindan, Kannan & Ferreira, Neuza C.M.Q.F. & Banaitis, Audrius, 2022. "Measuring urban digitalization using cognitive mapping and the best worst method (BWM)," Technology in Society, Elsevier, vol. 71(C).
    5. Ayyildiz, Ertugrul, 2022. "Fermatean fuzzy step-wise Weight Assessment Ratio Analysis (SWARA) and its application to prioritizing indicators to achieve sustainable development goal-7," Renewable Energy, Elsevier, vol. 193(C), pages 136-148.
    6. Fahim, Patrick B.M. & Rezaei, Jafar & Montreuil, Benoit & Tavasszy, Lorant, 2022. "Port performance evaluation and selection in the Physical Internet," Transport Policy, Elsevier, vol. 124(C), pages 83-94.
    7. Burak Can Altay & Abdullah Erdem Boztas & Abdullah Okumuş & Muhammet Gul & Erkan Çelik, 2023. "How Will Autonomous Vehicles Decide in Case of an Accident? An Interval Type-2 Fuzzy Best–Worst Method for Weighting the Criteria from Moral Values Point of View," Sustainability, MDPI, vol. 15(11), pages 1-20, June.
    8. Wu, Qun & Liu, Xinwang & Qin, Jindong & Zhou, Ligang & Mardani, Abbas & Deveci, Muhammet, 2022. "An integrated multi-criteria decision-making and multi-objective optimization model for socially responsible portfolio selection," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    9. Dilupa Nakandala & Yung Po Tsang & Henry Lau & Carman Ka Man Lee, 2022. "An Industrial Blockchain-Based Multi-Criteria Decision Framework for Global Freight Management in Agricultural Supply Chains," Mathematics, MDPI, vol. 10(19), pages 1-23, September.
    10. Lin, Xueshan & Huang, Tao & Bompard, Ettore & Wang, Beibei & Zheng, Yaxian, 2023. "Ex-ante market power evaluation and mitigation in day-ahead electricity market considering market maturity levels," Energy, Elsevier, vol. 278(C).
    11. Göçmen Polat, Elifcan & Yücesan, Melih & Gül, Muhammet, 2023. "A comparative framework for criticality assessment of strategic raw materials in Turkey," Resources Policy, Elsevier, vol. 82(C).
    12. Carman-Ka-Man Lee & Lucas Lui & Yung-Po Tsang, 2021. "Formulation and Prioritization of Sustainable New Product Design in Smart Glasses Development," Sustainability, MDPI, vol. 13(18), pages 1-18, September.
    13. Zsombor Szádoczki & Sándor Bozóki & Patrik Juhász & Sergii V. Kadenko & Vitaliy Tsyganok, 2023. "Incomplete pairwise comparison matrices based on graphs with average degree approximately 3," Annals of Operations Research, Springer, vol. 326(2), pages 783-807, July.
    14. Vineet Kaushik & Shobha Tewari, 2023. "Modeling Opportunity Indicators Fostering Social Entrepreneurship: A Hybrid Delphi and Best-Worst Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 168(1), pages 667-698, August.
    15. Jian Wang & Jin-Chun Huang & Shan-Lin Huang & Gwo-Hshiung Tzeng & Ting Zhu, 2021. "Improvement Path for Resource-Constrained Cities Identified Using an Environmental Co-Governance Assessment Framework Based on BWM-mV Model," IJERPH, MDPI, vol. 18(9), pages 1-30, May.
    16. Murad, C.A. & Bellinello, M.M. & Silva, A.J. & Netto, A. Caminada & de Souza, G.F.M. & Nabeta, S.I., 2022. "A novel methodology employed for ranking and consolidating performance indicators in holding companies with multiple power plants based on multi-criteria decision-making method," Operations Research Perspectives, Elsevier, vol. 9(C).
    17. Bai, Chunguang & Zhu, Qingyun & Sarkis, Joseph, 2021. "Joint blockchain service vendor-platform selection using social network relationships: A multi-provider multi-user decision perspective," International Journal of Production Economics, Elsevier, vol. 238(C).
    18. Jurgita Kuizinaitė & Mangirdas Morkūnas & Artiom Volkov, 2023. "Assessment of the Most Appropriate Measures for Mitigation of Risks in the Agri-Food Supply Chain," Sustainability, MDPI, vol. 15(12), pages 1-18, June.
    19. Gupta, Himanshu & Yadav, Avinash Kumar & Kusi-Sarpong, Simonov & Khan, Sharfuddin Ahmed & Sharma, Shashi Chandra, 2022. "Strategies to overcome barriers to innovative digitalisation technologies for supply chain logistics resilience during pandemic," Technology in Society, Elsevier, vol. 69(C).
    20. Adabavazeh, Nazila & Nikbakht, Mehrdad & Tirkolaee, Erfan Babaee, 2023. "Identifying and prioritizing resilient health system units to tackle the COVID-19 pandemic," Socio-Economic Planning Sciences, Elsevier, vol. 85(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:gam:jsusta:v:13:y:2021:i:4:p:2081-:d:499825. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.